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2. Discussion on the paper 'Statistical contributions to bioinformatics: Design, modelling, structure learning and integration' by Jeffrey S. Morris and Veerabhadran Baladandayuthapani
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Hae-Won Uh, Jeanine J. Houwing-Duistermaat, and Arief Gusnanto
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0301 basic medicine ,Statistics and Probability ,Computer science ,0206 medical engineering ,02 engineering and technology ,Machine learning ,computer.software_genre ,Bioinformatics ,FDR ,glycomics ,Glycomics ,03 medical and health sciences ,Directed networks ,protein structure ,Structure learning ,derived traits ,business.industry ,Protein structure prediction ,filtering ,Important research ,030104 developmental biology ,Artificial intelligence ,Statistics, Probability and Uncertainty ,business ,computer ,020602 bioinformatics ,Differential (mathematics) - Abstract
Bioinformatics is an important research area for statisticians. This discussion provides some additional topics to the paper, namely on statistical contributions to detect differential expressed genes, for protein structure prediction, and for the analysis of highly correlated features in Glycomics datasets.
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- 2017
3. Introduction to the JBCB Special Issue on Selected Papers from BICOB-2020.
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Eulenstein, Oliver, Ding, Qin, and Al-Mubaid, Hisham
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COMPUTATIONAL biology ,PROTEIN structure ,EMAIL - Abstract
Like every year, the BICOB organizing committee prepared a special issue of a bioinformatics journal for papers selected from among the best papers in BICOB2020. This year, the Journal of Bioinformatics and Computational Biology (JBCB) graciously agreed to a special issue for selected best papers of BICOB-2020. Published 27 February 2021 The 2020 International Conference on Bioinformatics and Computational Biology, BICOB-2020, was the 12th edition of this conference. [Extracted from the article]
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- 2021
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4. Folding of a peptide continuum: Semiotic approach to protein folding.
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Lacková, Ľudmila
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PROTEIN folding ,PROTEIN structure ,PAPER arts ,CELL physiology - Abstract
In this paper I attempt to study the notion of "folding of a semiotic continuum" in a direction of a possible application to the biological processes (the process of protein folding). More specifically, the process of obtaining protein structures (protein folding) is compared in this paper to the folding of a semiotic continuum. Consequently, peptide chain is presented as a continuous line potential to be formed (folded) in order to create functional units. The functional units are protein structures having certain function in the cell or organism (semiotic agents). Moreover, protein folding is analyzed in terms of tension between syntax and semantics. [ABSTRACT FROM AUTHOR]
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- 2020
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5. ResidueFinder: extracting individual residue mentions from protein literature.
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Becker, Ton E and Jakobsson, Eric
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AMINO acid sequence ,KEYWORD searching ,PROTEIN structure ,MOLECULAR biology ,TEXT files - Abstract
Background: The revolution in molecular biology has shown how protein function and structure are based on specific sequences of amino acids. Thus, an important feature in many papers is the mention of the significance of individual amino acids in the context of the entire sequence of the protein. MutationFinder is a widely used program for finding mentions of specific mutations in texts. We report on augmenting the positive attributes of MutationFinder with a more inclusive regular expression list to create ResidueFinder, which finds mentions of native amino acids as well as mutations. We also consider parameter options for both ResidueFinder and MutationFinder to explore trade-offs between precision, recall, and computational efficiency. We test our methods and software in full text as well as abstracts. Results: We find there is much more variety of formats for mentioning residues in the entire text of papers than in abstracts alone. Failure to take these multiple formats into account results in many false negatives in the program. Since MutationFinder, like several other programs, was primarily tested on abstracts, we found it necessary to build an expanded regular expression list to achieve acceptable recall in full text searches. We also discovered a number of artifacts arising from PDF to text conversion, which we wrote elements in the regular expression library to address. Taking into account those factors resulted in high recall on randomly selected primary research articles. We also developed a streamlined regular expression (called "cut") which enables a several hundredfold speedup in both MutationFinder and ResidueFinder with only a modest compromise of recall. All regular expressions were tested using expanded F-measure statistics, i.e., we compute F
β for various values of where the larger the value of β the more recall is weighted, the smaller the value of β the more precision is weighted. Conclusions: ResidueFinder is a simple, effective, and efficient program for finding individual residue mentions in primary literature starting with text files, implemented in Python, and available in SourceForge.net. The most computationally efficient versions of ResidueFinder could enable creation and maintenance of a database of residue mentions encompassing all articles in PubMed. [ABSTRACT FROM AUTHOR]- Published
- 2021
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6. AI-Driven Deep Learning Techniques in Protein Structure Prediction.
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Chen, Lingtao, Li, Qiaomu, Nasif, Kazi Fahim Ahmad, Xie, Ying, Deng, Bobin, Niu, Shuteng, Pouriyeh, Seyedamin, Dai, Zhiyu, Chen, Jiawei, and Xie, Chloe Yixin
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MACHINE learning ,PROTEIN structure prediction ,COMPUTATIONAL intelligence ,PROTEIN structure ,PROTEIN models ,DEEP learning - Abstract
Protein structure prediction is important for understanding their function and behavior. This review study presents a comprehensive review of the computational models used in predicting protein structure. It covers the progression from established protein modeling to state-of-the-art artificial intelligence (AI) frameworks. The paper will start with a brief introduction to protein structures, protein modeling, and AI. The section on established protein modeling will discuss homology modeling, ab initio modeling, and threading. The next section is deep learning-based models. It introduces some state-of-the-art AI models, such as AlphaFold (AlphaFold, AlphaFold2, AlphaFold3), RoseTTAFold, ProteinBERT, etc. This section also discusses how AI techniques have been integrated into established frameworks like Swiss-Model, Rosetta, and I-TASSER. The model performance is compared using the rankings of CASP14 (Critical Assessment of Structure Prediction) and CASP15. CASP16 is ongoing, and its results are not included in this review. Continuous Automated Model EvaluatiOn (CAMEO) complements the biennial CASP experiment. Template modeling score (TM-score), global distance test total score (GDT_TS), and Local Distance Difference Test (lDDT) score are discussed too. This paper then acknowledges the ongoing difficulties in predicting protein structure and emphasizes the necessity of additional searches like dynamic protein behavior, conformational changes, and protein–protein interactions. In the application section, this paper introduces some applications in various fields like drug design, industry, education, and novel protein development. In summary, this paper provides a comprehensive overview of the latest advancements in established protein modeling and deep learning-based models for protein structure predictions. It emphasizes the significant advancements achieved by AI and identifies potential areas for further investigation. [ABSTRACT FROM AUTHOR]
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- 2024
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7. Protein loop structure prediction by community-based deep learning and its application to antibody CDR H3 loop modeling.
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Woo, Hyeonuk, Kim, Yubeen, and Seok, Chaok
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PROTEIN structure prediction ,DEEP learning ,PROTEIN structure ,PROTEIN content of food ,PROTEIN engineering ,IMMUNOGLOBULINS - Abstract
As of now, more than 60 years have passed since the first determination of protein structures through crystallography, and a significant portion of protein structures can be predicted by computers. This is due to the groundbreaking enhancement in protein structure prediction achieved through neural network training utilizing extensive sequence and structure data. However, substantial challenges persist in structure prediction due to limited data availability, with antibody structure prediction standing as one such challenge. In this paper, we propose a novel neural network architecture that effectively enables structure prediction by reflecting the inherent combinatorial nature involved in protein structure formation. The core idea of this neural network architecture is not solely to track and generate a single structure but rather to form a community of multiple structures and pursue accurate structure prediction by exchanging information among community members. Applying this concept to antibody CDR H3 loop structure prediction resulted in improved structure sampling. Such an approach could be applied in the structural and functional studies of proteins, particularly in exploring various physiological processes mediated by loops. Moreover, it holds potential in addressing various other types of combinatorial structure prediction and design problems. Author summary: In this paper, we propose a new architecture that aims to improve upon protein structure prediction algorithms like AlphaFold or RoseTTAFold by considering the combinatorial nature of protein structure formation. Such an architecture, reflecting the physical principles of nature, is expected to yield beneficial results, particularly in scenarios with limited structure and sequence information. Named ComMat, this architecture does not focus on a single structure but rather on a set of multiple structures—a community—simultaneously. In this process, combinatorial exploration of protein structure is encouraged through information exchange among community members. ComMat is an instance that integrates this idea within the structure module of AlphaFold. Applying ComMat to antibody CDR H3 loop structure prediction yielded outstanding results in structure sampling and prediction when tested on the IgFold set and compared with IgFold and AlphaFold-Multimer. It confirmed that improved structure sampling stems from effective structural exploration. The proposed concept here could potentially be used in the development of various other combinatorial protein structure prediction and protein design methods. [ABSTRACT FROM AUTHOR]
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- 2024
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8. Crystal structure and molecular dynamics of human POLDIP2, a multifaceted adaptor protein in metabolism and genome stability
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Dana C. Thomas, Klaudia K. Maruszczak, Christopher D.O. Cooper, Anastasija A. Kulik, Richard J. Bingham, Naomi L. A. Nabi, and Martin Carr
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Circular dichroism ,Full‐Length Papers ,Protein domain ,POLDIP2 ,DNA polymerase ,Crystallography, X-Ray ,Biochemistry ,Genomic Instability ,Protein–protein interaction ,03 medical and health sciences ,Protein structure ,Protein Domains ,Full‐Length Paper ,PCNA ,Humans ,protein structure ,Molecular Biology ,030304 developmental biology ,0303 health sciences ,Chemistry ,Genome, Human ,Binding protein ,030302 biochemistry & molecular biology ,DNA replication ,Signal transducing adaptor protein ,Nuclear Proteins ,PDIP38 ,Biophysics ,PrimPol ,Linker - Abstract
Polymerase δ‐interacting protein 2 (POLDIP2, PDIP38) is a multifaceted, “moonlighting” protein, involved in binding protein partners from many different cellular processes, including mitochondrial metabolism and DNA replication and repair. How POLDIP2 interacts with many different proteins is unknown. Towards this goal, we present the crystal structure of POLDIP2 to 2.8 Å, which exhibited a compact two‐domain β‐strand‐rich globular structure, confirmed by circular dichroism and small angle X‐ray scattering approaches. POLDIP2 comprised canonical DUF525 and YccV domains, but with a conserved domain linker packed tightly, resulting in an “extended” YccV module. A central channel was observed, which we hypothesize could influence structural changes potentially mediated by redox conditions, following observation of a modified cysteine residue in the channel. Unstructured regions were rebuilt by ab initio modelling to generate a model of full‐length POLDIP2. Molecular dynamics simulations revealed a highly dynamic N‐terminal region tethered to the YccV‐domain by an extended linker, potentially facilitating interactions with distal binding partners. Models of POLDIP2 complexed with two of its partners, PrimPol and PCNA, indicated that dynamic flexibility of the POLDIP2 N‐terminus and loop regions likely mediate protein interactions., PDB Code(s): 6Z9C
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- 2021
9. Artificial intelligence for template-free protein structure prediction: a comprehensive review.
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Mufassirin, M. M. Mohamed, Newton, M. A. Hakim, and Sattar, Abdul
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PROTEIN structure prediction ,ARTIFICIAL intelligence ,PROTEIN structure ,AMINO acid sequence ,KNOWLEDGE gap theory ,DRUG discovery - Abstract
Protein structure prediction (PSP) is a grand challenge in bioinformatics, drug discovery, and related fields. PSP is computationally challenging because of an astronomically large conformational space to be searched and an unknown very complex energy function to be minimised. To obtain a given protein's structure, template-based PSP approaches adopt a similar protein's known structure, while template-free PSP approaches work when no similar protein's structure is known. Currently, proteins with known structures are greatly outnumbered by proteins with unknown structures. Template-free PSP has obtained significant progress recently via machine learning and search-based optimisation approaches. However, very accurate structures for complex proteins are yet to be achieved at a level suitable for effective drug design. Moreover, ab initio prediction of a protein's structure only from its amino acid sequence remains unsolved. Furthermore, the number of protein sequences with unknown structures is growing rapidly. Hence, to make further progress in PSP, more sophisticated and advanced artificial intelligence (AI) approaches are needed. However, getting involved in PSP research is difficult for AI researchers because of the lack of a comprehensive understanding of the whole problem, along with the background and the literature of all related sub-problems. Unfortunately, existing PSP review papers cover PSP research at a very high level and only some parts of PSP and only from a particular singular viewpoint. Using a systematic approach, this review paper provides a comprehensive survey of the state-of-the-art template-free PSP research to fill this knowledge gap. Moreover, covering required PSP preliminaries and computational formulations, this paper presents PSP research from AI perspectives, discusses the challenges, provides our commentaries, and outlines future research directions. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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10. Functional Peptides from Yak Milk Casein: Biological Activities and Structural Characteristics.
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Wang, Wen, Liang, Qi, Zhao, Baotang, Chen, Xuhui, and Song, Xuemei
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PEPTIDES ,AMINO acid sequence ,YAK ,PROTEIN structure ,PROTEOMICS ,CASEINS ,ANGIOTENSIN converting enzyme ,MILK proteins - Abstract
The average content of casein in yak milk is 40.2 g/L. Casein can be degraded by enzymatic digestion or food processing to produce abundant degradation peptides. International researchers have studied the degradation peptides of yak milk casein by using multiple techniques and methods, such as in vitro activity tests, cellular experiments, proteomics, bioinformatics, etc., and found that the degradation peptides have a wide range of functional activities that are beneficial to the human body, such as angiotensin-converting enzyme (ACE) inhibitory, antioxidant, anti-inflammatory, antidiabetic, antimicrobial, anticancer, and immunomodulatory activities, etc., and it has been proved that the types and strengths of functional activities are closely related to the structural characteristics of the peptides. This paper describes the characteristics of yak milk proteins, the functional activities, and mechanism of action of degraded peptides. Based on the types of functional activities of yak milk casein degradation peptides, we classified and elucidated the effects of structural factors, such as peptide molecular weight, peptide length, amino acid sequence, physicochemical properties, electrical charge, hydrophobicity, spatial conformation, chain length, and the type of enzyme on these activities. It reveals the great potential of yak milk casein degradation peptides as functional active peptide resources and as auxiliary treatments for diseases. It also provides important insights for analyzing yak casein degradation peptide activity and exploring high-value utilization. [ABSTRACT FROM AUTHOR]
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- 2024
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11. Artificial intelligence in fusion protein three‐dimensional structure prediction: Review and perspective.
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Kumar, Himansu and Kim, Pora
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PROTEIN structure prediction ,CHIMERIC proteins ,PROTEIN structure ,ARTIFICIAL intelligence ,CHROMOSOMAL rearrangement - Abstract
Recent advancements in artificial intelligence (AI) have accelerated the prediction of unknown protein structures. However, accurately predicting the three‐dimensional (3D) structures of fusion proteins remains a difficult task because the current AI‐based protein structure predictions are focused on the WT proteins rather than on the newly fused proteins in nature. Following the central dogma of biology, fusion proteins are translated from fusion transcripts, which are made by transcribing the fusion genes between two different loci through the chromosomal rearrangements in cancer. Accurately predicting the 3D structures of fusion proteins is important for understanding the functional roles and mechanisms of action of new chimeric proteins. However, predicting their 3D structure using a template‐based model is challenging because known template structures are often unavailable in databases. Deep learning (DL) models that utilize multi‐level protein information have revolutionized the prediction of protein 3D structures. In this review paper, we highlighted the latest advancements and ongoing challenges in predicting the 3D structure of fusion proteins using DL models. We aim to explore both the advantages and challenges of employing AlphaFold2, RoseTTAFold, tr‐Rosetta and D‐I‐TASSER for modelling the 3D structures. Highlights: This review provides the overall pipeline and landscape of the prediction of the 3D structure of fusion protein.This review provides the factors that should be considered in predicting the 3D structures of fusion proteins using AI approaches in each step.This review highlights the latest advancements and ongoing challenges in predicting the 3D structure of fusion proteins using deep learning models.This review explores the advantages and challenges of employing AlphaFold2, RoseTTAFold, tr-Rosetta, and D-I-TASSER to model 3D structures. [ABSTRACT FROM AUTHOR]
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- 2024
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12. MGPPI: multiscale graph neural networks for explainable protein-protein interaction prediction.
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Shiwei Zhao, Zhenyu Cui, Gonglei Zhang, Yanlong Gong, and Lingtao Su
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CONVOLUTIONAL neural networks ,GRAPH neural networks ,ARTIFICIAL neural networks ,BINDING sites ,PROTEIN structure - Abstract
Protein-Protein Interactions (PPIs) involves in various biological processes, which are of significant importance in cancer diagnosis and drug development. Computational based PPI prediction methods are more preferred due to their low cost and high accuracy. However, existing protein structure based methods are insufficient in the extraction of protein structural information. Furthermore, most methods are less interpretable, which hinder their practical application in the biomedical field. In this paper, we propose MGPPI, which is a Multiscale graph convolutional neural network model for PPI prediction. By incorporating multiscale module into the Graph Neural Network (GNN) and constructing multi convolutional layers, MGPPI can effectively capture both local and global protein structure information. For model interpretability, we introduce a novel visual explanation method named Gradient Weighted interaction Activation Mapping (Grad-WAM), which can highlight key binding residue sites. We evaluate the performance of MGPPI by comparing with state-of-the-arts methods on various datasets. Results shows that MGPPI outperforms other methods significantly and exhibits strong generalization capabilities on the multispecies dataset. As a practical case study, we predicted the binding affinity between the spike (S) protein of SARS-COV-2 and the human ACE2 receptor protein, and successfully identified key binding sites with known binding functions. Key binding sites mutation in PPIs can affect cancer patient survival statues. Therefore, we further verified Grad-WAM highlighted residue sites in separating patients survival groups in several different cancer type datasets. According to our results, some of the highlighted residues can be used as biomarkers in predicting patients survival probability. All these results together demonstrate the high accuracy and practical application value of MGPPI. Our method not only addresses the limitations of existing approaches but also can assists researchers in identifying crucial drug targets and help guide personalized cancer treatment. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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13. Prediction of protein secondary structure by the improved TCN-BiLSTM-MHA model with knowledge distillation.
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Zhao, Lufei, Li, Jingyi, Zhan, Weiqiang, Jiang, Xuchu, and Zhang, Biao
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PROTEIN structure prediction ,DEEP learning ,AMINO acid sequence ,PROTEIN structure ,DRUG development ,PROTEIN folding - Abstract
Secondary structure prediction is a key step in understanding protein function and biological properties and is highly important in the fields of new drug development, disease treatment, bioengineering, etc. Accurately predicting the secondary structure of proteins helps to reveal how proteins are folded and how they function in cells. The application of deep learning models in protein structure prediction is particularly important because of their ability to process complex sequence information and extract meaningful patterns and features, thus significantly improving the accuracy and efficiency of prediction. In this study, a combined model integrating an improved temporal convolutional network (TCN), bidirectional long short-term memory (BiLSTM), and a multi-head attention (MHA) mechanism is proposed to enhance the accuracy of protein prediction in both eight-state and three-state structures. One-hot encoding features and word vector representations of physicochemical properties are incorporated. A significant emphasis is placed on knowledge distillation techniques utilizing the ProtT5 pretrained model, leading to performance improvements. The improved TCN, achieved through multiscale fusion and bidirectional operations, allows for better extraction of amino acid sequence features than traditional TCN models. The model demonstrated excellent prediction performance on multiple datasets. For the TS115, CB513 and PDB (2018–2020) datasets, the prediction accuracy of the eight-state structure of the six datasets in this paper reached 88.2%, 84.9%, and 95.3%, respectively, and the prediction accuracy of the three-state structure reached 91.3%, 90.3%, and 96.8%, respectively. This study not only improves the accuracy of protein secondary structure prediction but also provides an important tool for understanding protein structure and function, which is particularly applicable to resource-constrained contexts and provides a valuable tool for understanding protein structure and function. [ABSTRACT FROM AUTHOR]
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- 2024
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14. Location Is Everything: Influence of His-Tag Fusion Site on Properties of Adenylosuccinate Synthetase from Helicobacter pylori.
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Mišković, Marija Zora, Wojtyś, Marta, Winiewska-Szajewska, Maria, Wielgus-Kutrowska, Beata, Matković, Marija, Domazet Jurašin, Darija, Štefanić, Zoran, Bzowska, Agnieszka, and Leščić Ašler, Ivana
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HELICOBACTER pylori ,CIRCULAR dichroism ,LIGHT scattering ,ENZYME kinetics ,BIOCHEMICAL substrates ,FLUORIMETRY - Abstract
The requirement for fast and dependable protein purification methods is constant, either for functional studies of natural proteins or for the production of biotechnological protein products. The original procedure has to be formulated for each individual protein, and this demanding task was significantly simplified by the introduction of affinity tags. Helicobacter pylori adenylosuccinate synthetase (AdSS) is present in solution in a dynamic equilibrium of monomers and biologically active homodimers. The addition of the His
6 -tag on the C-terminus (C-His-AdSS) was proven to have a negligible effect on the characteristics of this enzyme. This paper shows that the same enzyme with the His6 -tag fused on its N-terminus (N-His-AdSS) has a high tendency to precipitate. Circular dichroism and X-ray diffraction studies do not detect any structural change that could explain this propensity. However, the dynamic light scattering, differential scanning fluorimetry, and analytical ultracentrifugation measurements indicate that the monomer of this construct is prone to aggregation, which shifts the equilibrium towards the insoluble precipitant. In agreement, enzyme kinetics measurements showed reduced enzyme activity, but preserved affinity for the substrates, in comparison with the wild-type and C-His-AdSS. The presented results reinforce the notion that testing the influence of the tag on protein properties should not be overlooked. [ABSTRACT FROM AUTHOR]- Published
- 2024
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15. Millisecond mix-and-quench crystallography (MMQX) enables time-resolved studies of PEPCK with remote data collection
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M.J. McLeod, David Moreau, J.A. Clinger, Robert E. Thorne, and Todd Holyoak
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Materials science ,millisecond mix-and-quench crystallography ,enzymology ,macromolecular substances ,Biochemistry ,law.invention ,Protein structure ,enzyme mechanisms ,law ,structural biology ,General Materials Science ,protein structure ,x-ray crystallography ,X-ray crystallography ,Millisecond ,Data collection ,Crystallography ,Protein dynamics ,Time resolution ,General Chemistry ,Condensed Matter Physics ,Research Papers ,Synchrotron ,structure determination ,Time resolved crystallography ,QD901-999 ,time-resolved crystallography ,protein dynamics ,Phosphoenolpyruvate carboxykinase - Abstract
Improvements in cryo-trapping technology enable single-crystal time-resolved crystallography of an enzyme with 40 ms time resolution., Time-resolved crystallography of biomolecules in action has advanced rapidly as methods for serial crystallography have improved, but the large number of crystals and the complex experimental infrastructure that are required remain serious obstacles to its widespread application. Here, millisecond mix-and-quench crystallography (MMQX) has been developed, which yields millisecond time-resolved data using far fewer crystals and routine remote synchrotron data collection. To demonstrate the capabilities of MMQX, the conversion of oxaloacetic acid to phosphoenolpyruvate by phosphoenolpyruvate carboxykinase (PEPCK) is observed with a time resolution of 40 ms. By lowering the entry barrier to time-resolved crystallography, MMQX should enable a broad expansion in structural studies of protein dynamics.
- Published
- 2021
16. Cryo‐electron Microscopy Imaging of Alzheimer's Amyloid‐beta 42 Oligomer Displayed on a Functionally and Structurally Relevant Scaffold
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Daniel P. Farrell, Thorsten B. Blum, Frank DiMaio, Jinming Wu, Jan Pieter Abrahams, and Jinghui Luo
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Amyloid ,Amyloid beta ,Cryo-electron microscopy ,Peptide ,Oligomer ,Catalysis ,law.invention ,chemistry.chemical_compound ,03 medical and health sciences ,Protein structure ,0302 clinical medicine ,law ,Alzheimer Disease ,Humans ,Research Articles ,030304 developmental biology ,chemistry.chemical_classification ,0303 health sciences ,Amyloid beta-Peptides ,biology ,electron microscopy ,Chemistry ,Protein Structures | Hot Paper ,Cryoelectron Microscopy ,General Chemistry ,General Medicine ,Aβ42 oligomer ,3. Good health ,α-hemolysin ,Membrane ,protein structures ,biology.protein ,Biophysics ,Electron microscope ,030217 neurology & neurosurgery ,Research Article - Abstract
Amyloid‐β peptide (Aβ) oligomers are pathogenic species of amyloid aggregates in Alzheimer's disease. Like certain protein toxins, Aβ oligomers permeabilize cellular membranes, presumably through a pore formation mechanism. Owing to their structural and stoichiometric heterogeneity, the structure of these pores remains to be characterized. We studied a functional Aβ42‐pore equivalent, created by fusing Aβ42 to the oligomerizing, soluble domain of the α‐hemolysin (αHL) toxin. Our data reveal Aβ42‐αHL oligomers to share major structural, functional, and biological properties with wild‐type Aβ42‐pores. Single‐particle cryo‐EM analysis of Aβ42‐αHL oligomers (with an overall 3.3 Å resolution) reveals the Aβ42‐pore region to be intrinsically flexible. The Aβ42‐αHL oligomers will allow many of the features of the wild‐type amyloid oligomers to be studied that cannot be otherwise, and may be a highly specific antigen for the development of immuno‐base diagnostics and therapies., A functional and structural Aβ42‐oligomer equivalent, created by fusing Aβ42 to the oligomerizing, soluble domain of the α‐hemolysin (αHL) toxin, shares major structural, functional, and biological properties with Alzheimer's wild‐type Aβ42 oligomers. Cryo‐EM studies reveal that the αHL‐displayed oligomers structurally remain in a well‐defined stoichiometry, providing a stable mimetic antigen for the development of conformation‐specific antibodies.
- Published
- 2021
17. Cyclophilin OsCYP20‐2 with a novel variant integrates defense and cell elongation for chilling response in rice
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Qian Qian, Zhi-Yong Wang, Ge Qiang, Ming-Yi Bai, Bo Wang, Yuxiang Weng, Wei Luo, Yuan Zhao, Yunyuan Xu, Yuanyuan Zhang, Shanshan Li, Yuda Niu, and Kang Chong
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0106 biological sciences ,0301 basic medicine ,chilling tolerance ,Chloroplasts ,Physiology ,Mutant ,Plant Science ,01 natural sciences ,03 medical and health sciences ,OsCYP20‐2 ,Cyclophilins ,Protein structure ,OsFSD2 ,medicine ,cell elongation ,Cyclophilin ,Plant Proteins ,chemistry.chemical_classification ,Reactive oxygen species ,Oryza sativa ,Full Paper ,Cell growth ,Research ,food and beverages ,Oryza ,Full Papers ,Adaptation, Physiological ,Cell biology ,Chloroplast ,Cold Temperature ,030104 developmental biology ,medicine.anatomical_structure ,chemistry ,SLR1 ,Nucleus ,010606 plant biology & botany - Abstract
Summary Coordinating stress defense and plant growth is a survival strategy for adaptation to different environments that contains a series of processes, such as, cell growth, division and differentiation. However, little is known about the coordination mechanism for protein conformation change.A cyclophilin OsCYP20‐2 with a variant interacts with SLENDER RICE1 (SLR1) and OsFSD2 in the nucleus and chloroplasts, respectively, to integrate chilling tolerance and cell elongation in rice (Oryza sativa) (FSD2, Fe-superoxide dismutase 2).Mass spectrum assay showed that OsNuCYP20‐2 localized at the nucleus (nuclear located OsCYP20‐2) was a new variant of OsCYP20‐2 that truncated 71 amino‐acid residues in N‐terminal. The loss‐of function OsCYP20‐2 mutant showed sensitivity to chilling stress with accumulation of extra reactive oxygen species (ROS). In chloroplasts, the full‐length OsCYP20‐2 promotes OsFSD2 forming homodimers which enhance its activity, eliminating the accumulation of ROS under chilling stress. However, the mutant had shorter epidermal cells in comparison with wild‐type Hwayoung (HY). In the nucleus, OsCYP20‐2 caused conformation change of SLR1 to promote its degradation for cell elongation.Our data reveal a cyclophilin with a variant with dual‐localization in chloroplasts and the nucleus, which mediate chilling tolerance and cell elongation.
- Published
- 2019
18. Capturing structural changes of the S1 to S2 transition of photosystem II using time-resolved serial femtosecond crystallography
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Hisashi Naitow, Takashi Nomura, Michihiro Suga, Siu Kit Chan, Shinichiro Yonekura, Taiki Motomura, Eriko Nango, Yasufumi Umena, Takahiro Yamane, Yasumasa Joti, Hongjie Li, Michihiro Sugahara, Mamoru Suzuki, So Iwata, Takanori Nakane, Fusamichi Akita, Tetsunari Kimura, Shigeki Owada, Yoshiki Nakajima, Minoru Kubo, Kensuke Tono, Rie Tanaka, Jian Ren Shen, Yoshinori Matsuura, and Tetsuya Masuda
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Materials science ,Photosystem II ,membrane proteins ,Electron ,Reaction intermediate ,010402 general chemistry ,01 natural sciences ,Biochemistry ,03 medical and health sciences ,Protein structure ,Molecule ,General Materials Science ,serial crystallography ,030304 developmental biology ,0303 health sciences ,Crystallography ,molecular movies ,photosystem II ,General Chemistry ,time-resolved serial crystallography ,Condensed Matter Physics ,Research Papers ,0104 chemical sciences ,Volumetric flow rate ,QD901-999 ,Femtosecond ,protein structures ,X-ray free-electron lasers ,Excitation - Abstract
A method for determining the sample flow rate and concomitant light condition in time-resolved serial femtosecond crystallography is developed to analyze the intermediate-state structures of photosystem II., Photosystem II (PSII) catalyzes light-induced water oxidation through an Si-state cycle, leading to the generation of di-oxygen, protons and electrons. Pump–probe time-resolved serial femtosecond crystallography (TR-SFX) has been used to capture structural dynamics of light-sensitive proteins. In this approach, it is crucial to avoid light contamination in the samples when analyzing a particular reaction intermediate. Here, a method for determining a condition that avoids light contamination of the PSII microcrystals while minimizing sample consumption in TR-SFX is described. By swapping the pump and probe pulses with a very short delay between them, the structural changes that occur during the S1-to-S2 transition were examined and a boundary of the excitation region was accurately determined. With the sample flow rate and concomitant illumination conditions determined, the S2-state structure of PSII could be analyzed at room temperature, revealing the structural changes that occur during the S1-to-S2 transition at ambient temperature. Though the structure of the manganese cluster was similar to previous studies, the behaviors of the water molecules in the two channels (O1 and O4 channels) were found to be different. By comparing with the previous studies performed at low temperature or with a different delay time, the possible channels for water inlet and structural changes important for the water-splitting reaction were revealed.
- Published
- 2021
19. Improvement of Selenomonas ruminantium β-xylosidase thermal stability by replacing buried free cysteines via site directed mutagenesis.
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Dehnavi, Ehsan, Moeini, Soheila, Akbarzadeh, Ali, Dabirmanesh, Bahareh, Siadat, Seyed Omid Ranaei, and Khajeh, Khosro
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THERMAL stability , *CIRCULAR dichroism , *PAPER pulp , *XYLOSE , *TERTIARY structure , *FLUORESCENCE spectroscopy , *PROTEIN structure , *LACTOGLOBULINS - Abstract
β-xylosidase is an essential enzyme for breakdown of xylan to d -xylose. It has a significant potential application value for medicine, food, paper and pulp, and biofuel industries. Due to the negative consequences caused by buried free cysteine residues, mutational substitution of such residues is often accompanied by a notable increase in thermal stability. To characterize the role of cysteine residues in the structure, function and stability of Selenomonas ruminantium β- d -Xylosidase (SXA), we prepared and evaluated wild-type and four cysteines- deficient SXA proteins. Buried cysteine residues were replaced with. In comparison with the wild-type, the Km values of the mutants remained relatively constant while their kcat values decreased. The C101V and C286V displayed higher thermal stability than the wild-type at 55 and 60 °C. Conformational changes of the secondary and tertiary structure as derived from circular dichroism and fluorescence spectroscopy revealed that changing a buried cysteine to a hydrophobic residue could lead to an increase in thermal stability with minimal perturbation of the wild-type protein structure. In addition to experimental methods, the stability of WT SXA and C101V and C286V mutants at 333 K was also studied by MD simulation. Our theoretical data had a good agreement with the experimental results. [ABSTRACT FROM AUTHOR]
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- 2019
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20. Nonstructural protein 7 and 8 complexes of SARS‐CoV‐2
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Cheng Chen, Li Li, Jun He, Dan Su, and Changhui Zhang
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Models, Molecular ,Protein Conformation ,viruses ,Full‐Length Papers ,Protein domain ,RNA-dependent RNA polymerase ,Biology ,Viral Nonstructural Proteins ,medicine.disease_cause ,Crystallography, X-Ray ,Biochemistry ,SARS‐CoV‐2 ,nsp7 ,03 medical and health sciences ,Protein structure ,nsp8 ,Protein Domains ,Transcription (biology) ,COVID‐19 ,medicine ,Humans ,Molecular Biology ,030304 developmental biology ,Coronavirus ,0303 health sciences ,nsp7+8 complex ,Coronavirus RNA-Dependent RNA Polymerase ,SARS-CoV-2 ,030302 biochemistry & molecular biology ,COVID-19 ,Virology ,Viral replication ,Nucleic acid ,Protein Multimerization ,Viral genome replication - Abstract
The pandemic outbreak of coronavirus disease 2019 (COVID‐19) across the world has led to millions of infection cases and caused a global public health crisis. Current research suggests that SARS‐CoV‐2 is a highly contagious coronavirus that spreads rapidly through communities. To understand the mechanisms of viral replication, it is imperative to investigate coronavirus viral replicase, a huge protein complex comprising up to 16 viral nonstructural and associated host proteins, which is the most promising antiviral target for inhibiting viral genome replication and transcription. Recently, several components of the viral replicase complex in SARS‐CoV‐2 have been solved to provide a basis for the design of new antiviral therapeutics. Here, we report the crystal structure of the SARS‐CoV‐2 nsp7+8 tetramer, which comprises two copies of each protein representing nsp7's full‐length and the C‐terminus of nsp8 owing to N‐terminus proteolysis during the process of crystallization. We also identified a long helical extension and highly flexible N‐terminal domain of nsp8, which is preferred for interacting with single‐stranded nucleic acids., PDB Code(s): 7DCD
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- 2021
21. How Similar Are Proteins and Origami?
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Azulay, Hay, Lutaty, Aviv, and Qvit, Nir
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PROTEIN folding ,ORIGAMI ,PROTEIN structure ,PROTEINS ,PROTEIN models ,CYTOSKELETAL proteins - Abstract
Protein folding and structural biology are highly active disciplines that combine basic research in various fields, including biology, chemistry, physics, and computer science, with practical applications in biomedicine and nanotechnology. However, there are still gaps in the understanding of the detailed mechanisms of protein folding, and protein structure-function relations. In an effort to bridge these gaps, this paper studies the equivalence of proteins and origami. Research on proteins and origami provides strong evidence to support the use of origami folding principles and mechanical models to explain aspects of proteins formation and function. Although not identical, the equivalence of origami and proteins emerges in: (i) the folding processes, (ii) the shape and structure of proteins and origami models, and (iii) the intrinsic mechanical properties of the folded structures/models, which allows them to synchronically fold/unfold and effectively distribute forces to the whole structure. As a result, origami can contribute to the understanding of various key protein-related mechanisms and support the design of de novo proteins and nanomaterials. [ABSTRACT FROM AUTHOR]
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- 2022
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22. Intelligent Alignment Monitoring Method for Tortilla Processing Based on Machine Vision.
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Sun, Yerong and Yi, Kechuan
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COMPUTER vision ,CORN flour ,NOODLES ,TORTILLAS ,WHEAT proteins ,FOOD industry ,PROTEIN structure - Abstract
As people pay more and more attention to a healthy diet, it has become a consensus to eat more coarse grains. The development of its edible value is of great significance for a healthy human diet and has attracted the attention of many scholars and food processing companies. However, due to the differences in protein composition and structure between corn flour and wheat protein, it is difficult to form a network structure during processing, and the viscoelasticity and flexibility are poor. Based on this, this paper proposes a machine vision-based noodle positioning monitoring method to achieve noodle alignment monitoring in the noodle processing process. First, the images are captured by binocular cameras and preprocessed. Further, feature detection and matching algorithms are used to recover the pose information between binocular cameras, and then the recognition targets are matched. Finally, noodle alignment monitoring during noodle processing is achieved. Experiments show that the detection accuracy of the method proposed in this paper is much higher than the traditional manual detection, which can improve the noodle quality and reduce labor costs. [ABSTRACT FROM AUTHOR]
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- 2023
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23. The susceptibility of disulfide bonds towards radiation damage may be explained by S⋯O interactions
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Pinak Chakrabarti, Jesmita Dhar, Manfred S. Weiss, Shubhra Ghosh Dastidar, and Rajasri Bhattacharyya
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S⋯O interactions ,030303 biophysics ,disulfide bonds ,Photochemistry ,Biochemistry ,03 medical and health sciences ,Electron transfer ,Protein structure ,Nucleophile ,NBO ,General Materials Science ,lcsh:Science ,030304 developmental biology ,0303 health sciences ,Hydrogen bond ,Chemistry ,quantum-chemical calculations ,General Chemistry ,Condensed Matter Physics ,electron transfer ,Research Papers ,s...o interactions ,radiation damage ,Electrophile ,lcsh:Q ,Protein crystallization ,Macromolecule ,Natural bond orbital - Abstract
Irradiation of proteins with intense X-ray radiation generates specific structural and chemical alterations, such as metal-ion reduction, reduction of disulfide bonds and decarboxylation reactions. An analysis of a set of disulfide bonds in known structures suggests that the most susceptible disulfide bonds feature a carbonyl O atom positioned along the extension of the S—S bond vector, forming a stabilizing S⋯O interaction, which upon irradiation leads to polarization of the disulfide bond and its eventual reduction., Radiation-induced damage to protein crystals during X-ray diffraction data collection is a major impediment to obtaining accurate structural information on macromolecules. Some of the specific impairments that are inflicted upon highly brilliant X-ray irradiation are metal-ion reduction, disulfide-bond cleavage and a loss of the integrity of the carboxyl groups of acidic residues. With respect to disulfide-bond reduction, previous results have indicated that not all disulfide bridges are equally susceptible to damage. A careful analysis of the chemical environment of disulfide bonds in the structures of elastase, lysozyme, acetylcholinesterase and other proteins suggests that S—S bonds which engage in a close contact with a carbonyl O atom along the extension of the S—S bond vector are more susceptible to reduction than the others. Such an arrangement predisposes electron transfer to occur from the O atom to the disulfide bond, leading to its reduction. The interaction between a nucleophile and an electrophile, akin to hydrogen bonding, stabilizes protein structures, but it also provides a pathway of electron transfer to the S—S bond, leading to its reduction during exposure of the protein crystal to an intense X-ray beam. An otherwise stabilizing interaction can thus be the cause of destabilization under the condition of radiation exposure.
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- 2020
24. Induced DNA bending by unique dimerization of HigA antitoxin
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Bong-Jin Lee, Do-Hee Kim, Sung Jean Park, Chinar Pathak, Hyo Jung Kim, Hyejin Yoon, and Jin Young Park
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Operator (biology) ,Stereochemistry ,Dimer ,Biochemistry ,complex mixtures ,Mycobacterium tuberculosis ,03 medical and health sciences ,chemistry.chemical_compound ,Protein structure ,NMR spectroscopy ,General Materials Science ,lcsh:Science ,030304 developmental biology ,X-ray crystallography ,0303 health sciences ,TA system ,biology ,030306 microbiology ,antitoxins ,Promoter ,General Chemistry ,HigBA ,DNA ,Condensed Matter Physics ,biology.organism_classification ,Research Papers ,Protein tertiary structure ,structure determination ,chemistry ,protein structures ,lcsh:Q ,Antitoxin - Abstract
The crystal structures of HigA3 antitoxin and DNA-bound HigA3 allow detailed structural insights into the HigBA toxin–antitoxin system of Mycobacterium tuberculosis. The unique dimerization of HigA3 induces DNA bending., The bacterial toxin–antitoxin (TA) system regulates cell growth under various environmental stresses. Mycobacterium tuberculosis, the causative pathogen of tuberculosis (TB), has three HigBA type II TA systems with reverse gene organization, consisting of the toxin protein HigB and labile antitoxin protein HigA. Most type II TA modules are transcriptionally autoregulated by the antitoxin itself. In this report, we first present the crystal structure of the M. tuberculosis HigA3 antitoxin (MtHigA3) and MtHigA3 bound to its operator DNA complex. We also investigated the interaction between MtHigA3 and DNA using NMR spectroscopy. The MtHigA3 antitoxin structure is a homodimer that contains a structurally well conserved DNA-binding domain at the N-terminus and a dimerization domain at the C-terminus. Upon comparing the HigA homologue structures, a distinct difference was found in the C-terminal region that possesses the β-lid, and diverse orientations of two helix–turn–helix (HTH) motifs from HigA homologue dimers were observed. The structure of MtHigA3 bound to DNA reveals that the promoter DNA is bound to two HTH motifs of the MtHigA3 dimer presenting 46.5° bending, and the distance between the two HTH motifs of each MtHigA3 monomer was increased in MtHigA3 bound to DNA. The β-lid, which is found only in the tertiary structure of MtHigA3 among the HigA homologues, causes the formation of a tight dimerization network and leads to a unique arrangement for dimer formation that is related to the curvature of the bound DNA. This work could contribute to the understanding of the HigBA system of M. tuberculosis at the atomic level and may contribute to the development of new antibiotics for TB treatment.
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- 2020
25. Census of halide-binding sites in protein structures
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Mayya Uspenskaya, Dmitrii Usoltsev, Albert Guskov, Andrey V. Kajava, Rostislav K. Skitchenko, Centre de recherche en Biologie Cellulaire (CRBM), Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université Montpellier 1 (UM1), and Molecular Dynamics
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Bromides ,Statistics and Probability ,Stereochemistry ,Coordination number ,Halide ,FLUORIDE ,IODINE ,Biochemistry ,03 medical and health sciences ,0302 clinical medicine ,Protein structure ,PHOTOSYSTEM-II ,Side chain ,THYROID-HORMONES ,Moiety ,CRYSTAL-STRUCTURES ,Binding site ,Molecular Biology ,030304 developmental biology ,0303 health sciences ,Binding Sites ,Chemistry ,MOLECULAR-MECHANISMS ,CHLORIDE CHANNELS ,Proteins ,Censuses ,computer.file_format ,Iodides ,BROMIDE ,Protein Data Bank ,Original Papers ,Structural Bioinformatics ,Computer Science Applications ,ANION CHANNEL ,Computational Mathematics ,Computational Theory and Mathematics ,Halogen ,[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ,computer ,EOSINOPHIL PEROXIDASE ,030217 neurology & neurosurgery - Abstract
Motivation Halides are negatively charged ions of halogens, forming fluorides (F−), chlorides (Cl−), bromides (Br−) and iodides (I−). These anions are quite reactive and interact both specifically and non-specifically with proteins. Despite their ubiquitous presence and important roles in protein function, little is known about the preferences of halides binding to proteins. To address this problem, we performed the analysis of halide–protein interactions, based on the entries in the Protein Data Bank. Results We have compiled a pipeline for the quick analysis of halide-binding sites in proteins using the available software. Our analysis revealed that all of halides are strongly attracted by the guanidinium moiety of arginine side chains, however, there are also certain preferences among halides for other partners. Furthermore, there is a certain preference for coordination numbers in the binding sites, with a correlation between coordination numbers and amino acid composition. This pipeline can be used as a tool for the analysis of specific halide–protein interactions and assist phasing experiments relying on halides as anomalous scatters. Availability and implementation All data described in this article can be reproduced via complied pipeline published at https://github.com/rostkick/Halide_sites/blob/master/README.md. Supplementary information Supplementary data are available at Bioinformatics online.
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- 2020
26. A complete compendium of crystal structures for the human SEPT3 subgroup reveals functional plasticity at a specific septin interface
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Ana Paula Ulian de Araújo, J. N. A. Macedo, Diego A. Leonardo, Humberto D'Muniz Pereira, José Brandão-Neto, Napoleão Fonseca Valadares, Richard Charles Garratt, Patricia S. Kumagai, Danielle Karoline Silva do Vale Castro, and Sabrina Matos de Oliveira da Silva
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GTP' ,macromolecular substances ,Septin ,Biochemistry ,03 medical and health sciences ,Protein structure ,septins ,General Materials Science ,Binding site ,protein structure ,lcsh:Science ,filaments ,gtp binding/hydrolysis ,x-ray crystallography ,030304 developmental biology ,Coiled coil ,0303 health sciences ,Chemistry ,030302 biochemistry & molecular biology ,CRISTALOGRAFIA DE RAIOS X ,Biological membrane ,General Chemistry ,Condensed Matter Physics ,Research Papers ,Helix ,Biophysics ,lcsh:Q ,Function (biology) - Abstract
The relationship between GTP binding and hydrolysis on the one hand and septin filament assembly and function on the other has yet to be fully elucidated. The crystal structures of SEPT3 subgroup members bound to either GDP or to a GTP analogue shed light on this question by indicating how the squeezing of one of the inter-subunit interfaces may lead to the exposure of a polybasic region important for membrane association., Human septins 3, 9 and 12 are the only members of a specific subgroup of septins that display several unusual features, including the absence of a C-terminal coiled coil. This particular subgroup (the SEPT3 septins) are present in rod-like octameric protofilaments but are lacking in similar hexameric assemblies, which only contain representatives of the three remaining subgroups. Both hexamers and octamers can self-assemble into mixed filaments by end-to-end association, implying that the SEPT3 septins may facilitate polymerization but not necessarily function. These filaments frequently associate into higher order complexes which associate with biological membranes, triggering a wide range of cellular events. In the present work, a complete compendium of crystal structures for the GTP-binding domains of all of the SEPT3 subgroup members when bound to either GDP or to a GTP analogue is provided. The structures reveal a unique degree of plasticity at one of the filamentous interfaces (dubbed NC). Specifically, structures of the GDP and GTPγS complexes of SEPT9 reveal a squeezing mechanism at the NC interface which would expel a polybasic region from its binding site and render it free to interact with negatively charged membranes. On the other hand, a polyacidic region associated with helix α5′, the orientation of which is particular to this subgroup, provides a safe haven for the polybasic region when retracted within the interface. Together, these results suggest a mechanism which couples GTP binding and hydrolysis to membrane association and implies a unique role for the SEPT3 subgroup in this process. These observations can be accounted for by constellations of specific amino-acid residues that are found only in this subgroup and by the absence of the C-terminal coiled coil. Such conclusions can only be reached owing to the completeness of the structural studies presented here.
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- 2020
27. Confocal Raman Spectral Imaging Study of DAPT, a γ-secretase Inhibitor, Induced Physiological and Biochemical Reponses in Osteosarcoma Cells
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Shuang Wang, Difan Wang, Jie Li, Kaige Wang, Rui Wang, Jie Qin, Qingli He, and Haishan Zeng
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Drug ,animal structures ,media_common.quotation_subject ,Confocal ,Spectrum Analysis, Raman ,Drug Responses ,03 medical and health sciences ,Mice ,0302 clinical medicine ,Protein structure ,Cell Line, Tumor ,Osteosarcoma cells ,medicine ,Animals ,Fragmentation (cell biology) ,media_common ,Confocal Raman microspectral imaging ,Osteosarcoma ,Principal Component Analysis ,Chemistry ,General Medicine ,Dipeptides ,medicine.disease ,Cellular Structures ,Biochemistry ,Apoptosis ,Nucleic acid ,030211 gastroenterology & hepatology ,Amyloid Precursor Protein Secretases ,Drug Screening Assays, Antitumor ,DAPT ,Function (biology) ,Cellular Heterogeneity ,Research Paper - Abstract
Confocal Raman microspectral imaging was adopted to elucidate the cellular drug responses of osteosarcoma cells (OC) to N-[N-(3, 5-difluorophenyl acetyl)-L-alanyl]-sphenylglycine butyl ester (DAPT), a γ-secretase inhibitor, by identifying the drug induced subcellular compositional and structural changes. Methods: Spectral information were acquired from cultured osteosarcoma cells treated with 0 (Untreated Group, UT), 10 (10 μM DAPT treated, 10T), 20 μM (20 μM DAPT treated, 20T) DAPT for 24 hours. A one-way ANOVA and Tukey's honest significant difference (HSD) post hoc multiple test were sequentially applied to address spectral features among three groups. Multivariate algorithms such as K-means clustering analysis (KCA) and Principal component analysis (PCA) were used to highlight the structural and compositional differences, while, univariate imaging was applied to illustrate the distribution pattern of certain cellular components after drug treatment. Results: Major biochemical changes in DAPT-induced apoptosis came from changes in the content and structure of proteins, lipids, and nucleic acids. By adopted multivariate algorithms, the drug induced cellular changes was identified by the morphology and spectral characteristics between untreated cells and treated cells, testified that DAPT mainly acted in the nuclear region. With the increase of the drug concentration, the content of main subcellular compositions, such nucleic acid, protein, and lipid decreased. In an addition, DAPT-induced nuclear fragmentation and apoptosis was depicted by the univariate Raman image of major cellular components (nucleic acids, proteins and lipids). Conclusions: The achieved Raman spectral and imaging results illustrated detailed DAPT-induced subcellular compositional and structural variations as a function of drug dose. Such observations can not only explain drug therapeutic mechanisms of OC DAPT treatment, and also provide new insights for accessing the medicine curative efficacy and predicting prognosis.
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- 2020
28. Structural and kinetic insights into flavin-containing monooxygenase and calponin-homology domains in human MICAL3
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Haemin Lee, Junsoo Kim, Jonghyeon Son, Yong Kwon Lee, Hyun Suk Jung, Donghyuk Shin, Kyunghwan Kim, Junga Park, Minseo Kim, Han-ul Kim, Seong Yun Hwang, Yeon Jin Roh, Sorah Kim, Kwang Yeon Hwang, Aro Lee, and Byung Cheon Lee
- Subjects
Stereochemistry ,actin depolymerization ,Flavoprotein ,Flavin-containing monooxygenase ,Calponin homology domain ,monooxygenases ,Biochemistry ,03 medical and health sciences ,Protein structure ,enzyme mechanisms ,Oxidoreductase ,calponin-homology domain ,mical ,General Materials Science ,refinement ,protein structure ,Cytoskeleton ,Actin ,x-ray crystallography ,030304 developmental biology ,chemistry.chemical_classification ,0303 health sciences ,Crystallography ,biology ,Chemistry ,030302 biochemistry & molecular biology ,General Chemistry ,Monooxygenase ,Condensed Matter Physics ,Research Papers ,structure determination ,QD901-999 ,biology.protein ,f-actin - Abstract
The structure of human MICAL3 provides information about its mechanism., MICAL is an oxidoreductase that participates in cytoskeleton reorganization via actin disassembly in the presence of NADPH. Although three MICALs (MICAL1, MICAL2 and MICAL3) have been identified in mammals, only the structure of mouse MICAL1 has been reported. Here, the first crystal structure of human MICAL3, which contains the flavin-containing monooxygenase (FMO) and calponin-homology (CH) domains, is reported. MICAL3 has an FAD/NADP-binding Rossmann-fold domain for monooxygenase activity like MICAL1. The FMO and CH domains of both MICAL3 and MICAL1 are highly similar in structure, but superimposition of the two structures shows a different relative position of the CH domain in the asymmetric unit. Based on kinetic analyses, the catalytic efficiency of MICAL3 dramatically increased on adding F-actin only when the CH domain was available. However, this did not occur when two residues, Glu213 and Arg530, were mutated in the FMO and CH domains, respectively. Overall, MICAL3 is structurally highly similar to MICAL1, which suggests that they may adopt the same catalytic mechanism, but the difference in the relative position of the CH domain produces a difference in F-actin substrate specificity.
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- 2020
29. A computational approach to the study of interactions between proteins and miR10-b, miR-335, and miR-21 involved in breast cancer
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Yassine Kasmi, Rahma Ait Hammou, and Moulay Mustapha Ennaji
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lcsh:Medicine ,Computational biology ,miR-335 ,gene interactions ,03 medical and health sciences ,0302 clinical medicine ,Protein structure ,breast cancer ,microRNA ,Medicine ,PTEN ,Radiology, Nuclear Medicine and imaging ,Epigenetics ,Gene ,030304 developmental biology ,0303 health sciences ,Messenger RNA ,Original Paper ,biology ,business.industry ,lcsh:R ,Non-coding RNA ,Oncology ,Docking (molecular) ,biology.protein ,miR-21 ,business ,miR-10b ,030217 neurology & neurosurgery - Abstract
MiR-10b, miR-335, and miR-21 are classes of microRNAs (miRNAs) that are overexpressed in breast cancer. Thus, in our study we aimed to test the hypothesis that miRNAs may have direct interactions with proteins and the possibility to inhibit/activate the functional site of proteins and enzymes. For this purpose, we choose three miRNAs involved in breast cancer to study interactions between some proteins and genes, including BRCA1 and PTEN, by processing the docking and matching tools using the Hex8 and HADDOCK server. Mathematically, the hidden Markov models were created by using MATLAB script according to the algorithm in order to study and validate the interactions and bonds between proteins and miRNAs. The main results demonstrate the ability of miR-10b, miR-335, and miR-21 to create direct interactions with 3D protein structures. Furthermore, these results may lead to another pathway of research, i.e. the direct interaction between proteins and their sub-units, to highlight the data obtained previously and demonstrate that proteins may directly interact with ncRNA instead of mRNA. Moreover, our study suggests developing research on different pathways of association proteins-miRNAs as a part of epigenetic extra-nuclear regulation. Taken together, our study provides the first evidence of direct interactions between miRNAs and proteins.
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- 2019
30. Toward G protein-coupled receptor structure-based drug design using X-ray lasers
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Uwe Weierstall, Wei Liu, Rie Tanaka, Anna Shiriaeva, Yasumasa Joti, Gye Won Han, Isabel Moraes, Alexander Batyuk, Eriko Nango, Nadia A. Zatsepin, Chufeng Li, So Iwata, Kensuke Tono, Vadim Cherezov, Benjamin Stauch, Takanori Nakane, Cornelius Gati, and Andrii Ishchenko
- Subjects
serial femtosecond crystallography ,genetic structures ,membrane proteins ,Computational biology ,Biochemistry ,drug discovery ,03 medical and health sciences ,g protein-coupled receptors ,0302 clinical medicine ,Molecular recognition ,Protein structure ,General Materials Science ,protein structure ,lcsh:Science ,030304 developmental biology ,G protein-coupled receptor ,0303 health sciences ,Chemistry ,Drug discovery ,General Chemistry ,equipment and supplies ,Condensed Matter Physics ,Research Papers ,eye diseases ,structure determination ,3. Good health ,x-ray free-electron lasers ,Structure based ,lcsh:Q ,sense organs ,Target protein ,molecular recognition ,030217 neurology & neurosurgery - Abstract
A method is presented for efficient co-crystal structure determination for G protein-coupled receptors taking advantage of serial femtosecond crystallography., Rational structure-based drug design (SBDD) relies on the availability of a large number of co-crystal structures to map the ligand-binding pocket of the target protein and use this information for lead-compound optimization via an iterative process. While SBDD has proven successful for many drug-discovery projects, its application to G protein-coupled receptors (GPCRs) has been limited owing to extreme difficulties with their crystallization. Here, a method is presented for the rapid determination of multiple co-crystal structures for a target GPCR in complex with various ligands, taking advantage of the serial femtosecond crystallography approach, which obviates the need for large crystals and requires only submilligram quantities of purified protein. The method was applied to the human β2-adrenergic receptor, resulting in eight room-temperature co-crystal structures with six different ligands, including previously unreported structures with carvedilol and propranolol. The generality of the proposed method was tested with three other receptors. This approach has the potential to enable SBDD for GPCRs and other difficult-to-crystallize membrane proteins.
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- 2019
31. Structure–activity relationship studies of allosteric inhibitors of EYA2 tyrosine phosphatase
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Jothi Anantharajan, Joma Joy, Alvin W. Hung, CongBao Kang, Weijun Xu, Jeffrey Hill, Elizabeth Yihui Ng, Grace Lin, Rui Zhao, John Wee Liang Kuan, Nithya Baburajendran, Shuang Liu, Heide L. Ford, Yong Yao Loh, Thomas H. Keller, Anna E Jasson, Nur Huda Binte Ahmad, and Yee Khoon Yeo
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Chemistry ,Drug discovery ,Full‐Length Papers ,Phosphatase ,Allosteric regulation ,Intracellular Signaling Peptides and Proteins ,Nuclear Proteins ,Protein tyrosine phosphatase ,Plasma protein binding ,Biochemistry ,Structure-Activity Relationship ,Protein structure ,Structure–activity relationship ,Humans ,Enzyme Inhibitors ,Protein Tyrosine Phosphatases ,Molecular Biology ,Function (biology) - Abstract
Human eyes absent (EYA) proteins possess Tyr phosphatase activity which is critical for numerous cancer and metastasis promoting activities, making it an attractive target for cancer therapy. In this work, we demonstrate that the inhibitor-bound form of EYA2 does not favour binding to Mg2+ , which is indispensable for the Tyr phosphatase activity. We further describe characterization and optimization of this class of allosteric inhibitors. A series of analogues were synthesized to improve potency of the inhibitors and to elucidate structure-activity relationships. Two co-crystal structures confirm the binding modes of this class of inhibitors. Our medicinal chemical, structural, biochemical and biophysical studies provide insight into the molecular interactions of EYA2 with these allosteric inhibitors. The compounds derived from this study are useful for exploring the function of the Tyr phosphatase activity of EYA2 in normal and cancerous cells and serve as reference compounds for screening or developing allosteric phosphatase inhibitors. Finally, the co-crystal structures reported in this study will aid in structure-based drug discovery against EYA2. This article is protected by copyright. All rights reserved.
- Published
- 2021
32. Structural basis of the pleiotropic and specific phenotypic consequences of missense mutations in the multifunctional NAD(P)H:quinone oxidoreductase 1 and their pharmacological rescue
- Author
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Adithi Kannan, Angel L. Pey, Juan Luis Pacheco-Garcia, Pavla Vankova, Rogelio Palomino-Morales, Noel Mesa-Torres, Athi N. Naganathan, Milagros Medina, Ernesto Anoz-Carbonell, Petr Man, and Eduardo Salido
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Medicine (General) ,QH301-705.5 ,Clinical Biochemistry ,Mutation, Missense ,Flavoprotein ,Flavin group ,Quinone oxidoreductase ,medicine.disease_cause ,Biochemistry ,Protein structure ,R5-920 ,medicine ,NAD(P)H Dehydrogenase (Quinone) ,Humans ,Biology (General) ,Ligand binding ,Mutation ,biology ,Chemistry ,Organic Chemistry ,Quinones ,Multifunctional proteins ,Ligand (biochemistry) ,NAD ,Disease-causing mutation ,Phenotype ,Cell biology ,FAD binding ,biology.protein ,Flavin-Adenine Dinucleotide ,NQO1 ,Post-translational modification ,Multifunctional protein ,Protein Binding ,Research Paper - Abstract
JLP-G and ALP were supported by the ERDF/Spanish Ministry of Science, Innovation and Universities-State Research Agency (Grant RTI2018-096246-B-I00) and Consejeria de Economia, Conocimiento, Empresas y Universidad, Junta de Andalucia (Grants P11-CTS-7187 and P18-RT-2413) . NM-T was supported by Aula FUNCANIS-UGR. ES was supported by the ERDF/Spanish Ministry of Science, Innovation and Universities-State Research Agency (Grant SAF2015-69796) . Access to an EU_FT-ICR_MS network installation was funded by the EU Horizon 2020 grant 731077. EA-C and MM were supported by the Spanish Ministry of Science and Innovation-State Research Agency (Grant PID2019-103901 GB-I00) and Gobierno de Aragon-FEDER (Grant E35_20R) . Support of the BioCeV center (CZ.1.05/1.1.00/02.0109) and the CMS/CIISB facility (MEYS CZ-LM2018127) is also gratefully acknowledged. ANN was supported by grants BT/PR26099/BID/7/811/2017 from Department of Biotechnology (DBT, India) and MTR/2019/000392 from Science, Engineering and Research Board (SERB, India) ., The multifunctional nature of human flavoproteins is critically linked to their ability to populate multiple conformational states. Ligand binding, post-translational modifications and disease-associated mutations can reshape this functional landscape, although the structure-function relationships of these effects are not well understood. Herein, we characterized the structural and functional consequences of two mutations (the cancer associated P187S and the phosphomimetic S82D) on different ligation states which are relevant to flavin binding, intracellular stability and catalysis of the disease-associated NQO1 flavoprotein. We found that these mutations affected the stability locally and their effects propagated differently through the protein structure depending both on the nature of the mutation and the ligand bound, showing directional preference from the mutated site and leading to specific phenotypic manifestations in different functional traits (FAD binding, catalysis and inhibition, intracellular stability and pharmacological response to ligands). Our study thus supports that pleitropic effects of disease-causing mutations and phosphorylation events on human flavoproteins may be caused by longrange structural propagation of stability effects to different functional sites that depend on the ligation-state and site-specific perturbations. Our approach can be of general application to investigate these pleiotropic effects at the flavoproteome scale in the absence of high-resolution structural models., ERDF/Spanish Ministry of Science, Innovation and Universities-State Research Agency RTI2018-096246-B-I00- SAF2015-69796, Junta de Andalucia P11-CTS-7187- P18-RT-2413, Aula FUNCANIS-UGR, European Commission 731077, Spanish Ministry of Science and Innovation-State Research Agency PID2019-103901 GB-I00, Gobierno de Aragon-FEDER E35_20R, BioCeV center CZ.1.05/1.1.00/02.0109, CMS/CIISB facility MEYS CZ-LM2018127, Department of Biotechnology (DBT) India BT/PR26099/BID/7/811/2017, Science, Engineering and Research Board (SERB, India) MTR/2019/000392
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- 2021
33. DIProT: A deep learning based interactive toolkit for efficient and effective Protein design.
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Jieling He, Wenxu Wu, and Xiaowo Wang
- Subjects
DEEP learning ,PROTEIN structure ,PROTEIN folding ,PROTEIN engineering ,AMINO acid sequence - Abstract
The protein inverse folding problem, designing amino acid sequences that fold into desired protein structures, is a critical challenge in biological sciences. Despite numerous data-driven and knowledge-driven methods, there remains a need for a user-friendly toolkit that effectively integrates these approaches for in-silico protein design. In this paper, we present DIProT, an interactive protein design toolkit. DIProT leverages a non-autoregressive deep generative model to solve the inverse folding problem, combined with a protein structure prediction model. This integration allows users to incorporate prior knowledge into the design process, evaluate designs in silico, and form a virtual design loop with human feedback. Our inverse folding model demonstrates competitive performance in terms of effectiveness and efficiency on TS50 and CATH4.2 datasets, with promising sequence recovery and inference time. Case studies further illustrate how DIProT can facilitate user-guided protein design. [ABSTRACT FROM AUTHOR]
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- 2024
- Full Text
- View/download PDF
34. Cold Spot SCANNER: Colab Notebook for predicting cold spots in protein–protein interfaces.
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Gurusinghe, Sagara N. S. and Shifman, Julia M.
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SCANNING systems ,PROTEIN-protein interactions ,PROTEIN engineering ,PROTEIN structure ,NOTEBOOKS ,IDENTIFICATION ,GYROTRONS - Abstract
Background: Protein–protein interactions (PPIs) are conveyed through binding interfaces or surface patches on proteins that become buried upon binding. Structural and biophysical analysis of many protein–protein interfaces revealed certain unique features of these surfaces that determine the energetics of interactions and play a critical role in protein evolution. One of the significant aspects of binding interfaces is the presence of binding hot spots, where mutations are highly deleterious for binding. Conversely, binding cold spots are positions occupied by suboptimal amino acids and several mutations in such positions could lead to affinity enhancement. While there are many software programs for identification of hot spot positions, there is currently a lack of software for cold spot detection. Results: In this paper, we present Cold Spot SCANNER, a Colab Notebook, which scans a PPI binding interface and identifies cold spots resulting from cavities, unfavorable charge-charge, and unfavorable charge-hydrophobic interactions. The software offers a Py3DMOL-based interface that allows users to visualize cold spots in the context of the protein structure and generates a zip file containing the results for easy download. Conclusions: Cold spot identification is of great importance to protein engineering studies and provides a useful insight into protein evolution. Cold Spot SCANNER is open to all users without login requirements and can be accessible at: https://colab.research.google.com/github/sagagugit/Cold-Spot-Scanner/blob/main/Cold_Spot_Scanner.ipynb. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
35. Recent processing of peanut protein in food industry: a molecular structure perspective.
- Author
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Zhang, Huayang, Xia, Yunze, Li, Wenhao, Ma, Xia, Chen, Liang, Wang, Dianxuan, and Qu, Chenling
- Subjects
- *
PEANUTS , *MOLECULAR structure , *PROTEIN products industry , *PROTEIN structure , *FOOD industry , *MILK substitutes - Abstract
Summary: Peanuts produce millions of tons of high‐protein peanut meal (after oil extraction) annually that can be used for food. Peanut protein, as a plant‐based protein, is a great alternative to animal protein to address protein deficiencies and rising health problems in the world. It has a high nutritional value, while the globular structure results in poor functional properties, limiting its application. Better functional properties can be obtained through processing and modification. This paper elaborates the nutritional and functional properties of peanut protein and highlights the application of peanut protein in food industry in recent years. Applications for peanut protein include meat and milk substitutes, edible films, nanoparticles, and some new technologies such as electrostatic spinning and three‐dimensional (3D) printing in recent years. This paper could improve people's understanding of the molecular structure of peanut protein and the physicochemical properties associated with the structure changes during processing. It could also contribute to better utilisation of peanut protein, providing more varieties of peanut protein products for the food industry. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
36. Analysis on quantum reinforcement learning algorithms for prediction of protein sequence.
- Author
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Kalpana, R., Sathishkumar, P. J., Shenbagavalli, B., and Subburaj, S.
- Subjects
- *
MACHINE learning , *REINFORCEMENT learning , *AMINO acid sequence , *PROTEIN structure prediction , *DEEP learning , *PROTEIN structure - Abstract
Protein structure expectation is a particularly mind boggling issue that it is frequently assaulted and disintegrated using four distinct levels and they are: 1-D forecast of under- lying highlights along the essential succession of amino acids sequences, 2-D forecast of spatial connections between the sequence of amino acids, 3-D forecast of a tertiary structure of protein and quaternary structure of protein. This paper also try to introduce some assessment tools for finding the accuracy of result from applying ML and DL tools. And try to analyses and compare various algorithms based on deep learning methods verses machine learning methods used for sequence prediction. This paper also examines the turn of events and utilization of concealed Markov model, uphold vector machines, Bayesian techniques, and grouping strategies. This investigation will be helpful in creating future strategies to improve the exactness of protein auxiliary structure expectation. In this paper, also introduce and summarize the problem of quantum essential elements of: (1) Variational auto-encoder (2) GAN, generative adversarial network (3) RNN, recurrent neural (4) CNN, convolutional neural networks protein structure prediction. Later on also summarizes the evolution of predictive algorithms for 1-4D structure of protein from Amino Acid Sequences and summarize the deep learning ideas to prediction of structure of protein and learned algorithms of the last decade. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
37. First National Prevalence in Italian Horse Population and Phylogenesis Highlight a Fourth Sub-Type Candidate of Equine Hepacivirus.
- Author
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Nardini, Roberto, Pacchiarotti, Giulia, Svicher, Valentina, Salpini, Romina, Bellocchi, Maria Concetta, Conti, Raffaella, Sala, Marcello Giovanni, La Rocca, Davide, Carioti, Luca, Cersini, Antonella, Manna, Giuseppe, and Scicluna, Maria Teresa
- Subjects
HORSES ,HORSE breeding ,TERTIARY structure ,PROTEIN structure ,EQUIDAE ,RNA viruses ,DONKEYS ,WILD horses - Abstract
Equine hepacivirus (EqHV, Flaviviridae, hepacivirus) is a small, enveloped RNA virus generally causing sub-clinical hepatitis with occasional fatalities. EqHV is reported in equids worldwide, but for Italy data are limited. To address this, a survey study was set up to estimate prevalence at a national level and among different production categories (equestrian; competition; work and meat; reproduction) and national macro-regions (North, Central, South, and Islands). Data obtained testing 1801 horse serum samples by Real-Time RT PCR were compared within the categories and regions. The NS3 fragment of the PCR-positive samples was sequenced by Sanger protocol for phylogenetic and mutational analysis. The tertiary structure of the NS3 protein was also assessed. The estimated national prevalence was 4.27% [1.97–6.59, 95% CI] and no statistical differences were detected among production categories and macro-regions. The phylogenesis confirmed the distribution in Italy of the three known EqHV subtypes, also suggesting a possible fourth sub-type that, however, requires further confirmation. Mutational profiles that could also affect the NS3 binding affinity to the viral RNA were detected. The present paper demonstrates that EqHV should be included in diagnostic protocols when investigating causes of hepatitis, and in quality control protocols for blood derived products due to its parental transmission. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
38. A two‐armed probe for in‐cell DEER measurements on proteins
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Doris Heinrich, Donny de Bruin, Marcellus Ubbink, Martina Huber, Joeri A. J. Wondergem, Monika Timmer, Mark Overhand, Qing Miao, Anneloes Blok, and Enrico Zurlo
- Subjects
Lysis ,Disulfide Linkage ,spin labels ,010402 general chemistry ,01 natural sciences ,Catalysis ,Dictyostelium discoideum ,law.invention ,Protein structure ,law ,Molecule ,Dictyostelium ,Electron paramagnetic resonance ,biology ,Full Paper ,010405 organic chemistry ,Chemistry ,Protein Structure Analysis ,Organic Chemistry ,Electron Spin Resonance Spectroscopy ,Proteins ,General Chemistry ,Site-directed spin labeling ,Full Papers ,biology.organism_classification ,0104 chemical sciences ,Crystallography ,double electron–electron resonance (DEER) ,protein structures ,gadolinium ,Linker ,EPR spectroscopy - Abstract
The application of double electron‐electron resonance (DEER) with site‐directed spin labeling (SDSL) to measure distances in proteins and protein complexes in living cells puts rigorous restraints on the spin‐label. The linkage and paramagnetic centers need to resist the reducing conditions of the cell. Rigid attachment of the probe to the protein improves precision of the measured distances. Here, three two‐armed GdIII complexes, GdIII‐CLaNP13a/b/c were synthesized. Rather than the disulfide linkage of most other CLaNP molecules, a thioether linkage was used to avoid reductive dissociation of the linker. The doubly GdIII labeled N55C/V57C/K147C/T151C variants of T4Lysozyme were measured by 95 GHz DEER. The constructs were measured in vitro, in cell lysate and in Dictyostelium discoideum cells. Measured distances were 4.5 nm, consistent with results from paramagnetic NMR. A narrow distance distribution and typical modulation depth, also in cell, indicate complete and durable labeling and probe rigidity due to the dual attachment sites., Two armed and ready! A two armed, thus rigid, GdIII‐CLaNP13 probe for double electron–electron resonance (DEER) measurements on proteins can be used to measure nanometer distances in cells with high precision.
- Published
- 2020
39. On the use of side-chain NMR relaxation data to derive structural and dynamical information on proteins: A case study using Hen Lysozyme
- Author
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Wilfred F. van Gunsteren, Lorna J. Smith, and Niels Hansen
- Subjects
Averaging time ,conformation sampling ,nuclear magnetic resonance ,S2 order parameters ,structure refinement ,Thermodynamics ,Crystal structure ,Molecular Dynamics Simulation ,010402 general chemistry ,01 natural sciences ,Biochemistry ,Protein Structure, Secondary ,Molecular dynamics ,Protein structure ,Side chain ,Animals ,Nuclear Magnetic Resonance, Biomolecular ,Molecular Biology ,Independence (probability theory) ,Physics ,Quantitative Biology::Biomolecules ,Full Paper ,010405 organic chemistry ,Hydrogen bond ,Organic Chemistry ,Rotation around a fixed axis ,Hydrogen Bonding ,Full Papers ,Symmetry (physics) ,Protein Structure, Tertiary ,0104 chemical sciences ,Molecular Medicine ,Muramidase ,Chickens - Abstract
Values of S2CH and S2NH order parameters derived from NMR relaxation measurements on proteins cannot be used straightforwardly to determine protein structure because they cannot be related to a single protein structure, but are defined in terms of an average over a conformational ensemble. Molecular dynamics simulation can generate a conformational ensemble and thus can be used to restrain S2CH and S2NH order parameters towards experimentally derived target values S2CH (exp) and S2NH (exp). Application of S2CH and S2NH order-parameter restraining MD simulation to bond vectors in 63 side chains of the protein hen egg white lysozyme using 51 S2CH (exp) target values and 28 S2NH (exp) target values shows that a conformational ensemble compatible with the experimentally derived data can be obtained by using this technique. It is observed that S2CH order-parameter restraining of C-H bonds in methyl groups is less reliable than S2NH order-parameter restraining because of the possibly less valid assumptions and approximations used to derive experimental S2CH (exp) values from NMR relaxation measurements and the necessity to adopt the assumption of uniform rotational motion of methyl C-H bonds around their symmetry axis and of the independence of these motions from each other. The restrained simulations demonstrate that side chains on the protein surface are highly dynamic. Any hydrogen bonds they form and that appear in any of four different crystal structures, are fluctuating with short lifetimes in solution., ChemBioChem, 22 (6), ISSN:1439-4227, ISSN:1439-7633
- Published
- 2020
40. Predicting the Real‐Valued Inter‐Residue Distances for Proteins
- Author
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Wenze Ding and Haipeng Gong
- Subjects
Computer science ,General Chemical Engineering ,General Physics and Astronomy ,Medicine (miscellaneous) ,02 engineering and technology ,010402 general chemistry ,01 natural sciences ,Biochemistry, Genetics and Molecular Biology (miscellaneous) ,Multiclass classification ,Protein structure ,General Materials Science ,lcsh:Science ,Residue (complex analysis) ,Full Paper ,business.industry ,Deep learning ,General Engineering ,deep learning ,Protein structure prediction ,Full Papers ,021001 nanoscience & nanotechnology ,protein inter‐residue distance ,Regression ,0104 chemical sciences ,protein structure prediction ,lcsh:Q ,Artificial intelligence ,real‐valued distance prediction ,generative adversarial networks ,0210 nano-technology ,Transfer of learning ,business ,Distance transform ,Algorithm - Abstract
Predicting protein structure from the amino acid sequence has been a challenge with theoretical and practical significance in biophysics. Despite the recent progresses elicited by improved inter‐residue contact prediction, contact‐based structure prediction has gradually reached the performance ceiling. New methods have been proposed to predict the inter‐residue distance, but unanimously by simplifying the real‐valued distance prediction into a multiclass classification problem. Here, a lightweight regression‐based distance prediction method is shown, which adopts the generative adversarial network to capture the delicate geometric relationship between residue pairs and thus could predict the continuous, real‐valued inter‐residue distance rapidly and satisfactorily. The predicted residue distance map allows quick structure modeling by the CNS suite, and the constructed models approach the same level of quality as the other state‐of‐the‐art protein structure prediction methods when tested on CASP13 targets. Moreover, this method can be used directly for the structure prediction of membrane proteins without transfer learning., A lightweight GAN‐based protein inter‐residue distance prediction method is reported. This method is capable of capturing the delicate geometric relationship between residue pairs and thus could predict the continuous, real‐valued distance rapidly and satisfactorily. Pipelined with structure modeling software like the CNS suite, this method could construct protein structure models with the state‐of‐the‐art quality.
- Published
- 2020
41. NMR spectroscopy of the main protease of SARS‐CoV‐2 and fragment‐based screening identify three protein hotspots and an antiviral fragment
- Author
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Florence Leroux, Julie Charton, François-Xavier Cantrelle, Xavier Hanoulle, Sandrine Belouzard, Danai Moschidi, Isabelle Landrieu, Lucile Brier, Jean Dubuisson, Valérie Landry, Emmanuelle Boll, Benoit Deprez, Frédérique Dewitte, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Biologie Structurale Intégrative (ERL 9002 - BSI ), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Médicaments et molécules pour agir sur les Systèmes Vivants - U 1177 (M2SV), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 (CIIL), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS), Projet 3CLPRO-SCREEN-NMR (I-SITE Université Lille Nord-Europe)Institut Pasteur de Lille, HANOULLE, Xavier, Centre National de la Recherche Scientifique (CNRS)-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, and Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)
- Subjects
Protein Conformation ,medicine.medical_treatment ,Drug Evaluation, Preclinical ,[CHIM.THER]Chemical Sciences/Medicinal Chemistry ,01 natural sciences ,Protein structure ,Chlorocebus aethiops ,Coronavirus 3C Proteases ,Research Articles ,[SDV.MP.VIR] Life Sciences [q-bio]/Microbiology and Parasitology/Virology ,0303 health sciences ,biology ,[SDV.BBM.BS]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM] ,Drug discovery ,Chemistry ,fragment screening ,Nuclear magnetic resonance spectroscopy ,General Medicine ,3. Good health ,Protein Structure | Hot Paper ,[SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology ,Research Article ,Stereochemistry ,[SDV.BBM.BS] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Structural Biology [q-bio.BM] ,[CHIM.THER] Chemical Sciences/Medicinal Chemistry ,Allosteric regulation ,Context (language use) ,Microbial Sensitivity Tests ,Cysteine Proteinase Inhibitors ,010402 general chemistry ,Antiviral Agents ,Catalysis ,drug discovery ,Small Molecule Libraries ,03 medical and health sciences ,NMR spectroscopy ,medicine ,Animals ,viruses ,Binding site ,protein structure ,Nuclear Magnetic Resonance, Biomolecular ,Vero Cells ,030304 developmental biology ,Protease ,Binding Sites ,SARS-CoV-2 ,010405 organic chemistry ,Active site ,General Chemistry ,0104 chemical sciences ,biology.protein ,Protein Multimerization - Abstract
The main protease (3CLp) of the SARS‐CoV‐2, the causative agent for the COVID‐19 pandemic, is one of the main targets for drug development. To be active, 3CLp relies on a complex interplay between dimerization, active site flexibility, and allosteric regulation. The deciphering of these mechanisms is a crucial step to enable the search for inhibitors. In this context, using NMR spectroscopy, we studied the conformation of dimeric 3CLp from the SARS‐CoV‐2 and monitored ligand binding, based on NMR signal assignments. We performed a fragment‐based screening that led to the identification of 38 fragment hits. Their binding sites showed three hotspots on 3CLp, two in the substrate binding pocket and one at the dimer interface. F01 is a non‐covalent inhibitor of the 3CLp and has antiviral activity in SARS‐CoV‐2 infected cells. This study sheds light on the complex structure‐function relationships of 3CLp and constitutes a strong basis to assist in developing potent 3CLp inhibitors., We report the liquid‐sate NMR spectroscopy analysis of the dimeric SARS‐CoV‐2 main protease (3CLp), including its backbone assignments, to study its complex conformational regulation. Using fragment‐based NMR screening, we highlighted three hotspots on the protein, two in the substrate binding pocket and one at the dimer interface, and we identified a non‐covalent reversible inhibitor of 3CLp that has antiviral activity in infected cells.
- Published
- 2021
42. Comparative Evaluation of Shape Retrieval Methods on Macromolecular Surfaces: An Application of Computer Vision Methods in Structural Bioinformatics
- Author
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Nathalie Lagarde, Florent Langenfeld, Léa Sirugue, Daniela Craciun, Maxime Maria, Taoufik Labib, Matthieu Montes, and Mickael Machat
- Subjects
Statistics and Probability ,Structure (mathematical logic) ,AcademicSubjects/SCI01060 ,Computer science ,business.industry ,Biochemistry ,Original Papers ,Structural Bioinformatics ,Computer Science Applications ,Comparative evaluation ,Computational Mathematics ,Structural bioinformatics ,Protein sequencing ,Protein structure ,Molecular recognition ,Computational Theory and Mathematics ,Computer vision ,Shape retrieval, Computer Vision, Protein Shape, Structural Bioinformatics, Shape similarity ,Artificial intelligence ,Representation (mathematics) ,Surface protein ,business ,Molecular Biology - Abstract
Motivation The investigation of the structure of biological systems at the molecular level gives insights about their functions and dynamics. Shape and surface of biomolecules are fundamental to molecular recognition events. Characterizing their geometry can lead to more adequate predictions of their interactions. In the present work, we assess the performance of reference shape retrieval methods from the computer vision community on protein shapes. Results Shape retrieval methods are efficient in identifying orthologous proteins and tracking large conformational changes. This work illustrates the interest for the protein surface shape as a higher-level representation of the protein structure that (i) abstracts the underlying protein sequence, structure or fold, (ii) allows the use of shape retrieval methods to screen large databases of protein structures to identify surficial homologs and possible interacting partners and (iii) opens an extension of the protein structure–function paradigm toward a protein structure-surface(s)-function paradigm. Availabilityand implementation All data are available online at http://datasetmachat.drugdesign.fr. Supplementary information Supplementary data are available at Bioinformatics online.
- Published
- 2021
43. Various algorithms of machine learning and deep learning for predicting 1-4D structure of protein from amino acid sequences.
- Author
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Pandey, Atrakesh and Jain, Rekha
- Subjects
AMINO acid sequence ,MACHINE learning ,DEEP learning ,PROTEIN structure ,QUATERNARY structure ,ESSENTIAL amino acids - Abstract
In bioinformatics and computational and frameworks science, AI approaches are ordinarily utilized. The improvement of AI techniques for the forecast of protein structures, perhaps the main issues in primary science and bioinformatics, is explored here. Protein structure expectation is a particularly mind boggling issue that it is frequently assaulted and disintegrated using four distinct levels and they are: 1-D forecast of underlying highlights along the essential succession of amino acids sequences,2-D forecast of spatial connections between the sequence of amino acids, 3-D forecast of a tertiary structure of protein and quaternary structure of protein. Throughout the long term, a different assortment of both managed and solo AI approaches have been applied to take care of these issues and have contributed fundamentally to propelling the best in class expectation of protein structure. In this survey paper tries to introduce some assessment tools for finding the accuracy of result from applying ML and DL tools. We try to analyses and compare various algorithms based on deep learning methods verses machine learning methods used for sequence prediction. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
44. Cloning, expression, and molecular modification of glycoside hydrolase family 5 genes from Thermoascus aurantiacus.
- Author
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Shao, Hongwei
- Subjects
GENE expression ,MOLECULAR cloning ,TRANSMEMBRANE domains ,NUCLEOTIDE sequence ,PROTEIN structure ,GLUCOSIDASES - Abstract
In this paper, a novel bifunctional cellulase gene cel1 was cloned from Thermoascus aurantiacus by PCR and heterologously expressed in Pichia pastoris GS115. Bioinformatics and other related tools were used to compare the nucleotide homology of target genes, and analyze the signal peptide, transmembrane domain, hydrophilicity, secondary and tertiary structure of proteins. It was concluded that cel1 has similar endoglucanase nucleotide sequences and falls under the GH5 family. It was also found that cel1 has nucleotide sequences similar to glucosidase, which can infer that cel1 may have the properties of glucosidase, indicating that cel1 is multifunctional. At the same time, a part of the nucleotide sequence of the gene was removed to obtain a new gene cel2, and after highly efficient heterologous expression, its specific activity was found to be 2.1 times higher. Its enhancement is related to the exposure of the protein's hollow three-dimensional structure. This paper provides good material for exploring the relationship between the structure of bifunctional enzymes and their functions, which lays a solid foundation for further research and applications, and provides useful insight for gene mining of other novel enzymes. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
45. Structural semiology, Peirce, and biolinguistics.
- Author
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Lacková, Ľudmila
- Subjects
STRUCTURAL linguistics ,PROTEIN structure ,MORPHOLOGY ,VALENCE (Chemistry) ,SEMIOTICS - Abstract
Peirce's sign model is introduced as incompatible with structural semiology in the majority of semiotics textbooks. In this paper, I would like to argue against this general polarization of the semiotic discipline. I focus on compatibilities between Lucien Tesnière's syntactic theory (verbal valency) and Peirce's logic of relatives. My main argument is that structural linguistics is not necessarily dyadic, and that Peirce's sign doctrine is perfectly structural. To define the structural approach in Peirce, I analyze the notions of form (structure) and substance in Hjelmslev and Peirce. The aim of my argument is to contribute to attempts to introduce Peirce's theory to the field of linguistics in the hope that such an integration will be beneficiary for general linguistics. To extend and support my argument, I provide some examples from biology where Peirce's theory has been applied. I demonstrate an analogy between the biological structures of proteins and the structure of a sentence with Peirce's own writings. I consequently introduce Peirce as the first structural semiologist and as the first biolinguist. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
46. Structural and mechanistic insight into stem‐loop RNA processing by yeast Pichia stipitis Dicer
- Author
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Satoru Machida, Chen Ying, Fu Qinqin, Chacko Jobichen, Yuren Adam Yuan, Chen Wei, Li Jianwei, and JingRu Chan
- Subjects
Ribonuclease III ,Full‐Length Papers ,Biochemistry ,Protein Structure, Secondary ,Small hairpin RNA ,Fungal Proteins ,03 medical and health sciences ,Structure-Activity Relationship ,Protein structure ,Protein Domains ,Molecular Biology ,030304 developmental biology ,0303 health sciences ,biology ,Chemistry ,030302 biochemistry & molecular biology ,RNA ,RNA, Fungal ,Stem-loop ,Cell biology ,Saccharomycetales ,biology.protein ,Nucleic Acid Conformation ,RNA Cleavage ,Protein Multimerization ,Sequence motif ,Dicer - Abstract
Dicer is a member of the ribonuclease III enzyme family and processes double-stranded RNA into small functional RNAs. The variation in the domain architecture of Dicer among different species whilst preserving its biological dicing function is intriguing. Here, we describe the structure and function of a novel catalytically active RNase III protein, a non-canonical Dicer (PsDCR1), found in budding yeast Pichia stipitis. The structure of the catalytically active region (the catalytic RNase III domain and double-stranded RNA-binding domain 1 [dsRBD1]) of DCR1 showed that RNaseIII domain is structurally similar to yeast RNase III (Rnt1p) but uniquely presents dsRBD1 in a diagonal orientation, forming a catalytic core made of homodimer and large RNA-binding surface. The second dsRNA binding domain at C-terminus, which is absent in Rnt1, enhances the RNA cleavage activity. Although the cleavage pattern of PsDCR1 anchors an apical loop similar to Rnt1, the cleavage activity depended on the sequence motif at the lower stem, not the apical loop, of hairpin RNA. Through RNA sequencing and RNA mutations, we showed that RNA cleavage by PsDCR1 is determined by the stem-loop structure of the RNA substrate, suggesting the possibility that stem-loop RNA-guided gene silencing pathway exists in budding yeast.
- Published
- 2021
47. Multi-conformation representation of Mpro identifies promising candidates for drug repurposing against COVID-19
- Author
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Debarati Paul, Shubhra Ghosh Dastidar, and Debadrita Basu
- Subjects
Drug ,Virtual screening ,Coronavirus disease 2019 (COVID-19) ,Computer science ,Protein Conformation ,media_common.quotation_subject ,Drug Evaluation, Preclinical ,Computational biology ,Molecular dynamics ,Molecular Dynamics Simulation ,010402 general chemistry ,01 natural sciences ,Catalysis ,Inorganic Chemistry ,chemistry.chemical_compound ,Protein structure ,Cangrelor ,0103 physical sciences ,Drug Discovery ,Humans ,Physical and Theoretical Chemistry ,Coronavirus 3C Proteases ,media_common ,MPro ,Original Paper ,010304 chemical physics ,SARS-CoV-2 ,Organic Chemistry ,Representation (systemics) ,Drug Repositioning ,COVID-19 ,0104 chemical sciences ,Computer Science Applications ,COVID-19 Drug Treatment ,Drug repositioning ,Computational Theory and Mathematics ,chemistry ,Lead compound - Abstract
The COVID-19 main protease (Mpro), one of the conserved proteins of the novel coronavirus is crucial for its replication and so is a very lucrative drug target. Till now, there is no drug molecule that has been convincingly identified as the inhibitor of the function of this protein. The current pandemic situation demands a shortcut to quickly reach to a lead compound or a drug, which may not be the best but might serve as an interim solution at least. Following this notion, the present investigation uses virtual screening to find a molecule which is alraedy approved as a drug for some other disease but could be repurposed to inhibit Mpro. The potential of the present method of work to identify such a molecule, which otherwise would have been missed out, lies in the fact that instead of just using the crystallographically identified conformation of the receptor’s ligand binding pocket, molecular dynamics generated ensemble of conformations has been used. It implicitly included the possibilities of “induced-fit” and/or “population shift” mechanisms of ligand fitting. As a result, the investigation has not only identified antiviral drugs like ribavirin, ritonavir, etc., but it has also captured a wide variety of drugs for various other diseases like amrubicin, cangrelor, desmopressin, diosmin, etc. as the potent possibilities. Some of these ligands are versatile to form stable interactions with various different conformations of the receptor and therefore have been statistically surfaced in the investigation. Overall the investigation offers a wide range of compounds for further testing to confirm their scopes of applications to combat the COVID-19 pandemic. Supplementary Information The online version contains supplementary material available at 10.1007/s00894-021-04732-1.
- Published
- 2021
48. Structures of three ependymin-related proteins suggest their function as a hydrophobic molecule binder
- Author
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Jeong Kuk Park, Keon Young Kim, Yeo Won Sim, Yong-In Kim, Jin Kyun Kim, Cheol Lee, Jeongran Han, Chae Un Kim, J. Eugene Lee, and SangYoun Park
- Subjects
0303 health sciences ,General Chemistry ,Condensed Matter Physics ,Research Papers ,Biochemistry ,structure determination ,mammalian ependymin-related protein ,03 medical and health sciences ,0302 clinical medicine ,General Materials Science ,lcsh:Q ,X-ray structure ,ependymin ,protein structure ,UCC1 ,lcsh:Science ,030217 neurology & neurosurgery ,030304 developmental biology ,X-ray crystallography - Abstract
Ependymin-related proteins fold into a dimer using a subunit formed by stacking antiparallel β-sheets and contain a hydrophobic pocket that is found in the similar folds of bacterial VioE and LolA/LolB. As in VioE and LolA/LolB, this hydrophobic pocket may be used to bind hydrophobic molecules., Ependymin was first discovered as a predominant protein in brain extracellular fluid in fish and was suggested to be involved in functions mostly related to learning and memory. Orthologous proteins to ependymin called ependymin-related proteins (EPDRs) have been found to exist in various tissues from sea urchins to humans, yet their functional role remains to be revealed. In this study, the structures of EPDR1 from frog, mouse and human were determined and analyzed. All of the EPDR1s fold into a dimer using a monomeric subunit that is mostly made up of two stacking antiparallel β-sheets with a curvature on one side, resulting in the formation of a deep hydrophobic pocket. All six of the cysteine residues in the monomeric subunit participate in the formation of three intramolecular disulfide bonds. Other interesting features of EPDR1 include two asparagine residues with glycosylation and a Ca2+-binding site. The EPDR1 fold is very similar to the folds of bacterial VioE and LolA/LolB, which also use a similar hydrophobic pocket for their respective functions as a hydrophobic substrate-binding enzyme and a lipoprotein carrier, respectively. A further fatty-acid binding assay using EPDR1 suggests that it indeed binds to fatty acids, presumably via this pocket. Additional interactome analysis of EPDR1 showed that EPDR1 interacts with insulin-like growth factor 2 receptor and flotillin proteins, which are known to be involved in protein and vesicle translocation.
- Published
- 2019
49. Conservation of the structure and function of bacterial tryptophan synthases
- Author
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Grazyna Joachimiak, Boguslaw Nocek, Lance Bigelow, Besnik Bajrami, Robert Jedrzejczak, Matthias Endres, Samantha Wellington, Stephen Johnston, Karolina Michalska, Stewart L. Fisher, Catherine Hatzos-Skintges, Deborah T. Hung, Changsoo Chang, Partha P. Nag, Andrzej Joachimiak, and Jennifer P. Gale
- Subjects
crystal structure ,enzyme inhibitors ,Tryptophan synthase ,medicine.disease_cause ,Biochemistry ,Legionella pneumophila ,drug discovery ,03 medical and health sciences ,enzyme mechanisms ,medicine ,General Materials Science ,tryptophan ,tryptophan synthase ,protein structure ,Francisella tularensis ,Escherichia coli ,030304 developmental biology ,X-ray crystallography ,Indole test ,0303 health sciences ,Crystallography ,biology ,catalysis ,Chemistry ,030302 biochemistry & molecular biology ,Tryptophan ,Pathogenic bacteria ,General Chemistry ,Condensed Matter Physics ,biology.organism_classification ,Research Papers ,allosteric regulation ,structure determination ,Streptococcus pneumoniae ,QD901-999 ,biology.protein ,molecular recognition ,Bacteria - Abstract
The tryptophan synthases from three human pathogens show remarkable structural conservation, but at the same time display local differences in both their catalytic and allosteric sites that may be responsible for the observed differences in catalysis and inhibitor binding. This functional dissimilarity may be exploited in the design of species-specific enzyme inhibitors., Tryptophan biosynthesis is one of the most characterized processes in bacteria, in which the enzymes from Salmonella typhimurium and Escherichia coli serve as model systems. Tryptophan synthase (TrpAB) catalyzes the final two steps of tryptophan biosynthesis in plants, fungi and bacteria. This pyridoxal 5′-phosphate (PLP)-dependent enzyme consists of two protein chains, α (TrpA) and β (TrpB), functioning as a linear αββα heterotetrameric complex containing two TrpAB units. The reaction has a complicated, multistep mechanism resulting in the β-replacement of the hydroxyl group of l-serine with an indole moiety. Recent studies have shown that functional TrpAB is required for the survival of pathogenic bacteria in macrophages and for evading host defense. Therefore, TrpAB is a promising target for drug discovery, as its orthologs include enzymes from the important human pathogens Streptococcus pneumoniae, Legionella pneumophila and Francisella tularensis, the causative agents of pneumonia, legionnaires’ disease and tularemia, respectively. However, specific biochemical and structural properties of the TrpABs from these organisms have not been investigated. To fill the important phylogenetic gaps in the understanding of TrpABs and to uncover unique features of TrpAB orthologs to spearhead future drug-discovery efforts, the TrpABs from L. pneumophila, F. tularensis and S. pneumoniae have been characterized. In addition to kinetic properties and inhibitor-sensitivity data, structural information gathered using X-ray crystallography is presented. The enzymes show remarkable structural conservation, but at the same time display local differences in both their catalytic and allosteric sites that may be responsible for the observed differences in catalysis and inhibitor binding. This functional dissimilarity may be exploited in the design of species-specific enzyme inhibitors.
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- 2019
50. Fatty-acid receptor CD36 functions as a hydrogen sulfide-targeted receptor with its Cys333-Cys272 disulfide bond serving as a specific molecular switch to accelerate gastric cancer metastasisResearch in context
- Author
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Tuvshin Bao, Xiaohui Wang, Yuqi Kang, Junjie Zhang, Shuang Dong, Wei Wang, Rui Wang, Li Chen, Zhirong Wang, Xiaoming Qiu, Qilin Fan, Kekun Wang, Yinfang Hao, Beibei Tao, Yixi Cai, Xinyu Mo, Xutong Li, Zhe Wang, and Shengyue Wang
- Subjects
0301 basic medicine ,CD36 Antigens ,Research paper ,CD36 ,Mutant ,Lysine ,lcsh:Medicine ,Receptors, Odorant ,Metastasis ,Mice ,0302 clinical medicine ,Protein structure ,Cell Movement ,Long chain-fatty acid ,Disulfides ,Hydrogen Sulfide ,Neoplasm Metastasis ,Receptor ,lcsh:R5-920 ,biology ,Chemistry ,H2S ,Fatty Acids ,General Medicine ,Cell biology ,030220 oncology & carcinogenesis ,Heterografts ,lcsh:Medicine (General) ,Nitric Oxide ,General Biochemistry, Genetics and Molecular Biology ,Nrf2 ,Arthropod Proteins ,03 medical and health sciences ,Protein Domains ,Stomach Neoplasms ,Cell Line, Tumor ,medicine ,Animals ,Humans ,Neoplasm Invasiveness ,Cysteine ,Cell Proliferation ,Disulfide bond ,lcsh:R ,Wild type ,medicine.disease ,equipment and supplies ,030104 developmental biology ,biology.protein - Abstract
Background: Hydrogen Sulfide (H2S), a third member of gasotransmitter family along with nitric oxide (NO) and carbon monoxide (CO), exerts a wide range of cellular and molecular actions in our body. There is a large body of evidence suggesting that H2S plays an important role in cancer metastasis; however, the molecular mechanisms of H2S-mediated acceleration of cancer metastasis remain unknown. Methods: We examined the promote effects of H2S on phenotype of gastric cancer (GC) cells (including those of express wild type CD36 and mutant CD36) in vitro and in vivo. GC patients' samples were used for clinical translational significance evaluation. Findings: H2S triggered lipid metabolism reprogramming by significantly up-regulating the expression of the fatty-acid receptor CD36 (CD36) and directly activating CD36 in GC cells. Mechanistically, a disulfide bond located between cysteine (Cys)333 and Cys272 within the CD36 protein structure that was labile to H2S-mediated modification. The long chain-fatty acid (LC-FA) binding pocket was capped by a turn in the CD36 protein, located between helical and sheet structures that were stabilized by the Cys333-Cys272. This limited the secondary binding between LC-FAs and lysine (Lys)334. Breaking the Cys333-Cys272 disulfide bond restored the second LC-FA binding conformation of CD36. Targeting CD36 in vivo blocked H2S-promoted metastasis and improved animal survival. Interpretation: These findings identify that the Cys333-Cys272 disulfide bond disrupted the integrity of the second LC-FA binding conformation of CD36. Therefore, CD36 can directly activate LC-FA access to the cytoplasm by acting as a direct target molecule for H2S. Keywords: H2S, CD36, Disulfide bond, Long chain-fatty acid, Nrf2, Metastasis
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- 2019
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