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In human, mutations in the gene encoding the enamel matrix protein ameloblastin (Ambn) have been identified in cases of amelogenesis imperfecta. In mouse models, perturbations in the Ambn gene have caused loss of enamel and dramatic disruptions in enamel-making ameloblast cell function. Critical roles for Ambn in ameloblast cell signaling and polarization as well as adhesion to the nascent enamel matrix have been supported. Recently, we have identified a multitargeting domain (MTD) in Ambn that interacts with cell membrane, with the majority enamel matrix protein amelogenin, and with itself. This domain includes an amphipathic helix (AH) motif that directly interacts with cell membrane. In this study, we analyzed the sequence of the MTD for evolutionary conservation and found high conservation among mammals within the MTD and particularly within the AH motif. We computationally predicted that the AH motif lost its hydrophobic moment upon deleting hydrophobic but not hydrophilic residues from the motif. Furthermore, we rationally designed peptides that encompassed the Ambn MTD and contained deletions of largely hydrophobic or hydrophilic stretches of residues. To assess their AH-forming and membrane-binding abilities, we combined those peptides with synthetic phospholipid membrane vesicles and performed circular dichroism, membrane leakage, and vesicle clearance measurements. Circular dichroism showed retention of α-helix formation in all peptides except the one with the largest deletion of eleven amino acids including seven that were hydrophobic. This same peptide variant failed to cause leakage or clearance of synthetic membranes, while smaller deletions yielded intermediate membrane interaction as measured by leakage and clearance assays. Our data revealed that deletion of key hydrophobic residues from the AH leads to the most dramatic loss of Ambn-membrane interaction. Pinpointing roles of residues within the MTD has important implications for the multifunctionality of Ambn., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The AXXXA and GXXXG motifs are frequently observed in helices, especially in membrane proteins. The motif GXXXG is known to stabilize helix-helix association in membrane proteins via C α HO bonding. AXXXA sequence motif additionally stabilizes the folded state of proteins. We found 27,000 and 18,000 occurrences of AXXXA and GXXXG motifs in a non-redundant set of 6000 obligate homodimeric (OD) complexes. Interestingly, this is less pronounced in transient homodimers (TD) and heterodimers (HetD). On average each obligate homodimer contains four AXXXA motifs, it is 2 and 3.5 for HetD and TD, respectively. Focusing on the binding surface it is seen that 27 % of the ODs contain at least one AXXXA motif at the interface, whereas it is 17 % and 15 % for HetD and TD respectively. AXXXA predominantly stabilizes the OD quaternary structure via the side chain C β C β interactions. This interaction is energetically favorable and is found to be a major driving force for OD quaternary structure stability. C β- C β interactions are observed ∼6 times higher than the known C α HO interaction for helix-helix stabilization. Two additional new interactions of C β O and OO are observed at the AXXXA containing interface regions. The occurrence of the motif gets drastically reduced if any of the terminal Ala residues are replaced by Gly. Our findings show the importance of AXXXA in providing stability to the quaternary structure through specific hydrophobic interactions and the specificity of the Ala residue at motif termini. The knowledge gained can be used for designing synthetic proteins of improved stability and for designing peptide-based therapeutics., Competing Interests: Declaration of competing interest The authors declare that they have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Many polymerases and other proteins are endowed with a catalytic domain belonging to the nucleotidyltransferase fold, which has also been deemed the non-canonical palm domain, in which three conserved acidic residues coordinate two divalent metal ions. Tertiary structure-based evolutionary analyses provide valuable information when the phylogenetic signal contained in the primary structure is blurry or has been lost, as is the case with these proteins. Pairwise structural comparisons of proteins with a nucleotidyltransferase fold were performed in the PDBefold web server: the RMSD, the number of superimposed residues, and the Qscore were obtained. The structural alignment score (RMSD × 100/number of superimposed residues) and the 1-Qscore were calculated, and distance matrices were constructed, from which a dendogram and a phylogenetic network were drawn for each score. The dendograms and the phylogenetic networks display well-defined clades, reflecting high levels of structural conservation within each clade, not mirrored by primary sequence. The conserved structural core between all these proteins consists of the catalytic nucleotidyltransferase fold, which is surrounded by different functional domains. Hence, many of the clades include proteins that bind different substrates or partake in non-related functions. Enzymes endowed with a nucleotidyltransferase fold are present in all domains of life, and participate in essential cellular and viral functions, which suggests that this domain is very ancient. Despite the loss of evolutionary traces in their primary structure, tertiary structure-based analyses allow us to delve into the evolution and functional diversification of the NT fold., Competing Interests: Declarations. Conflict of interest: The author has no relevant financial or non-financial interests to disclose., (© 2024. The Author(s).)

Interactions of biological molecules in organisms are considered to be primary factors for the lifecycle of that organism. Various important biological functions are dependent on such interactions and among different kinds of interactions, the protein DNA interactions are very important for the processes of transcription, regulation of gene expression, DNA repairing and packaging. Thus, keeping the knowledge of such interactions and the sites of those interactions is necessary to study the mechanism of various biological processes. As experimental identification through biological assays is quite resource-demanding, costly and error-prone, scientists opt for the computational methods for efficient and accurate identification of such DNA-protein interaction sites. Thus, herein, we propose a novel and accurate method namely DeepDBS for the identification of DNA-binding sites in proteins, using primary amino acid sequences of proteins under study. From protein sequences, deep representations were computed through a one-dimensional convolution neural network (1D-CNN), recurrent neural network (RNN) and long short-term memory (LSTM) network and were further used to train a Random Forest classifier. Random Forest with LSTM-based features outperformed the other models, as well as the existing state-of-the-art methods with an accuracy score of 0.99 for self-consistency test, 10-fold cross-validation, 5-fold cross-validation, and jackknife validation while 0.92 for independent dataset testing. It is concluded based on results that the DeepDBS can help accurate and efficient identification of DNA binding sites (DBS) in proteins., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Protein secondary structure prediction (PSSP) is a critical task in computational biology, pivotal for understanding protein function and advancing medical diagnostics. Recently, approaches that integrate multiple amino acid sequence features have gained significant attention in PSSP research., Objectives: We aim to automatically extract additional features represented by evolutionary information from a large number of sequences while simultaneously incorporating positional information for more comprehensive sequence features. Additionally, we consider the interdependence between secondary structures during the prediction stage., Methods: To this end, we propose a deep neural network model, ILMCNet, which utilizes a language model and Conditional Random Field (CRF). Protein language models (PLMs) pre-trained on sequences from multiple large databases can provide sequence features that incorporate evolutionary information. ILMCNet uses positional encoding to ensure that the input features include positional information. To better utilize these features, we propose a hybrid network architecture that employs a Transformer Encoder to enhance features and integrates a feature extraction module combining a Convolutional Neural Network (CNN) with a Bidirectional Long Short-Term Memory Network (BiLSTM). This design enables deep extraction of localized features while capturing global bidirectional information. In the prediction stage, ILMCNet employs CRF to capture the interdependencies between secondary structures., Results: Experimental results on benchmark datasets such as CB513, TS115, NEW364, CASP11, and CASP12 demonstrate that the prediction performance of our method surpasses that of comparable approaches., Conclusions: This study proposes a new approach to PSSP research and is expected to play an important role in other protein-related research fields, such as protein tertiary structure prediction.

Statistical analysis of multiple sequence alignments of homologous proteins has revealed groups of coevolving amino acids called sectors. These groups of amino-acid sites feature collective correlations in their amino-acid usage, and they are associated to functional properties. Modeling showed that nonlinear selection on an additive functional trait of a protein is generically expected to give rise to a functional sector. These modeling results motivated a principled method, called ICOD, which is designed to identify functional sectors, as well as mutational effects, from sequence data. However, a challenge for all methods aiming to identify sectors from multiple sequence alignments is that correlations in amino-acid usage can also arise from the mere fact that homologous sequences share common ancestry, i.e. from phylogeny. Here, we generate controlled synthetic data from a minimal model comprising both phylogeny and functional sectors. We use this data to dissect the impact of phylogeny on sector identification and on mutational effect inference by different methods. We find that ICOD is most robust to phylogeny, but that conservation is also quite robust. Next, we consider natural multiple sequence alignments of protein families for which deep mutational scan experimental data is available. We show that in this natural data, conservation and ICOD best identify sites with strong functional roles, in agreement with our results on synthetic data. Importantly, these two methods have different premises, since they respectively focus on conservation and on correlations. Thus, their joint use can reveal complementary information., Competing Interests: We have no competing interests., (Copyright: © 2024 Dietler et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Asparagine peptide lyase (APL) is among the seven groups of proteases, also known as proteolytic enzymes, which are classified according to their catalytic residue. APLs are synthesized as precursors or propeptides that undergo self-cleavage through autoproteolytic reaction. At present, APLs are grouped into 10 families belonging to six different clans of proteases. Recognizing their critical roles in many biological processes including virus maturation, and virulence, accurate identification and characterization of APLs is indispensable. Experimental identification and characterization of APLs is laborious and time-consuming. Here, we developed APLpred, a novel support vector machine (SVM) based predictor that can predict APLs from the primary sequences. APLpred was developed using Boruta-based optimal features derived from seven encodings and subsequently trained using five machine learning algorithms. After evaluating each model on an independent dataset, we selected APLpred (an SVM-based model) due to its consistent performance during cross-validation and independent evaluation. We anticipate APLpred will be an effective tool for identifying APLs. This could aid in designing inhibitors against these enzymes and exploring their functions. The APLpred web server is freely available at https://procarb.org/APLpred/., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The monkeypox virus (mpox virus, MPXV) epidemic in 2022 has posed a significant public health risk. Yet, the evolutionary principles of MPXV remain largely unknown. Here, we examined the evolutionary patterns of protein sequences and codon usage in MPXV. We first demonstrated the signal of positive selection in OPG027, specifically in the Clade I lineage of MPXV. Subsequently, we discovered accelerated protein sequence evolution over time in the variants responsible for the 2022 outbreak. Furthermore, we showed strong epistasis between amino acid substitutions located in different genes. The codon adaptation index (CAI) analysis revealed that MPXV genes tended to use more non-preferred codons compared to human genes, and the CAI decreased over time and diverged between clades, with Clade I > IIa and IIb-A > IIb-B. While the decrease in fatality rate among the three groups aligned with the CAI pattern, it remains unclear whether this correlation was coincidental or if the deoptimization of codon usage in MPXV led to a reduction in fatality rates. This study sheds new light on the mechanisms that govern the evolution of MPXV in human populations., (© The Author(s) 2024. Published by Oxford University Press and Science Press on behalf of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China.)

Many clinically used drugs are derived from or inspired by bacterial natural products that often are produced through nonribosomal peptide synthetases (NRPSs), megasynthetases that activate and join individual amino acids in an assembly line fashion. In this work, we describe a detailed phylogenetic analysis of several bacterial NRPSs that led to the identification of yet undescribed recombination sites within the thiolation (T) domain that can be used for NRPS engineering. We then developed an evolution-inspired "eXchange Unit between T domains" (XUT) approach, which allows the assembly of NRPS fragments over a broad range of GC contents, protein similarities, and extender unit specificities, as demonstrated for the specific production of a proteasome inhibitor designed and assembled from five different NRPS fragments.

Characterizing the effects of mutations on stability is critical for understanding the function and evolution of proteins and improving their biophysical properties. High throughput folding and abundance assays have been successfully used to characterize missense mutations associated with reduced stability. However, screening for increased thermodynamic stability is more challenging since such mutations are rarer and their impact on assay readout is more subtle. Here, a multiplex assay for high throughput screening of protein folding was developed by combining deep mutational scanning, fluorescence-activated cell sorting, and deep sequencing. By analyzing a library of 2000 variants of Adenylate kinase we demonstrate that the readout of the method correlates with stability and that mutants with up to 13 °C increase in thermal melting temperature could be identified with low false positive rate. The discovery of many stabilizing mutations also enabled the analysis of general substitution patterns associated with increased stability in Adenylate kinase. This high throughput method to identify stabilizing mutations can be combined with functional screens to identify mutations that improve both stability and activity., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Human papillomaviruses (HPV) are small DNA viruses associated with cervical cancer, warts, and other epithelial tumors. Structural studies have shown that the HPV capsid consists of 360 copies of the major capsid protein, L1, arranged as 72 pentamers in a T=7 icosahedral lattice, coassembling with substoichiometric amounts of the minor capsid protein, L2. However, the residues involved in the coassembly of L1 and L2 remain undefined due to the lack of structure information. Here, we investigated the solvent accessibility surfaces (SASs) of the central cavity residues of the HPV16 L1 pentamer in the crystal structure because those internal exposed residues might mediate the association with L2. Twenty residues in L1 protein were selected to be analyzed, with four residues in the lumen of the L1 pentamer identified as important: F256, R315, Q317, and T340. Mutations to these four residues reduced the PsV (pseudovirus) infection capacity in 293FT cells, and mutations to R315, Q317, and T340 substantially perturb L2 from coassembling into L1 capsid. Compared with wild-type (WT) PsVs, these mutant PsVs also have a reduced ability to become internalized into host cells. Finally, we identified a stretch of negatively charged residues on L2 (amino acids [aa] 337 to 340 [EEIE]), mutations to which completely abrogate L2 assembly into L1 capsid and subsequently impair the endocytosis and infectivity of HPV16 PsVs. These findings shed light on the elusive coassembly between HPV L1 and L2. IMPORTANCE Over 200 types of HPV have been isolated, with several high-risk types correlated with the occurrence of cervical cancer. The HPV major capsid protein, L1, assembles into a T=7 icosahedral viral shell, and associates with the minor capsid protein, L2, which plays a critical role in the HPV life cycle. Despite the important role of the L2 protein, its structure and coassembly with L1 remain elusive. In this study, we analyzed the amino acid residues at the proposed interface between L1 and L2. Certain mutations at these sites decreased the amount of L2 protein assembled into the capsid, which, in turn, led to a decrease in viral infectivity. Knowledge about these residues and the coassembly of L1 and L2 could help to expand our understanding of HPV biology and aid in the development of countermeasures against a wide range of HPV types by targeting the L2 protein.

Bacillus sp. HR21-6 is capable of the chemo- and regioselective synthesis of lipophilic partially acetylated phenolic compounds derived from olive polyphenols, which are powerful antioxidants important in the formulation of functional foods. In this work, an acetyl esterase was identified in the secretome of this strain by non-targeted proteomics, and classified in the GDSL family (superfamily SGNH). The recombinant protein was expressed and purified from Escherichia coli in the soluble form, and biochemically characterized. Site-directed mutagenesis was performed to understand the role of different amino acids that are conserved among GDSL superfamily of esterases. Mutation of Ser-10, Gly-45 or His-185 abolished the enzyme activity, while mutation of Asn-77 or Thr-184 altered the substrate specificity of the enzyme. This new enzyme is able to perform chemoselective conversions of olive phenolic compounds with great interest in the food industry, such as hydroxytyrosol, 3,4-dihydroxyphenylglycol, and oleuropein., Competing Interests: Declaration of competing interest The authors declare that there are no competing interests associated with the manuscript., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Epistatic interactions can make the outcomes of evolution unpredictable, but no comprehensive data are available on the extent and temporal dynamics of changes in the effects of mutations as protein sequences evolve. Here, we use phylogenetic deep mutational scanning to measure the functional effect of every possible amino acid mutation in a series of ancestral and extant steroid receptor DNA binding domains. Across 700 million years of evolution, epistatic interactions caused the effects of most mutations to become decorrelated from their initial effects and their windows of evolutionary accessibility to open and close transiently. Most effects changed gradually and without bias at rates that were largely constant across time, indicating a neutral process caused by many weak epistatic interactions. Our findings show that protein sequences drift inexorably into contingency and unpredictability, but that the process is statistically predictable, given sufficient phylogenetic and experimental data.

Information about Plasmodium malariae is scanty worldwide due to its "benign" nature and low infection rates. Consequently, studies on the genetic polymorphisms of P. malariae are lacking. Here, we report genetic polymorphisms of 28 P. malariae circumsporozoite protein (Pmcsp) isolates from Malaysia which were compared with those in other regions in Asia as well as those from Africa. Phylogenetic analysis revealed that most Malaysian P. malariae isolates clustered together but independently from other Asian isolates. Low nucleotide diversity was observed in Pmcsp non-repeat regions in contrast to high nucleotide diversity observed in non-repeat regions of Plasmodium knowlesi CSP gene, the current major cause of malaria in Malaysia. This study contributes to the characterisation of naturally occurring polymorphisms in the P. malariae CSP gene., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Since the publication of the first chicken genome sequence, we have encountered genes playing key roles in mammalian immunology, but being seemingly absent in birds. One of those was, until recently, Foxp3, the master transcription factor of regulatory T cells in mammals. Therefore, avian regulatory T cell research is still poorly standardized. In this study we identify a chicken ortholog of Foxp3 We prove sequence homology with known mammalian and sauropsid sequences, but also reveal differences in major domains. Expression profiling shows an association of Foxp3 and CD25 expression levels in CD4 + CD25 + peripheral T cells and identifies a CD4 - CD25 + Foxp3 high subset of thymic lymphocytes that likely represents yet undescribed avian regulatory T precursor cells. We conclude that Foxp3 is existent in chickens and that it shares certain functional characteristics with its mammalian ortholog. Nevertheless, pathways for regulatory T cell development and Foxp3 function are likely to differ between mammals and birds. The identification and characterization of chicken Foxp3 will help to define avian regulatory T cells and to analyze their functional properties and thereby advance the field of avian immunology., (Copyright © 2022 by The American Association of Immunologists, Inc.)

The task of protein sequence design is central to nearly all rational protein engineering problems, and enormous effort has gone into the development of energy functions to guide design. Here, we investigate the capability of a deep neural network model to automate design of sequences onto protein backbones, having learned directly from crystal structure data and without any human-specified priors. The model generalizes to native topologies not seen during training, producing experimentally stable designs. We evaluate the generalizability of our method to a de novo TIM-barrel scaffold. The model produces novel sequences, and high-resolution crystal structures of two designs show excellent agreement with in silico models. Our findings demonstrate the tractability of an entirely learned method for protein sequence design., (© 2022. The Author(s).)

Background: Fatty acid elongases (FAEs), which catalyse elongation reactions of a carbon chain of very-long-chain fatty acids, play an important role in shoot development in rice. The elongation reactions consist of four sequential reactions catalysed by distinct enzymes, which are assumed to form an elongation complex. However, no interacting proteins of ONION1 (ONI1) and ONI2, which are ketoacyl CoA synthase catalyzing the first step and are required for shoot development in rice, are reported., Methods and Results: In this study ketoacyl CoA reductase (KCR) that interacts with ONI1 and ONI2 was searched. A database search identified 10 KCR genes in the rice genome. Among the genes, the expression pattern of KCR1 was similar to that of ONI2. Yeast two-hybrid analysis showed interaction of ONI2 with KCR1, which was confirmed by GST pull-down assay. No interacting partner of ONI1 was identified., Conclusions: Our results suggest that ONI2 and KCR1 form an FAE complex that may play a role in biosynthesizing VLCFAs during shoot development., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

Nucleoli are well defined for their function in ribosome biogenesis, but only a small fraction of the nucleolar proteome has been characterized. Here, we report that the proto-oncogene, c-Jun, is targeted to the nucleolus. Using live cell imaging in myogenic cells, we document that the c-Jun basic domain contains a unique, evolutionarily conserved motif that determines nucleolar targeting. Fos family Jun dimer partners, such as Fra2, while nuclear, do not co-localize with c-Jun in the nucleolus. A point mutation in c-Jun that mimics Fra2 (M260E) in its Nucleolar Localization sequence (NoLS) results in loss of c-Jun nucleolar targeting while still preserving nuclear localization. Fra2 can sequester c-Jun in the nucleoplasm, indicating that the stoichiometric ratio of heterodimeric partners regulates c-Jun nucleolar targeting. Finally, nucleolar localization of c-Jun modulates nucleolar architecture and ribosomal RNA accumulation. These studies highlight a novel role for Jun family proteins in the nucleolus, having potential implications for a diverse array of AP-1-regulated cellular processes., (© 2021 Federation of European Biochemical Societies.)

Background: Using in silico sequence analyses, the present study aims to clone and express the gene-encoding sequence of a GH19 chitinase from Enterobacter sp. in Escherichia coli., Methods and Results: The putative open reading frame of a GH19 chitinase from Enterobacter sp. strain EGY1 was cloned and expressed into pGEM®-T and pET-28a (+) vectors, respectively using a degenerate primer. The isolated nucleotide sequence (1821 bp, GenBank accession no.: MK533791.2) was translated to a chiRAM protein (606 amino acids, UniProt accession no.: A0A4D6J2L9). The in silico protein sequence analysis of chiRAM revealed a class I GH19 chitinase: an N-terminus signal peptide (Met 1 -Ala 23 ), a catalytic domain (Val 83 -Glu 347 and the catalytic triad Glu 149 , Glu 171 , and Ser 218 ), a proline-rich hinge region (Pro 414 -Pro 450 ), a polycystic kidney disease protein motif (Gly 465 -Ser 533 ), a C-terminus chitin-binding domain (Ala 553 - Glu 593 ), and conserved class I motifs (NYNY and AQETGG). A three-dimensional model was constructed by LOMETS MODELLER of PDB template: 2dkvA (class I chitinase of Oryza sativa L. japonica). Recombinant chiRAM was overexpressed as inclusion bodies (IBs) (~ 72 kDa; SDS-PAGE) in 1.0 mM IPTG induced E. coli BL21 (DE3) Rosetta strain at room temperature 18 h after induction. Optimized expression yielded active chiRAM with 1.974 ± 0.0002 U/mL, on shrimp colloidal chitin (SCC), in induced E. coli BL21 (DE3) Rosetta cells growing in SB medium. LC-MS/MS identified a band of 72 kDa in the soluble fraction with a 52.3% coverage sequence exclusive to the GH19 chitinase of Enterobacter cloacae (WP_063869339.1)., Conclusions: Although chiRAM of Enterobacter sp. was successfully cloned and expressed in E. coli with appreciable chitinase activity, future studies should focus on minimizing IBs to facilitate chiRAM purification and characterization., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

We report two structures of the human voltage-gated potassium channel (Kv) Kv1.3 in immune cells alone (apo-Kv1.3) and bound to an immunomodulatory drug called dalazatide (dalazatide-Kv1.3). Both the apo-Kv1.3 and dalazatide-Kv1.3 structures are in an activated state based on their depolarized voltage sensor and open inner gate. In apo-Kv1.3, the aromatic residue in the signature sequence (Y447) adopts a position that diverges 11 Å from other K + channels. The outer pore is significantly rearranged, causing widening of the selectivity filter and perturbation of ion binding within the filter. This conformation is stabilized by a network of intrasubunit hydrogen bonds. In dalazatide-Kv1.3, binding of dalazatide to the channel's outer vestibule narrows the selectivity filter, Y447 occupies a position seen in other K + channels, and this conformation is stabilized by a network of intersubunit hydrogen bonds. These remarkable rearrangements in the selectivity filter underlie Kv1.3's transition into the drug-blocked state., Competing Interests: Competing interest statement: K.G.C. is a co-inventor of a patent on dalazatide, which has been licensed by the University of California, Irvine to TEKv., (Copyright © 2022 the Author(s). Published by PNAS.)

Background: Transcription elongation is a dynamic and tightly regulated step of gene expression in eukaryotic cells. Eleven nineteen Lysine rich Leukemia (ELL) and ELL Associated Factors (EAF) family of conserved proteins are required for efficient RNA polymerase II-mediated transcription elongation. Orthologs of these proteins have been identified in different organisms, including fission yeast and humans., Methods and Results: In the present study, we have examined the sequence, structural and functional conservation between the fission yeast and human ELL and EAF orthologs. Our computational analysis revealed that these proteins share some sequence characteristics, and were predominantly disordered in both organisms. Our functional complementation assays revealed that both human ELL and EAF proteins could complement the lack of ell1 + or eaf1 + in Schizosaccharomyces pombe respectively. Furthermore, our domain mapping experiments demonstrated that both the amino and carboxyl terminal domains of human EAF proteins could functionally complement the S. pombe eaf1 deletion phenotypes. However, only the carboxyl-terminus domain of human ELL was able to partially rescue the phenotypes associated with lack of ell1 + in S. pombe., Conclusions: Collectively, our work adds ELL-EAF to the increasing list of human-yeast complementation gene pairs, wherein the simpler fission yeast can be used to further enhance our understanding of the role of these proteins in transcription elongation and human disease., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

Eukarya pyruvate kinases possess glutamate at position 117 (numbering of rabbit muscle enzyme), whereas bacteria have either glutamate or lysine. Those with E117 are K + -dependent, whereas those with K117 are K + -independent. In a phylogenetic tree, 80% of the sequences with E117 are occupied by T113/K114/T120 and 77% of those with K117 possess L113/Q114/(L,I,V)120. This work aims to understand these residues' contribution to the K + -independent pyruvate kinases using the K + -dependent rabbit muscle enzyme. Residues 117 and 120 are crucial in the differences between the K + -dependent and -independent mutants. K + -independent activity increased with L113 and Q114 to K117, but L120 induced structural differences that inactivated the enzyme. T120 appears to be key in folding the protein and closure of the lid of the active site to acquire its active conformation in the K + -dependent enzymes. E117K mutant was K + -independent and the enzyme acquired the active conformation by a different mechanism. In the K + -independent apoenzyme of Mycobacterium tuberculosis , K72 (K117) flips out of the active site; in the holoenzyme, K72 faces toward the active site bridging the substrates through water molecules. The results provide evidence that two different mechanisms have evolved for the catalysis of this reaction.

A knowledgebase of the systematic functional annotation of fusion genes is critical for understanding genomic breakage context and developing therapeutic strategies. FusionGDB is a unique functional annotation database of human fusion genes and has been widely used for studies with diverse aims. In this study, we report fusion gene annotation updates aided by deep learning (FusionGDB 2.0) available at https://compbio.uth.edu/FusionGDB2/. FusionGDB 2.0 has substantial updates of contents such as up-to-date human fusion genes, fusion gene breakage tendency score with FusionAI deep learning model based on 20 kb DNA sequence around BP, investigation of overlapping between fusion breakpoints with 44 human genomic features across five cellular role's categories, transcribed chimeric sequence and following open reading frame analysis with coding potential based on deep learning approach with Ribo-seq read features, and rigorous investigation of the protein feature retention of individual fusion partner genes in the protein level. Among ∼102k fusion genes, about 15k kept their ORF as In-frames, which is two times compared to the previous version, FusionGDB. FusionGDB 2.0 will be used as the reference knowledgebase of fusion gene annotations. FusionGDB 2.0 provides eight categories of annotations and it will be helpful for diverse human genomic studies., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Nanobodies, a subclass of antibodies found in camelids, are versatile molecular binding scaffolds composed of a single polypeptide chain. The small size of nanobodies bestows multiple therapeutic advantages (stability, tumor penetration) with the first therapeutic approval in 2018 cementing the clinical viability of this format. Structured data and sequence information of nanobodies will enable the accelerated clinical development of nanobody-based therapeutics. Though the nanobody sequence and structure data are deposited in the public domain at an accelerating pace, the heterogeneity of sources and lack of standardization hampers reliable harvesting of nanobody information. We address this issue by creating the Integrated Database of Nanobodies for Immunoinformatics (INDI, http://naturalantibody.com/nanobodies). INDI collates nanobodies from all the major public outlets of biological sequences: patents, GenBank, next-generation sequencing repositories, structures and scientific publications. We equip INDI with powerful nanobody-specific sequence and text search facilitating access to >11 million nanobody sequences. INDI should facilitate development of novel nanobody-specific computational protocols helping to deliver on the therapeutic promise of this drug format., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point-the pH at which a particular molecule carries no net electrical charge-is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides' isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

SARS-CoV-2 is a newly discovered beta coronavirus at the end of 2019, which is highly pathogenic and poses a serious threat to human health. In this paper, 1875 SARS-CoV-2 whole genome sequences and the sequence coding spike protein (S gene) sampled from the United States were used for bioinformatics analysis to study the molecular evolutionary characteristics of its genome and spike protein. The MCMC method was used to calculate the evolution rate of the whole genome sequence and the nucleotide mutation rate of the S gene. The results showed that the nucleotide mutation rate of the whole genome was 6.677 × 10 -4 substitution per site per year, and the nucleotide mutation rate of the S gene was 8.066 × 10 -4 substitution per site per year, which was at a medium level compared with other RNA viruses. Our findings confirmed the scientific hypothesis that the rate of evolution of the virus gradually decreases over time. We also found 13 statistically significant positive selection sites in the SARS-CoV-2 genome. In addition, the results showed that there were 101 nonsynonymous mutation sites in the amino acid sequence of S protein, including seven putative harmful mutation sites. This paper has preliminarily clarified the evolutionary characteristics of SARS-CoV-2 in the United States, providing a scientific basis for future surveillance and prevention of virus variants., (© 2021 Wiley Periodicals LLC.)

Background/aim: Renal cell carcinoma (RCC) is among the most common renal malignancies and requires reliable biomarkers for optimum diagnosis and prognosis. Copines are a family of calcium-dependent phospholipid-binding proteins that were reported to be associated with various cancers. We aimed to investigate the prognostic value of Copines 1 and 3 in RCC patients., Materials and Methods: Copines 1 and 3 bioinformatics analysis and immunohistochemical (IHC) staining were performed on patients with RCC., Results: The findings revealed significant association between Copine 1 expression and the patients' age, nuclear grade, and tumor stage. Bioinformatics analysis showed a similar trend for the mRNA expression of CPNE1, the gene that encodes Copine 1. Interestingly, results revealed a positive association between Copine 1 and both EphA and Ki-67 expression levels. Noteworthy, there was no significant association between Copine 3 expression and any parameters., Conclusion: Copine 1 may be used as an independent biomarker or in combination with both EphA2 and Ki-67 to predict disease outcome., (Copyright © 2022 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

The Gag proteins of retroviruses play an essential role in virus particle assembly by forming a protein shell or capsid and thus generating the virion compartment. A variety of human proteins have now been identified with structural similarity to one or more of the major Gag domains. These human proteins are thought to have been evolved or "domesticated" from ancient integrations due to retroviral infections or retrotransposons. Here, we report that X-ray crystal structures of stably folded domains of MOAP1 (modulator of apoptosis 1) and PEG10 (paternally expressed gene 10) are highly similar to the C-terminal capsid (CA) domains of cognate Gag proteins. The structures confirm classification of MOAP1 and PEG10 as domesticated Gags, and suggest that these proteins may have preserved some of the key interactions that facilitated assembly of their ancestral Gags into capsids., (© 2021 Wiley Periodicals LLC.)

Historically, the genetic analysis of mammalian cells entailed the isolation of randomly arising mutant cell lines with altered properties, followed by laborious genetic mapping experiments to identify the mutant gene responsible for the phenotype. In recent years, somatic cell genetics has been revolutionized by functional genomics screens, in which expression of every protein-coding gene is systematically perturbed, and the phenotype of the perturbed cells is determined. We outline here a novel functional genomics screening strategy that differs fundamentally from commonly used approaches. In this strategy, we express libraries of artificial transmembrane proteins named traptamers and select rare cells with the desired phenotype because, by chance, a traptamer specifically perturbs the expression or activity of a target protein. Active traptamers are then recovered from the selected cells and can be used as tools to dissect the biological process under study. We also briefly describe how we have used this new strategy to provide insights into the complex process by which human papillomaviruses enter cells., (© 2021 Federation of European Biochemical Societies.)

The post-translational acetylation of lysine residues is found in many nonhistone proteins and is involved in a wide range of biological processes. Recently, we showed that the nucleoprotein of the influenza A virus is acetylated by histone acetyltransferases (HATs), a phenomenon that affects viral transcription. Here, we report that the PA subunit of influenza A virus RNA-dependent RNA polymerase is acetylated by the HATs, P300/CREB-binding protein-associated factor (PCAF), and general control nonderepressible 5 (GCN5), resulting in accelerated endonuclease activity. Specifically, the full-length PA subunit expressed in cultured 293T cells was found to be strongly acetylated. Moreover, the partial recombinant protein of the PA N-terminal region containing the endonuclease domain was also acetylated by PCAF and GCN5 in vitro, which facilitated its endonuclease activity. Mass spectrometry analyses identified K19 as a candidate acetylation target in the PA N-terminal region. Notably, the substitution of the lysine residue at position 19 with glutamine, a mimic of the acetyl-lysine residue, enhanced its endonuclease activity in vitro; this point mutation also accelerated influenza A virus RNA-dependent RNA polymerase activity in the cell. Our findings suggest that PA acetylation is important for the regulation of the endonuclease and RNA polymerase activities of the influenza A virus., (© 2021 Federation of European Biochemical Societies.)

By serially exposing an NDM-producing Klebsiella pneumoniae clinical strain to cefiderocol, we obtained a mutant with cefiderocol MIC of >128 μg/ml. The mutant contained an early stop codon in the iron transporter gene cirA , and its complementation fully restored susceptibility. The cirA -deficient mutant was competed out by the parental strain in vitro , suggesting reduced fitness. IMPORTANCE Cefiderocol, a newly approved cephalosporin agent with an extensive spectrum of activity against Gram-negative bacteria, is a siderophore cephalosporin that utilizes iron transporters to access the bacterial periplasm. Loss of functional CirA, an iron transporter, has been associated with cefiderocol resistance. Here, we show that such genetic change can be selected under selective pressure and cause high-level cefiderocol resistance, but with a high fitness cost. Whether these resistant mutants can survive beyond selective pressure will inform stewardship of this agent in the clinic.

Rooting is a key innovation during plant terrestrialization. RGFs/GLVs/CLELs are a family of secreted peptides, playing key roles in root stem cell niche maintenance and pattern formation. The origin of this peptide family is not well characterized. RGFs and their receptor genes, RGIs , were investigated comprehensively using phylogenetic and genetic analyses. We identified 203 RGF genes from 24 plant species, representing a variety of land plant lineages. We found that the RGF genes originate from land plants and expand via multiple duplication events. The lineage-specific RGF duplicates are retained due to their regulatory divergence, while a majority of RGFs experienced strong purifying selection in most land plants. Functional analysis indicated that RGFs and their receptor genes, RGIs , isolated from liverwort, tomato, and maize possess similar biological functions with their counterparts from Arabidopsis in root development. RGFs and RGIs are likely coevolved in land plants. Our studies shed light on the origin and functional conservation of this important peptide family in plant root development.

Endoplasmic reticulum-associated degradation (ERAD) is a protein quality control pathway of fundamental importance to cellular homeostasis. Although multiple ERAD pathways exist for targeting topologically distinct substrates, all pathways require substrate ubiquitination. Here, we characterize a key role for the UBE2G2 Binding Region (G2BR) of the ERAD accessory protein ancient ubiquitous protein 1 (AUP1) in ERAD pathways. This 27-amino acid (aa) region of AUP1 binds with high specificity and low nanomolar affinity to the backside of the ERAD ubiquitin-conjugating enzyme (E2) UBE2G2. The structure of the AUP1 G2BR (G2BRAUP1) in complex with UBE2G2 reveals an interface that includes a network of salt bridges, hydrogen bonds, and hydrophobic interactions essential for AUP1 function in cells. The G2BRAUP1 shares significant structural conservation with the G2BR found in the E3 ubiquitin ligase gp78 and in vitro can similarly allosterically activate ubiquitination in conjunction with ERAD E3s. In cells, AUP1 is uniquely required to maintain normal levels of UBE2G2; this is due to G2BRAUP1 binding to the E2 and preventing its rapid degradation. In addition, the G2BRAUP1 is required for both ER membrane recruitment of UBE2G2 and for its activation at the ER membrane. Thus, by binding to the backside of a critical ERAD E2, G2BRAUP1 plays multiple critical roles in ERAD., Competing Interests: The authors have declared that no competing interests exist.

The UniProt knowledgebase is a public database for protein sequence and function, covering the tree of life and over 220 million protein entries. Now, the whole community can use a new crowdsourcing annotation system to help scale up UniProt curation and receive proper attribution for their biocuration work., Competing Interests: The authors have declared that no competing interests exist.

The specification of the endostyle in non-vertebrate chordates and of the thyroid gland in vertebrates are fundamental steps in the evolution of the thyroid hormone (TH) signaling to coordinate development and body physiology in response to a range of environmental signals. The physiology and biology of TH signaling in vertebrates have been studied in the past, but a complete understanding of such a complex system is still lacking. Non-model species from non-vertebrate chordates may greatly improve our understanding of the evolution of this complex endocrine pathway. Adaptation of already existing proteins in order to perform new roles is a common feature observed during the course of evolution. Through sequence similarity approaches, we investigated the presence of bona fide thyroid peroxidase (TPO), iodothyronine deiodinase (DIO), and thyroid hormone receptors (THRs) in non-vertebrate and vertebrate chordates. Additionally, we determined both the conservation and divergence degrees of functional domains at the protein level. This study supports the hypothesis that non-vertebrate chordates have a functional thyroid hormone signaling system and provides additional information about its possible evolutionary adaptation.

In this article we present the synthesis and characterization of a new form of the membrane active peptide melittin: photomelittin. This peptide was created by substituting the proline residue in melittin for a synthetic azobenzene amino acid derivative. This azobenzene altered the membrane activity of the peptide while retaining much of the secondary structure. Furthermore, the peptide demonstrates added light-dependent activity in leakage assays. There is a 1.5-fold increase in activity when exposed to UV light as opposed to visible light. The peptides further exhibit light-dependent hemolytic activity against human red blood cells. This will enable future studies optimizing photomelittin and other azobenzene-containing membrane active peptides for uses in medicine, drug delivery, and other biotechnological applications., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The node-streak border region comprising notochord progenitor cells (NPCs) at the posterior node and neuro-mesodermal progenitor cells (NMPs) in the adjacent epiblast is the prime organizing center for axial elongation in mouse embryos. The T-box transcription factor brachyury (T) is essential for both formation of the notochord and maintenance of NMPs, and thus is a key regulator of trunk and tail development. The T promoter controlling T expression in NMPs and nascent mesoderm has been characterized in detail; however, control elements for T expression in the notochord have not been identified yet. We have generated a series of deletion alleles by CRISPR/Cas9 genome editing in mESCs, and analyzed their effects in mutant mouse embryos. We identified a 37 kb region upstream of T that is essential for notochord function and tailbud outgrowth. Within that region, we discovered a T-binding enhancer required for notochord cell specification and differentiation. Our data reveal a complex regulatory landscape controlling cell type-specific expression and function of T in NMP/nascent mesoderm and node/notochord, allowing proper trunk and tail development., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2021. Published by The Company of Biologists Ltd.)

The mapping from protein sequence to function is highly complex, making it challenging to predict how sequence changes will affect a protein's behavior and properties. We present a supervised deep learning framework to learn the sequence-function mapping from deep mutational scanning data and make predictions for new, uncharacterized sequence variants. We test multiple neural network architectures, including a graph convolutional network that incorporates protein structure, to explore how a network's internal representation affects its ability to learn the sequence-function mapping. Our supervised learning approach displays superior performance over physics-based and unsupervised prediction methods. We find that networks that capture nonlinear interactions and share parameters across sequence positions are important for learning the relationship between sequence and function. Further analysis of the trained models reveals the networks' ability to learn biologically meaningful information about protein structure and mechanism. Finally, we demonstrate the models' ability to navigate sequence space and design new proteins beyond the training set. We applied the protein G B1 domain (GB1) models to design a sequence that binds to immunoglobulin G with substantially higher affinity than wild-type GB1., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Membrane proteins are prone to misfolding and degradation. This is particularly true for mammalian forms of the gonadotropin-releasing hormone receptor (GnRHR). Although they function at the plasma membrane, mammalian GnRHRs accumulate within the secretory pathway. Their apparent instability is believed to have evolved through selection for attenuated GnRHR activity. Nevertheless, the molecular basis of this adaptation remains unclear. We show that adaptation coincides with a C-terminal truncation that compromises the translocon-mediated membrane integration of its seventh transmembrane domain (TM7). We also identify a series of polar residues in mammalian GnRHRs that compromise the membrane integration of TM2 and TM6. Reverting a lipid-exposed polar residue in TM6 to an ancestral hydrophobic residue restores expression with no impact on function. Evolutionary trends suggest variations in the polarity of this residue track with reproductive phenotypes. Our findings suggest that the marginal energetics of cotranslational folding can be exploited to tune membrane protein fitness., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Fusobacterium nucleatum is one of the most notorious species involved in colorectal cancer. It was reported that numerous outer membrane proteins (OMP) are actively involved in carcinogenesis. In this paper, the structure and stability of certain complexes, as well as DNA cleavage and ROS generation by fragments of OMP, were investigated using experimental and theoretical methods. Mass spectrometry, potentiometry, UV-Vis, CD, EPR, gel electrophoresis and calculations at the density functional theory (DFT) level were applied. Two consecutive model peptides, Ac-AKGHEHQLE-NH 2 and Ac-FGEHEHGRD-NH 2 , were studied. Both of these were rendered to form a variety of thermodynamically stable complexes with copper(II) ions. All of the complexes were stabilized, mainly due to interactions of metal with nitrogen and oxygen donor atoms, as well as rich hydrogen bond networks. It was also concluded that these complexes in the presence of hydrogen peroxide or ascorbic acid can effectively produce hydroxyl radicals and have an ability to cleave the DNA strands. Surprisingly, the second studied ligand at the micromolar concentration range causes overall DNA degradation.

Three decades of research have documented the spatiotemporal dynamics of RHO family GTPase membrane extraction regulated by guanine nucleotide dissociation inhibitors (GDIs), but the interplay of the kinetic mechanism and structural specificity of these interactions is as yet unresolved. To address this, we reconstituted the GDI-controlled spatial segregation of geranylgeranylated RHO protein RAC1 in vitro. Various biochemical and biophysical measurements provided unprecedented mechanistic details for GDI function with respect to RHO protein dynamics. We determined that membrane extraction of RHO GTPases by GDI occurs via a 3-step mechanism: (1) GDI non-specifically associates with the switch regions of the RHO GTPases; (2) an electrostatic switch determines the interaction specificity between the C-terminal polybasic region of RHO GTPases and two distinct negatively-charged clusters of GDI1; (3) a non-specific displacement of geranylgeranyl moiety from the membrane sequesters it into a hydrophobic cleft, effectively shielding it from the aqueous milieu. This study substantially extends the model for the mechanism of GDI-regulated RHO GTPase extraction from the membrane, and could have implications for clinical studies and drug development.

Scorpion venoms are mixtures of proteins, peptides and small molecular compounds with high specificity for ion channels and are therefore considered to be promising candidates in the venoms-to-drugs pipeline. Transcriptomes are important tools for studying the composition and expression of scorpion venom. Unfortunately, studying the venom gland transcriptome traditionally requires sacrificing the animal and therefore is always a single snapshot in time. This paper describes a new way of generating a scorpion venom gland transcriptome without sacrificing the animal, thereby allowing the study of the transcriptome at various time points within a single individual. By comparing these venom-derived transcriptomes to the traditional whole-telson transcriptomes we show that the relative expression levels of the major toxin classes are similar. We further performed a multi-day extraction using our proposed method to show the possibility of doing a multiple time point transcriptome analysis. This allows for the study of patterns of toxin gene activation over time a single individual, and allows assessment of the effects of diet, season and other factors that are known or likely to influence intraindividual venom composition. We discuss the gland characteristics that may allow this method to be successful in scorpions and provide a review of other venomous taxa to which this method may potentially be successfully applied., Competing Interests: The authors have declared that no competing interests exist.

Nitrate transport in cyanobacteria is mediated by ABC-transporter, which consists of a highly conserved ATP binding cassette (ABC) and a less conserved transmembrane domain (TMD). Under salt stress, recombinant glycinebetaine (GB) not only protected the rate of nitrate transport in transgenic Anabaena PCC 7120, rather stimulated the rate by interacting with the ABC-transporter proteins. In silico analyses revealed that nrtA protein consisted of 427 amino acids, the majority of which were hydrophobic and contained a Tat (twin-arginine translocation) signal profile of 34 amino acids (1-34). The nrtC subunit of 657 amino acids contained two hydrophobic distinct domains; the N-terminal (5-228 amino acids), which was 59% identical to nrtD (the ATP-binding subunit) and the C-terminal (268-591), 28.2% identical to nrtA, suggesting C-terminal as a solute binding domain and N-terminal as ATP binding domain. Subunit nrtD consisted of 277 amino acids and its N-terminal (21-254) was an ATP binding motif. Phylogenetic analysis revealed that nitrate-ABC-transporter proteins are highly conserved among the cyanobacterial species, though variation existed in sequences resulting in several subclades. Nostoc PCC 7120 was very close to Anabaena variabilis ATCC 29413, Anabaena sp. 4-3 and Anabaena sp. CA = ATCC 33047. On the other, Nostoc spp. NIES-3756 and PCC 7524 were often found in the same subclade suggesting more work before referring it to Anabaena PCC 7120 or Nostoc PCC 7120. The molecular interaction of nitrate with nrtA was hydrophilic, while hydrophobic with nrtC and nrtD. GB interaction with nrtACD was hydrophobic and showed higher affinity compared to nitrate., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests. The authors declare that there is no conflict of interest.

Infections typically begin with pathogens adhering to host cells. For bacteria, this adhesion can occur through specific ligand-binding domains. We identify a 20-kDa peptide-binding domain (PBD) in a 1.5-MDa RTX adhesin of a Gram-negative marine bacterium that colonizes diatoms. The crystal structure of this Ca 2+ -dependent PBD suggests that it may bind the C termini of host cell-surface proteins. A systematic peptide library analysis reveals an optimal tripeptide sequence with 30-nM affinity for the PBD, and X-ray crystallography details its peptide-protein interactions. Binding of the PBD to the diatom partner of the bacteria can be inhibited or competed away by the peptide, providing a molecular basis for inhibiting bacterium-host interactions. We further show that this PBD is found in other bacteria, including human pathogens such as Vibrio cholerae and Aeromonas veronii. Here, we produce the PBD ortholog from A. veronii and demonstrate, using the same peptide inhibitor, how pathogens may be prevented from adhering to their hosts., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Prior to this study, we discovered a protein characterized by many different amino acid sequences with the same number of amino acid residues. This turned out to be a unique cytochrome b, in which 1048 molecules out of 1689 contain 379 amino acid residues. A detailed study of the occurrence of this protein in living organisms at different taxonomic levels (from biological domains to biological orders of animals) has been carried out in the work presented here. We found that the main part of all b cytochromes is present in eukaryotes (99.2%), in biological kingdoms (95.9% in animals), in biological phylums (97.5% in chordates), and in biological classes (79.7% in mammals). Withal, this protein, containing 379 amino acid residues and characterized by many different amino acid sequences, is found only in eukaryotes (100%), only in animals (100%) and mainly in mammals (81.1%). Thus, a representative that has cytochrome b with a corresponding number of amino acid residues has not yet been identified among archaea and prokaryotes, while it is common in representatives of different biological types, classes, and orders of animals. It is believed that the structural diversity of a given protein within the same length and its one function of participation in the process of electron transfer relate to the physicochemical features of the extra- and intramembrane fragments of the polypeptide chain of this protein., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 Alexander A. Zamyatnin et al.)

6-aminohexanoic acid is an ω-amino acid with a hydrophobic, flexible structure. Although the ω-amino acid in question is mainly used clinically as an antifibrinolytic drug, other applications are also interesting and important. This synthetic lysine derivative, without an α-amino group, plays a significant role in chemical synthesis of modified peptides and in the polyamide synthetic fibers (nylon) industry. It is also often used as a linker in various biologically active structures. This review concentrates on the role of 6-aminohexanoic acid in the structure of various molecules.

Antiviral peptide (AVP) is a kind of antimicrobial peptide (AMP) that has the potential ability to fight against virus infection. Machine learning-based prediction with a computational biology approach can facilitate the development of the novel therapeutic agents. In this study, we proposed a double-stage classification scheme, named AVPIden, for predicting the AVPs and their functional activities against different viruses. The first stage is to distinguish the AVP from a broad-spectrum peptide collection, including not only the regular peptides (non-AMP) but also the AMPs without antiviral functions (non-AVP). The second stage is responsible for characterizing one or more virus families or species that the AVP targets. Imbalanced learning is utilized to improve the performance of prediction. The AVPIden uses multiple descriptors to precisely demonstrate the peptide properties and adopts explainable machine learning strategies based on Shapley value to exploit how the descriptors impact the antiviral activities. Finally, the evaluation performance of the proposed model suggests its ability to predict the antivirus activities and their potential functions against six virus families (Coronaviridae, Retroviridae, Herpesviridae, Paramyxoviridae, Orthomyxoviridae, Flaviviridae) and eight kinds of virus (FIV, HCV, HIV, HPIV3, HSV1, INFVA, RSV, SARS-CoV). The AVPIden gives an option for reinforcing the development of AVPs with the computer-aided method and has been deployed at http://awi.cuhk.edu.cn/AVPIden/., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Accurate prediction of immunogenic peptide recognized by T cell receptor (TCR) can greatly benefit vaccine development and cancer immunotherapy. However, identifying immunogenic peptides accurately is still a huge challenge. Most of the antigen peptides predicted in silico fail to elicit immune responses in vivo without considering TCR as a key factor. This inevitably causes costly and time-consuming experimental validation test for predicted antigens. Therefore, it is necessary to develop novel computational methods for precisely and effectively predicting immunogenic peptide recognized by TCR. Here, we described DLpTCR, a multimodal ensemble deep learning framework for predicting the likelihood of interaction between single/paired chain(s) of TCR and peptide presented by major histocompatibility complex molecules. To investigate the generality and robustness of the proposed model, COVID-19 data and IEDB data were constructed for independent evaluation. The DLpTCR model exhibited high predictive power with area under the curve up to 0.91 on COVID-19 data while predicting the interaction between peptide and single TCR chain. Additionally, the DLpTCR model achieved the overall accuracy of 81.03% on IEDB data while predicting the interaction between peptide and paired TCR chains. The results demonstrate that DLpTCR has the ability to learn general interaction rules and generalize to antigen peptide recognition by TCR. A user-friendly webserver is available at http://jianglab.org.cn/DLpTCR/. Additionally, a stand-alone software package that can be downloaded from https://github.com/jiangBiolab/DLpTCR., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

With the onset of the COVID-19 pandemic, the amount of data on genomic and proteomic sequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) stored in various databases has exponentially grown. A large volume of these data has led to the production of equally immense sets of immunological data, which require rigorous computational approaches to sort through and make sense of. Immunoinformatics has emerged in the recent decades as a field capable of offering this approach by bridging experimental and theoretical immunology with state-of-the-art computational tools. Here, we discuss how immunoinformatics can assist in the development of high-performance vaccines and drug discovery needed to curb the spread of SARS-CoV-2. Immunoinformatics can provide a set of computational tools to extract meaningful connections from the large sets of COVID-19 patient data, which can be implemented in the design of effective vaccines. With this in mind, we represent a pipeline to identify the role of immunoinformatics in COVID-19 treatment and vaccine development. In this process, a number of free databases of protein sequences, structures and mutations are introduced, along with docking web servers for assessing the interaction between antibodies and the SARS-CoV-2 spike protein segments as most commonly considered antigens in vaccine design., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Viruses represent one of the greatest threats to human health, necessitating the development of new antiviral drug candidates. Antiviral peptides often possess excellent biological activity and a favourable toxicity profile, and therefore represent a promising field of novel antiviral drugs. As the quantity of sequencing data grows annually, the development of an accurate in silico method for the prediction of peptide antiviral activities is important. This study leverages advances in deep learning and cheminformatics to produce a novel sequence-based deep neural network classifier for the prediction of antiviral peptide activity. The method outperforms the existent best-in-class, with an external test accuracy of 93.9%, Matthews correlation coefficient of 0.87 and an Area Under the Curve of 0.93 on the dataset of experimentally validated peptide activities. This cutting-edge classifier is available as an online web server at https://research.timmons.eu/ennavia, facilitating in silico screening and design of peptide antiviral drugs by the wider research community., (© The Author(s) 2021. Published by Oxford University Press.)