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The protein S100B is a part of the S100 protein family, which consists of at least 25 calcium-binding proteins. S100B is highly conserved across different species, supporting important biological functions. The protein was shown to play a role in gut microbiota eubiosis and is secreted in human breast milk, suggesting a physiological trophic function in newborn development. This study explores the possible presence of the S100B motif in plant genomes, and of S100B-like immunoreactive material in different plant extracts, opening up potential botanical uses for dietary supplementation. To explore the presence of the S100B motif in plants, a bioinformatic workflow was used. In addition, the immunoreactivity of S100B from vegetable and fruit samples was tested using an ELISA assay. The S100B motif was expected in silico in the genome of different edible plants belonging to the Viridiplantae clade, such as Durio zibethinus or Malus domestica and other medicinal species. S100B-like immunoreactive material was also detected in samples from fruits or leaves. The finding of S100B-like molecules in plants sheds new light on their role in phylogenesis and in the food chain. This study lays the foundation to elucidate the possible beneficial effects of plants or derivatives containing the S100B-like principle and their potential use in nutraceuticals. [ABSTRACT FROM AUTHOR]

ObjectiveEmerging drug resistance in Pseudomonas aeruginosa is of great concern in clinical settings. P. aeruginosa activates its efflux-pump system in order to evade the effect of antibiotics. The current investigation aims to detect MexB genes in P. aeruginosa, their structural and molecular analysis and their impact on antimicrobial susceptibility profiling.MethodsA total of 42 clinical specimens were aseptically collected from hospitalized patients who had underlying infections related to medical implants. Matrix-assisted laser desorption ionization-time of flight (MALDI-ToF) were used for the identification of isolates. The methods used in this study were antibiotic susceptibility profiling, minimum inhibitory concentration (MIC), polymerase chain reaction (PCR), sanger sequencing, phylogenetic analysis, MolProbity score, Ramachandran plot analysis and multiple sequence alignment.ResultsThe highest resistance was shown by P. aeruginosa against cefoperazone (67%), gentamycin and amikacin (66%) each, followed by cefotaxime (64%). The prevalence of multi-drug resistant (MDR) and extensively drug resistant (XDR) was 57% and 12%, respectively. The presence of an active efflux-pump system was indicated by the MexB genes found in most of the resistant isolates (p

The SH2 domains of SHP2 play a crucial role in determining the function of the SHP2 protein. While the folding and binding properties of the isolated NSH2 and CSH2 domains have been extensively studied, there is limited information about the tandem SH2 domains. This study aims to elucidate the folding and binding kinetics of the NSH2-CSH2 tandem domains of SHP2 through rapid kinetic experiments, complementing existing data on the isolated domains. The results indicate that while the domains generally fold and unfold independently, acidic pH conditions induce complex scenarios involving the formation of a misfolded intermediate. Furthermore, a comparison of the binding kinetics of isolated NSH2 and CSH2 domains with the NSH2-CSH2 tandem domains, using peptides that mimic specific portions of Gab2, suggests a dynamic interplay between NSH2 and CSH2 in binding Gab2 that modulate the microscopic association rate constant of the binding reaction. These findings, discussed in the context of previous research on the NSH2 and CSH2 domains, enhance our understanding of the function of the SH2 domain tandem of SHP2. [ABSTRACT FROM AUTHOR]

Optineurin (OPTN) is a multifunctional protein that interacts with a range of proteins to participate in various cellular functions. OPTN is associated with neurodegenerative diseases such as glaucoma and amyotrophic lateral sclerosis. OPTN contains multiple protein domains that enable it to participate in a variety of cellular functions, including NF-κB regulation, membrane transport, exocytosis, vesicular transport, maintenance of Golgi apparatus morphology, cell cycle control, ubiquitination regulation, and autophagy. The diversity in structure and function of OPTN poses challenges for exploring its specific mechanisms in diseases. This article reviews recent literature on OPTN and summarizes the functional roles of various OPTN domains, providing insights and references for further understanding the roles of OPTN in neurodegenerative diseases.

Abstract Background Classification of rare missense variants remains an ongoing challenge in genomic medicine. Evidence of pathogenicity is often sparse, and decisions about how to weigh different evidence classes may be subjective. We used a Bayesian variant classification framework to investigate the performance of variant co-localisation, missense constraint, and aggregating data across paralogous protein domains (“meta-domains”). Methods We constructed a database of all possible coding single nucleotide variants in the human genome and used PFam predictions to annotate structurally-equivalent positions across protein domains. We counted the number of pathogenic and benign missense variants at these equivalent positions in the ClinVar database, calculated a regional constraint score for each meta-domain, and assessed this approach versus existing missense constraint metrics for classifying variant pathogenicity and benignity. Results Alternative pathogenic missense variants at the same amino acid position in the same protein provide strong evidence of pathogenicity (positive likelihood ratio, LR+ = 85). Additionally, clinically annotated pathogenic or benign missense variants at equivalent positions in different proteins can provide moderate evidence of pathogenicity (LR+ = 7) or benignity (LR+ = 5), respectively. Applying these approaches sequentially (through PM5) increases sensitivity for classifying pathogenic missense variants from 27 to 41%. Missense constraint can also provide strong evidence of pathogenicity for some variants, but its absence provides no evidence of benignity. Conclusions We propose using structurally equivalent positions across related protein domains from different genes to augment evidence for variant co-localisation when classifying novel missense variants. Additionally, we advocate adopting a numerical evidence-based approach to integrating diverse data in variant interpretation.

Background: Classification of rare missense variants remains an ongoing challenge in genomic medicine. Evidence of pathogenicity is often sparse, and decisions about how to weigh different evidence classes may be subjective. We used a Bayesian variant classification framework to investigate the performance of variant co-localisation, missense constraint, and aggregating data across paralogous protein domains ("meta-domains"). Methods: We constructed a database of all possible coding single nucleotide variants in the human genome and used PFam predictions to annotate structurally-equivalent positions across protein domains. We counted the number of pathogenic and benign missense variants at these equivalent positions in the ClinVar database, calculated a regional constraint score for each meta-domain, and assessed this approach versus existing missense constraint metrics for classifying variant pathogenicity and benignity. Results: Alternative pathogenic missense variants at the same amino acid position in the same protein provide strong evidence of pathogenicity (positive likelihood ratio, LR+ = 85). Additionally, clinically annotated pathogenic or benign missense variants at equivalent positions in different proteins can provide moderate evidence of pathogenicity (LR+ = 7) or benignity (LR+ = 5), respectively. Applying these approaches sequentially (through PM5) increases sensitivity for classifying pathogenic missense variants from 27 to 41%. Missense constraint can also provide strong evidence of pathogenicity for some variants, but its absence provides no evidence of benignity. Conclusions: We propose using structurally equivalent positions across related protein domains from different genes to augment evidence for variant co-localisation when classifying novel missense variants. Additionally, we advocate adopting a numerical evidence-based approach to integrating diverse data in variant interpretation. [ABSTRACT FROM AUTHOR]

A single-domain protein catenane refers to two mechanically interlocked polypeptide rings that fold synergistically into a compact and integrated structure, which is extremely rare in nature. Here, we report a single-domain protein catenane of dihydrofolate reductase (cat -DHFR). This design was achieved by rewiring the connectivity between secondary motifs to introduce artificial entanglement and synthesis was readily accomplished through a series of programmed and streamlined post-translational processing events in cells without any additional in vitro reactions. The target molecule contained few exogenous motifs and was thoroughly characterized using a combination of ultra-performance liquid chromatography–mass spectrometry, sodium dodecyl sulfate–polyacrylamide gel electrophoresis, protease cleavage experiments and ion mobility spectrometry–mass spectrometry. Compared with the linear control, cat -DHFR retained its catalytic capability and exhibited enhanced stability against thermal or chemical denaturation due to conformational restriction. These results suggest that linear proteins may be converted into their concatenated single-domain counterparts with almost identical chemical compositions, well-preserved functions and elevated stabilities, representing an entirely new horizon in protein science. [ABSTRACT FROM AUTHOR]

The development and improvement of methods for comparing and searching for three-dimensional protein structures remain urgent tasks in modern structural biology. To solve this problem, we developed a new tool, SAFoldNet, which allows for searching, aligning, superimposing, and determining the exact coordinates of fragments of protein structures. The proposed search and alignment tool was built using neural networking. Specifically, we implemented the integrative synergy of neural network predictions and the well-known BLAST algorithm for searching and aligning sequences. The proposed method involves multistage processing, comprising a stage for converting the geometry of protein structures into sequences of a structural alphabet using a neural network, a search stage for forming a set of candidate structures, and a refinement stage for calculating the structural alignment and overlap and evaluating the similarity with the starting structure of the search. The effectiveness and practical applicability of the proposed tool were compared with those of several widely used services for searching and aligning protein structures. The results of the comparisons confirmed that the proposed method is effective and competitive relative to the available modern services. Furthermore, using the proposed approach, a service with a user-friendly web interface was developed, which allows for searching, aligning, and superimposing protein structures; determining the location of protein fragments; mapping onto a protein molecule chain; and providing structural similarity metrices (expected value and root mean square deviation). [ABSTRACT FROM AUTHOR]

Abstract Objectives Pearl millet (Pennisetum glaucum) is a cereal crop that is tolerant to a high temperature, a drought and a nutrient-poor condition. Characterizing pearl millet proteins can help to improve productivity of pearl millet and other crops. Transcription factors in general are proteins that regulate transcription of their target genes and thereby regulate diverse processes. Some transcription factor families in pearl millet were characterized in previous studies, but most of them are not. The objective of the data presented was to characterize amino acid sequences for most transcription factors in pearl millet. Data description Sequences of 2395 pearl millet proteins that have transcription factor-associated domains were extracted. Subcellular and suborganellar localization of these proteins was predicted by MULocDeep. Conserved domains in these sequences were confirmed by CD-Search. These proteins were classified into 85 families on the basis of those conserved domains. A phylogenetic tree including pearl millet proteins and their counterparts in Arabidopsis thaliana and rice was constructed for each of these families. Sequence motifs were identified by MEME for each of these families.

Proteins containing Ly6/uPAR (LU) domains exhibit very diverse biological functions and have broad taxonomic distributions in eukaryotes. In general, they adopt a characteristic three-fingered folding topology with three long loops projecting from a disulfide-rich globular core. The majority of the members of this protein domain family contain only a single LU domain, which can be secreted, glycolipid anchored, or constitute the extracellular ligand binding domain of type-I membrane proteins. Nonetheless, a few proteins contain multiple LU domains, for example, the urokinase receptor uPAR, C4.4A, and Haldisin. In the current review, we will discuss evolutionary aspects of this protein domain family with special emphasis on variations in their consensus disulfide bond patterns. Furthermore, we will present selected cases where missense mutations in LU domain-containing proteins leads to dysfunctional proteins that are causally linked to genesis of human disease.

Tissue inhibitors of metalloproteinases (TIMPs) are natural inhibitors of matrix metalloproteinases (MMPs), enzymes that contribute to cancer and many inflammatory and degenerative diseases. The TIMP N-terminal domain binds and inhibits an MMP catalytic domain, but the role of the TIMP C-terminal domain in MMP inhibition is poorly understood. Here, we employed yeast surface display for directed evolution of full-length human TIMP-1 to develop MMP-3-targeting ultrabinders. By simultaneously incorporating diversity into both domains, we identified TIMP-1 variants that were up to 10-fold improved in binding MMP-3 compared with WT TIMP-1, with inhibition constants (Ki ) in the low picomolar range. Analysis of individual and paired mutations from the selected TIMP-1 variants revealed cooperative effects between distant residues located on the N- and C-terminal TIMP domains, positioned on opposite sides of the interaction interface with MMP-3. Crystal structures of MMP-3 complexes with TIMP-1 variants revealed conformational changes in TIMP-1 near the cooperative mutation sites. Affinity was strengthened by cinching of a reciprocal "tyrosine clasp" formed between the N-terminal domain of TIMP-1 and proximal MMP-3 interface and by changes in secondary structure within the TIMP-1 C-terminal domain that stabilize interdomain interactions and improve complementarity to MMP-3. Our protein engineering and structural studies provide critical insight into the cooperative function of TIMP domains and the significance of peripheral TIMP epitopes in MMP recognition. Our findings suggest new strategies to engineer TIMP proteins for therapeutic applications, and our directed evolution approach may also enable exploration of functional domain interactions in other protein systems.

The cellular isoform of the prion protein (PrPC) serves as precursor to the infectious isoform (PrPSc), and as a cell-surface receptor, which binds misfolded protein oligomers as well as physiological ligands such as Cu2+ ions. PrPC consists of two domains: a flexible N-terminal domain and a structured C-terminal domain. Both the physiological and pathological functions of PrP depend on intramolecular interactions between these two domains, but the specific amino acid residues involved have proven challenging to define. Here, we employ a combination of chemical cross-linking, mass spectrometry, NMR, molecular dynamics simulations, and functional assays to identify residue-level contacts between the N- and C-terminal domains of PrPC. We also determine how these interdomain contacts are altered by binding of Cu2+ ions and by functionally relevant mutations. Our results provide a structural basis for interpreting both the normal and toxic activities of PrP.

We developed a computational approach called Domain-architecture Aware Inference of Orthologs (DAIO) for the analysis of protein orthology by combining phylogenetic and protein domain-architecture information. Using DAIO, we performed a systematic study of the proteomes of all human Herpesviridae species to define Strict Ortholog Groups (SOGs). In addition to assessing the taxonomic distribution for each protein based on sequence similarity, we performed a protein domain-architecture analysis for every protein family and computationally inferred gene duplication events. While many herpesvirus proteins have evolved without any detectable gene duplications or domain rearrangements, numerous herpesvirus protein families do exhibit complex evolutionary histories. Some proteins acquired additional domains (e.g., DNA polymerase), whereas others show a combination of domain acquisition and gene duplication (e.g., betaherpesvirus US22 family), with possible functional implications. This novel classification system of SOGs for human Herpesviridae proteins is available through the Virus Pathogen Resource (ViPR, www.viprbrc.org).

Simple Summary: There are several rare, disrupted genes that underlie neurological dysfunction. Many have not been characterized for their role in brain function or how they work in individual brain cells. The WW domain-containing adaptor with coiled-coil, WAC, gene is one example. Dysfunction of this gene underlies a rare syndrome, DeSanto–Shinawi syndrome (DESSH), with those diagnosed having symptoms including cranio-facial changes, autism, and attention deficit hyperactivity disorder. We sought to understand how the WAC protein functions in brain cells implicated in DESSH in two ways. First, we used available technologies to predict important conserved regions in the protein that may underlie cellular function, including how it localizes to distinct areas of a cell, and further correlated these findings with reported human genetic variants in these regions. These efforts uncovered novel regions in the protein necessary and sufficient for it to localize to the nucleus. Second, we deleted/used key regions of the WAC protein to test whether they were necessary/sufficient to localize WAC to distinct cell regions in brain neurons, and we found that the amino-terminus of the protein fulfilled this function. Moreover, other regions contribute to distinct biological functions of WAC, and this study first highlights these aspects of this unique neurodevelopmental protein. Dysfunction of the WW domain-containing adaptor with coiled-coil, WAC, gene underlies a rare autosomal dominant disorder, DeSanto–Shinawi syndrome (DESSH). DESSH is associated with facial dysmorphia, hypotonia, and cognitive alterations, including attention deficit hyperactivity disorder and autism. How the WAC protein localizes and functions in neural cells is critical to understanding its role during development. To understand the genotype–phenotype role of WAC, we developed a knowledgebase of WAC expression, evolution, human genomics, and structural/motif analysis combined with human protein domain deletions to assess how conserved domains guide cellular distribution. Then, we assessed localization in a cell type implicated in DESSH, cortical GABAergic neurons. WAC contains conserved charged amino acids, phosphorylation signals, and enriched nuclear motifs, suggesting a role in cellular signaling and gene transcription. Human DESSH variants are found within these regions. We also discovered and tested a nuclear localization domain that impacts the cellular distribution of the protein. These data provide new insights into the potential roles of this critical developmental gene, establishing a platform to assess further translational studies, including the screening of missense genetic variants in WAC. Moreover, these studies are essential for understanding the role of human WAC variants in more diverse neurological phenotypes, including autism spectrum disorder. [ABSTRACT FROM AUTHOR]

Abstract Background Alternative splicing can increase the diversity of gene functions by generating multiple isoforms with different sequences and functions. However, the extent to which splicing events have functional consequences remains unclear and predicting the impact of splicing events on protein activity is limited to gene-specific analysis. Results To accelerate the identification of functionally relevant alternative splicing events we created SAPFIR, a predictor of protein features associated with alternative splicing events. This webserver tool uses InterProScan to predict protein features such as functional domains, motifs and sites in the human and mouse genomes and link them to alternative splicing events. Alternative protein features are displayed as functions of the transcripts and splice sites. SAPFIR could be used to analyze proteins generated from a single gene or a group of genes and can directly identify alternative protein features in large sequence data sets. The accuracy and utility of SAPFIR was validated by its ability to rediscover previously validated alternative protein domains. In addition, our de novo analysis of public datasets using SAPFIR indicated that only a small portion of alternative protein domains was conserved between human and mouse, and that in human, genes involved in nervous system process, regulation of DNA-templated transcription and aging are more likely to produce isoforms missing functional domains due to alternative splicing. Conclusion Overall SAPFIR represents a new tool for the rapid identification of functional alternative splicing events and enables the identification of cellular functions affected by a defined splicing program. SAPFIR is freely available at https://bioinfo-scottgroup.med.usherbrooke.ca/sapfir/ , a website implemented in Python, with all major browsers supported. The source code is available at https://github.com/DelongZHOU/SAPFIR .

Abstract Background Both the protein domains and transcript structures influence protein functional variation. The genomic location of both protein domains and transcript structural features can be described using the genomic coordinates of their encoded sequences. However, the coordinates of protein domains and transcriptional features often differ greatly, and it is difficult to view them in combination at the genome-wide level. In this paper, we describe the development of a new tool that allows users to visualize domains and transcript features together, using either built-in or uploaded genome datasets, and export publication-ready figures. Results We developed a user-friendly, independent R package and Shiny web application named “VisProDom”. VisProDom consists of a genome-wide database containing entire annotated transcripts merged with annotated protein domains from the Pfam database. The built-in dataset includes 82 files, which merge genome general feature format (GFF) annotations with rpsblast tabular outputs from protein sequence searches in the Pfam database. Multiple genomes can be simultaneously screened for protein domains or transcript names. VisProDom includes step-by-step introductions and clickable elements for ease of use. Conclusion VisProDom can display hundreds of transcripts alongside protein domains and export figures in a publication-ready format. This makes it a valuable tool for molecular evolution and comparative genomics.

Proteins containing Ly6/uPAR (LU) domains exhibit very diverse biological functions and have broad taxonomic distributions in eukaryotes. In general, they adopt a characteristic three-fingered folding topology with three long loops projecting from a disulfide-rich globular core. The majority of the members of this protein domain family contain only a single LU domain, which can be secreted, glycolipid anchored, or constitute the extracellular ligand binding domain of type-I membrane proteins. Nonetheless, a few proteins contain multiple LU domains, for example, the urokinase receptor uPAR, C4.4A, and Haldisin. In the current review, we will discuss evolutionary aspects of this protein domain family with special emphasis on variations in their consensus disulfide bond patterns. Furthermore, we will present selected cases where missense mutations in LU domain-containing proteins leads to dysfunctional proteins that are causally linked to genesis of human disease.

In this paper, we present an update to the ellipsoid profile algorithm (EP), a simple technique for the measurement of the globularity of protein structures without the calculation of molecular surfaces. The globularity property is understood in this context as the ability of the molecule to fill a minimum volume enclosing ellipsoid (MVEE) that approximates its assumed globular shape. The more of the interior of this ellipsoid is occupied by the atoms of the protein, the better are its globularity metrics. These metrics are derived from the comparison of the volume of the voxelized representation of the atoms and the volume of all voxels that can fit inside that ellipsoid (a uniform unit Å cube lattice). The so-called ellipsoid profile shows how the globularity changes with the distance from the center. Two of its values, the so-called ellipsoid indexes, are used to classify the structure as globular, semi-globular or non-globular. Here, we enhance the workflow of the EP algorithm via an improved outlier detection subroutine based on principal component analysis. It is capable of robust distinguishing between the dense parts of the molecules and, for example, disordered chain fragments fully exposed to the solvent. The PCA-based method replaces the current approach based on kernel density estimation. The improved EP algorithm was tested on 2124 representatives of domain superfamilies from SCOP 2.08. The second part of this work is dedicated to the survey of globularity of 3594 representatives of biological assemblies from molecules currently deposited in the PDB and analyzed by the 3DComplex database (monomers and complexes up to 60 chains). [ABSTRACT FROM AUTHOR]

The nucleotide-binding and leucine-rich repeat (NB-LRR) genes, also known as resistance (R)-genes, play an important role in the activation of immune responses. In recent years, large-scale studies have been performed to highlight the diversification of plant NB-LRR repertories. It is well known that, to provide new functionalities, NB-LRR sequences are subject to duplication, domain fusions and acquisition and other kinds of mutations. Although some mechanisms that govern NB-LRR protein domain adaptations have been uncovered, to retrace the plant-lineage-specific evolution routes of R protein structure, a multi-genome comparative analysis was performed. This study allowed us to define groups of genes sharing homology relationships across different species. It is worth noting that the most populated groups contained well-characterized R proteins. The arsenal profile of such groups was investigated in five botanical families, including important crop species, to underline specific adaptation signatures. In addition, the dissection of 70 NB domains of well-characterized R-genes revealed the NB core motifs from which the three main R protein classes have been diversified. The structural remodeling of domain segments shaped the specific NB-LRR repertoires observed in each plant species. This analysis provided new evolutionary and functional insights on NB protein domain shuffling. Taken together, such findings improved our understanding of the molecular adaptive selection mechanisms occurring at plant R loci. [ABSTRACT FROM AUTHOR]

Protein function prediction is gradually emerging as an essential field in biological and computational studies. Though the latter has clinched a significant footprint, it has been observed that the application of computational information gathered from multiple sources has more significant influence than the one derived from a single source. Considering this fact, a methodology, PFP-GO, is proposed where heterogeneous sources like Protein Sequence, Protein Domain, and Protein-Protein Interaction Network have been processed separately for ranking each individual functional GO term. Based on this ranking, GO terms are propagated to the target proteins. While Protein sequence enriches the sequence-based information, Protein Domain and Protein-Protein Interaction Networks embed structural/functional and topological based information, respectively, during the phase of GO ranking. Performance analysis of PFP-GO is also based on Precision, Recall, and F-Score. The same was found to perform reasonably better when compared to the other existing state-of-art. PFP-GO has achieved an overall Precision, Recall, and F-Score of 0.67, 0.58, and 0.62, respectively. Furthermore, we check some of the top-ranked GO terms predicted by PFP-GO through multilayer network propagation that affect the 3D structure of the genome. The complete source code of PFP-GO is freely available at https://sites.google. com/view/pfp-go/. [ABSTRACT FROM AUTHOR]

In this study, we mined the PDB and created a structural library of 178,465 interfaces that mediate protein–protein/domain–domain interactions. Interfaces involving the same CATH fold(s) were clustered together. Our analysis of the library reveals similarities between chain–chain and domain–domain interactions. The library also illustrates how a single protein fold can interact with multiple folds using similar interfaces. The library is hence a useful resource to study the types of interactions between protein folds. Analyzing the data in the library reveals various interesting aspects of protein–protein and domain–domain interactions such as how proteins belonging to folds that interact with many other folds also have high number of Enzyme Commission terms. These data could be utilized to seek potential binding partners. It can also be utilized to investigate the different ways in which two or more folds interact with one another structurally. We constructed a statistical potential of pair preferences of amino acids across the interface for chain–chain and domain–domain interactions separately. They are quite similar further lending credence to the notion that domain–domain interfaces could be used to study chain–chain interactions. We analyzed protein complexes modeled by AlphaFold2 and RoseTTAFold and noticed that some of the modes of interaction involve folds and interfaces that have not been observed to bind in the PDB. Lastly and importantly, the library includes predicted small molecule‐binding sites at protein–protein interfaces. This has applications as interfaces containing small molecule‐binding sites can be easily targeted to prevent the interaction and perhaps form a part of a therapeutic strategy. [ABSTRACT FROM AUTHOR]

PDZ domains are the most diffused protein–protein interaction modules of the human proteome and are often present in tandem repeats. An example is PDZD2, a protein characterized by the presence of six PDZ domains that undergoes a proteolytic cleavage producing sPDZD2, comprising a tandem of two PDZ domains, namely PDZ5 and PDZ6. Albeit the physiopathological importance of sPDZD2 is well‐established, the interaction with endogenous ligands has been poorly characterized. To understand the determinants of the stability and function of sPDZD2, we investigated its folding pathway. Our data highlights the presence of a complex scenario involving a transiently populated folding intermediate that may be accumulated from the concurrent denaturation of both PDZ5 and PDZ6 domains. Importantly, double jump kinetic experiments allowed us to pinpoint the ability of this transient intermediate to bind the physiological ligand of sPDZD2 with increased affinity compared to the native state. In summary, our results provide an interesting example of a functionally competent misfolded intermediate, which may exert a cryptic function that is not captured from the analysis of the native state only. [ABSTRACT FROM AUTHOR]

Protein function prediction is gradually emerging as an essential field in biological and computational studies. Though the latter has clinched a significant footprint, it has been observed that the application of computational information gathered from multiple sources has more significant influence than the one derived from a single source. Considering this fact, a methodology, PFP-GO, is proposed where heterogeneous sources like Protein Sequence, Protein Domain, and Protein-Protein Interaction Network have been processed separately for ranking each individual functional GO term. Based on this ranking, GO terms are propagated to the target proteins. While Protein sequence enriches the sequence-based information, Protein Domain and Protein-Protein Interaction Networks embed structural/functional and topological based information, respectively, during the phase of GO ranking. Performance analysis of PFP-GO is also based on Precision, Recall, and F-Score. The same was found to perform reasonably better when compared to the other existing state-of-art. PFP-GO has achieved an overall Precision, Recall, and F-Score of 0.67, 0.58, and 0.62, respectively. Furthermore, we check some of the top-ranked GO terms predicted by PFP-GO through multilayer network propagation that affect the 3D structure of the genome. The complete source code of PFP-GO is freely available at https://sites.google.com/view/pfp-go/.

Methionine-rich prion-like proteins can regulate liquid–liquid phase separation processes in response to stresses. To date, however, very few proteins have been identified as methionine-rich prion-like. Herein, we have performed a computational survey of the human proteome to search for methionine-rich prion-like domains. We present a census of 51 manually curated methionine-rich prion-like proteins. Our results show that these proteins tend to be modular in nature, with molecular sizes significantly greater than those we would expect due to random sampling effects. These proteins also exhibit a remarkably high degree of spatial compaction when compared to average human proteins, even when protein size is accounted for. Computational evidence suggests that such a high degree of compactness might be due to the aggregation of methionine residues, pointing to a potential redox regulation of compactness. Gene ontology and network analyses, performed to shed light on the biological processes in which these proteins might participate, indicate that methionine-rich and non-methionine-rich prion-like proteins share gene ontology terms related to the regulation of transcription and translation but, more interestingly, these analyses also reveal that proteins from the methionine-rich group tend to share more gene ontology terms among them than they do with their non-methionine-rich prion-like counterparts. [ABSTRACT FROM AUTHOR]

Background: Both the protein domains and transcript structures influence protein functional variation. The genomic location of both protein domains and transcript structural features can be described using the genomic coordinates of their encoded sequences. However, the coordinates of protein domains and transcriptional features often differ greatly, and it is difficult to view them in combination at the genome-wide level. In this paper, we describe the development of a new tool that allows users to visualize domains and transcript features together, using either built-in or uploaded genome datasets, and export publication-ready figures. Results: We developed a user-friendly, independent R package and Shiny web application named "VisProDom". VisProDom consists of a genome-wide database containing entire annotated transcripts merged with annotated protein domains from the Pfam database. The built-in dataset includes 82 files, which merge genome general feature format (GFF) annotations with rpsblast tabular outputs from protein sequence searches in the Pfam database. Multiple genomes can be simultaneously screened for protein domains or transcript names. VisProDom includes step-by-step introductions and clickable elements for ease of use. Conclusion: VisProDom can display hundreds of transcripts alongside protein domains and export figures in a publication-ready format. This makes it a valuable tool for molecular evolution and comparative genomics. [ABSTRACT FROM AUTHOR]

Background: Alternative splicing can increase the diversity of gene functions by generating multiple isoforms with different sequences and functions. However, the extent to which splicing events have functional consequences remains unclear and predicting the impact of splicing events on protein activity is limited to gene-specific analysis. Results: To accelerate the identification of functionally relevant alternative splicing events we created SAPFIR, a predictor of protein features associated with alternative splicing events. This webserver tool uses InterProScan to predict protein features such as functional domains, motifs and sites in the human and mouse genomes and link them to alternative splicing events. Alternative protein features are displayed as functions of the transcripts and splice sites. SAPFIR could be used to analyze proteins generated from a single gene or a group of genes and can directly identify alternative protein features in large sequence data sets. The accuracy and utility of SAPFIR was validated by its ability to rediscover previously validated alternative protein domains. In addition, our de novo analysis of public datasets using SAPFIR indicated that only a small portion of alternative protein domains was conserved between human and mouse, and that in human, genes involved in nervous system process, regulation of DNA-templated transcription and aging are more likely to produce isoforms missing functional domains due to alternative splicing. Conclusion: Overall SAPFIR represents a new tool for the rapid identification of functional alternative splicing events and enables the identification of cellular functions affected by a defined splicing program. SAPFIR is freely available at https://bioinfo-scottgroup.med.usherbrooke.ca/sapfir/, a website implemented in Python, with all major browsers supported. The source code is available at https://github.com/DelongZHOU/SAPFIR. [ABSTRACT FROM AUTHOR]

Objectives: Pearl millet (Pennisetum glaucum) is a cereal crop that is tolerant to a high temperature, a drought and a nutrient-poor condition. Characterizing pearl millet proteins can help to improve productivity of pearl millet and other crops. Transcription factors in general are proteins that regulate transcription of their target genes and thereby regulate diverse processes. Some transcription factor families in pearl millet were characterized in previous studies, but most of them are not. The objective of the data presented was to characterize amino acid sequences for most transcription factors in pearl millet. Data description: Sequences of 2395 pearl millet proteins that have transcription factor-associated domains were extracted. Subcellular and suborganellar localization of these proteins was predicted by MULocDeep. Conserved domains in these sequences were confirmed by CD-Search. These proteins were classified into 85 families on the basis of those conserved domains. A phylogenetic tree including pearl millet proteins and their counterparts in Arabidopsis thaliana and rice was constructed for each of these families. Sequence motifs were identified by MEME for each of these families. [ABSTRACT FROM AUTHOR]

Expansins are a group of proteins from diverse organisms from bacteria to plants. Although expansins show structural conservation, their biological roles seem to differ among kingdoms. In plants, these proteins remodel the cell wall during plant growth and other processes. Contrarily, determination of bacterial expansin activity has proven difficult, although genetic evidence of bacterial mutants indicates that expansins participate in bacteria–plant interactions. Nevertheless, a large proportion of expansin genes are found in the genomes of free‐living bacteria, suggesting roles that are independent of the interaction with living plants. Here, we analyzed all available sequences of prokaryotic expansins for correlations between surface electric charge, extra protein modules, and sequence motifs for association with the bacteria exterior after export. Additionally, information on the fate of protein after translocation across the membrane also points to bacterial cell association of expansins through six different mechanisms, such as attachment of a lipid molecule for membrane anchoring in diderm species or covalent linking to the peptidoglycan layer in monoderms such as the Bacilliales. Our results have implications for expansin function in the context of bacteria–plant interactions and also for free‐living species in which expansins might affect cell–cell or cell–substrate interaction properties and indicate the need to re‐examine the roles currently considered for these proteins. [ABSTRACT FROM AUTHOR]

Many pigments, such as melanins, are widely distributed throughout the animal kingdom. Others have arisen as novelties in particular lineages, for example, the Green Fluorescent Protein (GFP) found in cnidarians. While GFPs, widely used as fluorescent tags in biomedical research, are the most famous cnidarian example, other novel proteins have also been identified within this phylum. A blue protein that contains a Kringle (KR) domain inserted within a Frizzled cysteine-rich domain (Fz-CRD) was previously described from the jellyfish Rhizostoma pulmo (named rpulFKz1), however little is known about this pigment’s evolution or distribution among cnidarians. We performed a systematic search for homologs of this protein in published genomes and transcriptomes of 93 cnidarians. Phylogenetic analyses revealed eight predicted proteins that possess both domains in the same arrangement and that fall within the same clade as rpulFKz1. The sequence of one of these proteins contains motifs that match sequenced peptides of Cassio Blue, the blue pigment from Cassiopea xamachana. Another one of these proteins belongs to Stomolophus meleagris, and chemical studies on blue pigments that may occur in this genus have shown similarities to rpulFKz1 and Cassio Blue. Therefore, we hypothesize that the eight rpulFKz1 homologs identified are also pigment precursors. All precursors identified were exclusive to jellyfish in the order Rhizostomeae, so we herein name this new pigment family “rhizostomins.” Not all rhizostomes analyzed are blue, however, so these rhizostomin proteins may also be responsible for other colors, or perform other biochemical and biophysical roles. Previous studies have hypothesized that cnidarian pigments are photoprotective, and this study serves as basis for future investigations not only on the function of rhizostomins, but also on potential biotechnological applications for these proteins.

Abstract Background Modularity is important for evolutionary innovation. The recombination of existing units to form larger complexes with new functionalities spares the need to create novel elements from scratch. In proteins, this principle can be observed at the level of protein domains, functional subunits which are regularly rearranged to acquire new functions. Results In this study we analyse the mechanisms leading to new domain arrangements in five major eukaryotic clades (vertebrates, insects, fungi, monocots and eudicots) at unprecedented depth and breadth. This allows, for the first time, to directly compare rates of rearrangements between different clades and identify both lineage specific and general patterns of evolution in the context of domain rearrangements. We analyse arrangement changes along phylogenetic trees by reconstructing ancestral domain content in combination with feasible single step events, such as fusion or fission. Using this approach we explain up to 70% of all rearrangements by tracing them back to their precursors. We find that rates in general and the ratio between these rates for a given clade in particular, are highly consistent across all clades. In agreement with previous studies, fusions are the most frequent event leading to new domain arrangements. A lineage specific pattern in fungi reveals exceptionally high loss rates compared to other clades, supporting recent studies highlighting the importance of loss for evolutionary innovation. Furthermore, our methodology allows us to link domain emergences at specific nodes in the phylogenetic tree to important functional developments, such as the origin of hair in mammals. Conclusions Our results demonstrate that domain rearrangements are based on a canonical set of mutational events with rates which lie within a relatively narrow and consistent range. In addition, gained knowledge about these rates provides a basis for advanced domain-based methodologies for phylogenetics and homology analysis which complement current sequence-based methods.

Secreted Wnt lipoproteins are cysteine-rich and lipid-modified morphogens that bind to the Frizzled (FZD) receptor and LDL receptor-related protein 6 (LRP6). Wnt engages FZD through protruding thumb and index finger domains, which are each assembled from paired β strands secured by disulfide bonds and grasp two sides of the FZD ectodomain. The importance of Wnt disulfide bonds has been assumed but uncharacterized. We systematically analyzed cysteines and associated disulfide bonds in the prototypic Wnt3a. Our data show that mutation of any individual cysteine of Wnt3a results in covalent Wnt oligomers through ectopic intermolecular disulfide bond formation and diminishes/abolishes Wnt signaling. Although individual cysteine mutations in the amino part of the saposin-like domain and in the base of the index finger are better tolerated and permit residual Wnt3a secretion/activity, those in the amino terminus, the thumb, and at the tip of the index finger are incompatible with secretion and/or activity. A few select double cysteine mutants based on the disulfide bond pattern restore Wnt secretion/activity. Further, a double cysteine mutation at the index finger tip results in a Wnt3a with normal secretion but minimal FZD binding and dominant negative properties. Our results experimentally validate predictions from the Wnt crystal structure and highlight critical but different roles of the saposin-like and cytokine-like domains, including the thumb and the index finger in Wnt folding/secretion and FZD binding. Finally, we modified existing expression vectors for 19 epitope-tagged human WNT proteins by removal of a tag-supplied ectopic cysteine, thereby generating tagged WNT ligands active in canonical and non-canonical signaling.

Abstract Background Orthology inference is normally based on full-length protein sequences. However, most proteins contain independently folding and recurring regions, domains. The domain architecture of a protein is vital for its function, and recombination events mean individual domains can have different evolutionary histories. It has previously been shown that orthologous proteins may differ in domain architecture, creating challenges for orthology inference methods operating on full-length sequences. We have developed Domainoid, a new tool aiming to overcome these challenges faced by full-length orthology methods by inferring orthology on the domain level. It employs the InParanoid algorithm on single domains separately, to infer groups of orthologous domains. Results This domain-oriented approach allows detection of discordant domain orthologs, cases where different domains on the same protein have different evolutionary histories. In addition to domain level analysis, protein level orthology based on the fraction of domains that are orthologous can be inferred. Domainoid orthology assignments were compared to those yielded by the conventional full-length approach InParanoid, and were validated in a standard benchmark. Conclusions Our results show that domain-based orthology inference can reveal many orthologous relationships that are not found by full-length sequence approaches. Availability https://bitbucket.org/sonnhammergroup/domainoid/

Human genome resequencing projects provide an unprecedented amount of data about single-nucleotide variations occurring in protein-coding regions and often leading to observable changes in the covalent structure of gene products. For many of these variations, links to Online Mendelian Inheritance in Man (OMIM) genetic diseases are available and are reported in many databases that are collecting human variation data such as Humsavar. However, the current knowledge on the molecular mechanisms that are leading to diseases is, in many cases, still limited. For understanding the complex mechanisms behind disease insurgence, the identification of putative models, when considering the protein structure and chemico-physical features of the variations, can be useful in many contexts, including early diagnosis and prognosis. In this study, we investigate the occurrence and distribution of human disease–related variations in the context of Pfam domains. The aim of this study is the identification and characterization of Pfam domains that are statistically more likely to be associated with disease-related variations. The study takes into consideration 2,513 human protein sequences with 22,763 disease-related variations. We describe patterns of disease-related variation types in biunivocal relation with Pfam domains, which are likely to be possible markers for linking Pfam domains to OMIM diseases. Furthermore, we take advantage of the specific association between disease-related variation types and Pfam domains for clustering diseases according to the Human Disease Ontology, and we establish a relation among variation types, Pfam domains, and disease classes. We find that Pfam models are specific markers of patterns of variation types and that they can serve to bridge genes, diseases, and disease classes. Data are available as Supplementary Material for 1,670 Pfam models, including 22,763 disease-related variations associated to 3,257 OMIM diseases.

Methionine-rich prion-like proteins can regulate liquid–liquid phase separation processes in response to stresses. To date, however, very few proteins have been identified as methionine-rich prion-like. Herein, we have performed a computational survey of the human proteome to search for methionine-rich prion-like domains. We present a census of 51 manually curated methionine-rich prion-like proteins. Our results show that these proteins tend to be modular in nature, with molecular sizes significantly greater than those we would expect due to random sampling effects. These proteins also exhibit a remarkably high degree of spatial compaction when compared to average human proteins, even when protein size is accounted for. Computational evidence suggests that such a high degree of compactness might be due to the aggregation of methionine residues, pointing to a potential redox regulation of compactness. Gene ontology and network analyses, performed to shed light on the biological processes in which these proteins might participate, indicate that methionine-rich and non-methionine-rich prion-like proteins share gene ontology terms related to the regulation of transcription and translation but, more interestingly, these analyses also reveal that proteins from the methionine-rich group tend to share more gene ontology terms among them than they do with their non-methionine-rich prion-like counterparts.

The DEK oncoprotein regulates cellular chromatin function via a number of protein–protein interactions. However, the biological relevance of its unique pseudo‐SAP/SAP‐box domain, which transmits DNA modulating activities in vitro, remains largely speculative. As hypothesis‐driven mutations failed to yield DNA‐binding null (DBN) mutants, we combined random mutagenesis with the Bacterial Growth Inhibition Screen (BGIS) to overcome this bottleneck. Re‐expression of a DEK‐DBN mutant in newly established human DEK knockout cells failed to reduce the increase in nuclear size as compared to wild type, indicating roles for DEK–DNA interactions in cellular chromatin organization. Our results extend the functional roles of DEK in metazoan chromatin and highlight the predictive ability of recombinant protein toxicity in E. coli for unbiased studies of eukaryotic DNA modulating protein domains. [ABSTRACT FROM AUTHOR]

In two proof‐of‐concept studies, we established and validated the Bacterial Growth Inhibition Screen (BGIS), which explores recombinant protein toxicity in Escherichia coli as a largely overlooked and alternative means for basic characterization of functional eukaryotic protein domains. By applying BGIS, we identified an unrecognized RNA‐interacting domain in the DEK oncoprotein (this study) and successfully combined BGIS with random mutagenesis as a screening tool for loss‐of‐function mutants of the DNA modulating domain of DEK [1]. Collectively, our findings shed new light on the phenomenon of recombinant protein toxicity in E. coli. Given the easy and rapid implementation and wide applicability, BGIS will extend the repertoire of basic methods for the identification, analysis and unbiased manipulation of proteins. [ABSTRACT FROM AUTHOR]

Quantitation of individual monoclonal antibodies (mAbs) within a combined antibody drug product is required for preclinical and clinical drug development. We have developed two antitoxins, XOMA 3B and XOMA 3E, each consisting of three mAbs that neutralize type B and type E botulinum neurotoxin (BoNT/B and BoNT/E) to treat serotype B and E botulism. To develop mAb-specific binding assays for each antitoxin, we mapped the epitopes of the six mAbs. Each mAb bound an epitope on either the BoNT light chain (LC) or translocation domain (H(N)). Epitope mapping data were used to design LC-H(N) domains with orthogonal mutations to make them specific for only one mAb in either XOMA 3B or XOMA 3E. Mutant LC-H(N) domains were cloned, expressed, and purified from Escherichia coli. Each mAb bound only to its specific domain with affinity comparable to the binding to holotoxin. Further engineering of domains allowed construction of enzyme-linked immunosorbent assays (ELISAs) that could characterize the integrity, binding affinity, and identity of each of the six mAbs in XOMA 3B and 3E without interference from the three BoNT/A mAbs in XOMA 3AB. Such antigen engineering is a general method allowing quantitation and characterization of individual mAbs in a mAb cocktail that bind the same protein.

The Chlamydomonas reinhardtii DNA-insertional transformant truncated light-harvesting antenna 1 (tla1) mutant, helped identify the novel TLA1 gene (GenBank Accession # AF534570-71) as an important genetic determinant in the chlorophyll antenna size of photosynthesis. Down-regulation in the amount of the TLA1 23 kDa protein in the cell resulted in smaller chlorophyll antenna size for both photosystems (in Tetali et al. Planta 225:813-829, 2007). Specific polyclonal antibodies, raised against the recombinant TLA1 protein, showed a cross-reaction with the predicted 23 kDa TLA1 protein in C. reinhardtii protein extracts, but also showed a strong cross-reaction with a protein band migrating to 28.5 kDa. Questions of polymorphism, or posttranslational modification of the TLA1 protein were raised as a result of the unexpected 28.5 kDa cross-reaction. Work in this paper aimed to elucidate the nature of the unexpected 28.5 kDa cross-reaction, as this was deemed to be important in terms of the functional role of the TLA1 protein in the regulation of the chlorophyll antenna size of photosynthesis. Immuno-precipitation of the 28.5 kDa protein, followed by LC-mass spectrometry, showed amino acid sequences ascribed to the psbD/D2 reaction center protein of PSII. The common antigenic determinant between TLA1 and D2 was shown to be a stretch of nine conserved amino acids V-F-L(V)LP-GNAL in the C-terminus of the two proteins, constituting a high antigenicity "GNAL" domain. Antibodies raised against the TLA1 protein containing this domain recognized both the TLA1 and the D2 protein. Conversely, antibodies raised against the TLA1 protein minus the GNAL domain specifically recognized the 23 kDa TLA1 protein and failed to recognize the 28.5 kDa D2 protein. D2 antibodies raised against an oligopeptide containing this domain also cross-reacted with the TLA1 protein. It is concluded that the 28.5 kDa cross-reaction of C. reinhardtii protein extracts with antiTLA1 antibodies is due to antibody affinity for the GNAL domain of the D2 protein and has no bearing on the identity or function of the TLA1 protein.

Abstract Background Families of related proteins and their different functions may be described systematically using common classifications and ontologies such as Pfam and GO (Gene Ontology), for example. However, many proteins consist of multiple domains, and each domain, or some combination of domains, can be responsible for a particular molecular function. Therefore, identifying which domains should be associated with a specific function is a non-trivial task. Results We describe a general approach for the computational discovery of associations between different sets of annotations by formalising the problem as a bipartite graph enrichment problem in the setting of a tripartite graph. We call this approach “CODAC” (for COmputational Discovery of Direct Associations using Common Neighbours). As one application of this approach, we describe “GODomainMiner” for associating GO terms with protein domains. We used GODomainMiner to predict GO-domain associations between each of the 3 GO ontology namespaces (MF, BP, and CC) and the Pfam, CATH, and SCOP domain classifications. Overall, GODomainMiner yields average enrichments of 15-, 41- and 25-fold GO-domain associations compared to the existing GO annotations in these 3 domain classifications, respectively. Conclusions These associations could potentially be used to annotate many of the protein chains in the Protein Databank and protein sequences in UniProt whose domain composition is known but which currently lack GO annotation.

Abstract Background Identification of genetic mechanisms and idiosyncrasies at the breed-level can provide valuable information for potential use in evolutionary studies, medical applications, and breeding of selective traits. Here, we analyzed genomic data collected from 136 Korean Native cattle, known as Hanwoo, using advanced statistical methods. Results Results revealed Hanwoo-specific protein domains which were largely characterized by immunoglobulin function. Furthermore, domain interactions of novel Hanwoo-specific genes reveal additional links to immunity. Novel Hanwoo-specific genes linked to muscle and other functions were identified, including protein domains with functions related to energy, fat storage, and muscle function that may provide insight into the mechanisms behind Hanwoo cattle’s uniquely high percentage of intramuscular fat and fat marbling. Conclusion The identification of Hanwoo-specific genes linked to immunity are potentially useful for future medical research and selective breeding. The significant genomic variations identified here can crucially identify genetic novelties that are arising from useful adaptations. These results will allow future researchers to compare and classify breeds, identify important genetic markers, and develop breeding strategies to further improve significant traits.

La shuttles between the nucleus and cytoplasm where it binds nascent RNA polymerase III (pol III) transcripts and mRNAs, respectively. La protects the 3ʹ end of pol III transcribed RNA precursors, such as pre-tRNAs, through the use of a well-characterized UUU-3ʹOH binding mode. La proteins are also RNA chaperones, and La-dependent RNA chaperone activity is hypothesized to promote pre-tRNA maturation and translation at cellular and viral internal ribosome entry sites via binding sites distinct from those used for UUU-3ʹOH recognition. Since the publication of La-UUU-3ʹOH co-crystal structures, biochemical and genetic experiments have expanded our understanding of how La proteins use UUU-3ʹOH-independent binding modes to make sequence-independent contacts that can increase affinity for ligands and promote RNA remodeling. Other recent work has also expanded our understanding of how La binds mRNAs through contacts to the poly(A) tail. In this review, we focus on advances in the study of La protein-RNA complex surfaces beyond the description of the La-UUU-3ʹOH binding mode. We highlight recent advances in the functions of expected canonical nucleic acid interaction surfaces, a heightened appreciation of disordered C-terminal regions, and the nature of sequence-independent RNA determinants in La-RNA target binding. We further discuss how these RNA binding modes may have relevance to the function of the La-related proteins. [ABSTRACT FROM AUTHOR]

RNA- and DNA-binding domains are essential building blocks for specific regulation of gene expression. While a number of canonical nucleic acid binding domains share sequence and structural conservation, others are less obviously linked by evolutionary traits. In this review, we describe a protein fold of about 150 aa in length, bearing a conserved β-β-β-β-α-linker-β-β-β-β-α topology and similar nucleic acid binding properties but no apparent sequence conservation. The same overall fold can also be achieved by dimerization of two proteins, each bearing a β-β-β-β-α topology. These proteins include but are not limited to the transcription factors PC4 and P24 from humans and plants, respectively, the human RNA-transport factor Pur-α (also termed PURA), as well as the ssDNA-binding SP_0782 protein from Streptococcus pneumonia and the bacteriophage coat proteins PP7 and MS2. Besides their common overall topology, these proteins share common nucleic acids binding surfaces and thus functional similarity. We conclude that these PC4-like domains include proteins from all kingdoms of life and are much more abundant than previously known. [ABSTRACT FROM AUTHOR]

In many application domains, neural networks are highly accurate and have been deployed at large scale. However, users often do not have good tools for understanding how these models arrive at their predictions. This has hindered adoption in fields such as the life and medical sciences, where researchers require that models base their decisions on underlying biological phenomena rather than peculiarities of the dataset. We propose a set of methods for critiquing deep learning models and demonstrate their application for protein family classification, a task for which high-accuracy models have considerable potential impact. Our methods extend the Sufficient Input Subsets (SIS) technique, which we use to identify subsets of features in each protein sequence that are alone sufficient for classification. Our suite of tools analyzes these subsets to shed light on the decision-making criteria employed by models trained on this task. These tools show that while deep models may perform classification for biologically relevant reasons, their behavior varies considerably across the choice of network architecture and parameter initialization. While the techniques that we develop are specific to the protein sequence classification task, the approach taken generalizes to a broad set of scientific contexts in which model interpretability is essential. [ABSTRACT FROM AUTHOR]

Alternative splicing (AS) is a mechanism of regulation of the proteome via enabling the production of multiple mRNAs from a single gene. To date, the dynamics of AS and its effects on the protein sequences of individuals in a large and genetically unrelated population of trees have not been investigated. Here we describe the diversity of AS events within a previously genotyped population of 268 individuals of Populus deltoides and their putative downstream functional effects. Using a robust bioinformatics pipeline, the AS events and resulting transcript isoforms were discovered and quantified for each individual in the population. Analysis of the AS revealed that, as expected, most AS isoforms are conserved. However, we also identified a substantial collection of new, unannotated splice junctions and transcript isoforms. Heritability estimates for the expression of transcript isoforms showed that approximately half of the isoforms are heritable. The genetic regulators of these AS isoforms and splice junction usage were then identified using a genome-wide association analysis. The expression of AS isoforms was predominately cis regulated while splice junction usage was generally regulated in trans. Additionally, we identified 696 genes encoding alternatively spliced isoforms that changed putative protein domains relative to the longest protein coding isoform of the gene, and 859 genes exhibiting this same phenomenon relative to the most highly expressed isoform. Finally, we found that 748 genes gained or lost micro-RNA binding sites relative to the longest protein coding isoform of a given gene, while 940 gained or lost micro-RNA binding sites relative to the most highly expressed isoform. These results indicate that a significant fraction of AS events are genetically regulated and that this isoform usage can result in protein domain architecture changes. [ABSTRACT FROM AUTHOR]

Abstract Background Discriminating driver mutations from the ones that play no role in cancer is a severe bottleneck in elucidating molecular mechanisms underlying cancer development. Since protein domains are representatives of functional regions within proteins, mutations on them may disturb the protein functionality. Therefore, studying mutations at domain level may point researchers to more accurate assessment of the functional impact of the mutations. Results This article presents a comprehensive study to map mutations from 29 cancer types to both sequence- and structure-based domains. Statistical analysis was performed to identify candidate domains in which mutations occur with high statistical significance. For each cancer type, the corresponding type-specific domains were distinguished among all candidate domains. Subsequently, cancer type-specific domains facilitated the identification of specific proteins for each cancer type. Besides, performing interactome analysis on specific proteins of each cancer type showed high levels of interconnectivity among them, which implies their functional relationship. To evaluate the role of mitochondrial genes, stem cell-specific genes and DNA repair genes in cancer development, their mutation frequency was determined via further analysis. Conclusions This study has provided researchers with a publicly available data repository for studying both CATH and Pfam domain regions on protein-coding genes. Moreover, the associations between different groups of genes/domains and various cancer types have been clarified. The work is available at http://www.cancerouspdomains.ir .