BIS2Analyzer: a server for co-evolution analysis of conserved protein families

Binding Evolution of the Dengue Virus Envelope Against DC-SIGN: A Combined Approach of Phylogenetics and Molecular Dynamics Analyses Over 30 Years of Dengue Virus in Brazil

The Red Queen Hypothesis (RQH), derived from Lewis Carroll's "Through the Looking-Glass", postulates that organisms must continually adapt in response to each other to maintain relative fitness. Within the context of host-pathogen interactions, the RQH implies an evolutionary arms race, wherein viruses evolve to exploit hosts and hosts evolve to resist viral invasion. This study delves into the dynamics of the RQH in the context of virus-cell interactions, specifically focusing on virus receptors and cell receptors. We observed multiple virus-host systems and noted patterns of co-evolution. As viruses evolved receptor-binding proteins to effectively engage with cell receptors, cells countered by altering their receptor genes. This ongoing mutual adaptation cycle has influenced the molecular intricacies of receptor-ligand interactions. Our data supports the RQH as a driving force behind the diversification and specialization of both viral and host cell receptors. Understanding this co-evolutionary dance offers insights into the unpredictability of emerging viral diseases and potential therapeutic interventions. Future research is crucial to dissect the nuanced molecular changes and the broader ecological consequences of this ever-evolving battle. Here, we combine phylogenetic inferences, structural modeling, and molecular dynamics analyses to describe the epidemiological characteristics of major Brazilian DENV strains that circulated from 1990 to 2022 from a combined perspective, thus providing us with a more detailed picture on the dynamics of such interactions over time.

Parallel evolution of picobirnaviruses from distinct ancestral origins

IMPORTANCE

Picobirnaviruses (PBVs) are highly heterogeneous viruses encoding a capsid and RdRp. Detected in a wide variety of animals with and without disease, their association with gastrointestinal and respiratory infections, and consequently their public health importance, has rightly been questioned. Determining the "true" host of Picobirnavirus lies at the center of this debate, as evidence exists for them having both vertebrate and prokaryotic origins. Using integrated and time-stamped phylogenetic approaches, we show they are contemporaneous viruses descending from two different ancestors: avian Reovirus and fungal Partitivirus. The fungal PBV-R2 species emerged with a single segment (RdRp) until it acquired a capsid from vertebrate PBV-R1 and PBV-R3 species. Protein and RNA folding analyses revealed how the former came to resemble the latter over time. Thus, parallel evolution from disparate hosts has driven the adaptation and genetic diversification of the Picobirnaviridae family.

Peptides of a Feather: How Computation Is Taking Peptide Therapeutics under Its Wing

Leveraging computation in the development of peptide therapeutics has garnered increasing recognition as a valuable tool to generate novel therapeutics for disease-related targets. To this end, computation has transformed the field of peptide design through identifying novel therapeutics that exhibit enhanced pharmacokinetic properties and reduced toxicity. The process of in-silico peptide design involves the application of molecular docking, molecular dynamics simulations, and machine learning algorithms. Three primary approaches for peptide therapeutic design including structural-based, protein mimicry, and short motif design have been predominantly adopted. Despite the ongoing progress made in this field, there are still significant challenges pertaining to peptide design including: enhancing the accuracy of computational methods; improving the success rate of preclinical and clinical trials; and developing better strategies to predict pharmacokinetics and toxicity. In this review, we discuss past and present research pertaining to the design and development of in-silico peptide therapeutics in addition to highlighting the potential of computation and artificial intelligence in the future of disease therapeutics.

Comparative Genome Analysis of Old World and New World TYLCV Reveals a Biasness toward Highly Variable Amino Acids in Coat Protein

Begomoviruses, belonging to the family Geminiviridae and the genus Begomovirus, are DNA viruses that are transmitted by whitefly Bemisia tabaci (Gennadius) in a circulative persistent manner. They can easily adapt to new hosts and environments due to their wide host range and global distribution. However, the factors responsible for their adaptability and coevolutionary forces are yet to be explored. Among BGVs, TYLCV exhibits the broadest range of hosts. In this study, we have identified variable and coevolving amino acid sites in the proteins of Tomato yellow leaf curl virus (TYLCV) isolates from Old World (African, Indian, Japanese, and Oceania) and New World (Central and Southern America). We focused on mutations in the coat protein (CP), as it is highly variable and interacts with both vectors and host plants. Our observations indicate that some mutations were accumulating in Old World TYLCV isolates due to positive selection, with the S149N mutation being of particular interest. This mutation is associated with TYLCV isolates that have spread in Europe and Asia and is dominant in 78% of TYLCV isolates. On the other hand, the S149T mutation is restricted to isolates from Saudi Arabia. We further explored the implications of these amino acid changes through structural modeling. The results presented in this study suggest that certain hypervariable regions in the genome of TYLCV are conserved and may be important for adapting to different host environments. These regions could contribute to the mutational robustness of the virus, allowing it to persist in different host populations.

Building Protein Atomic Models from Cryo-EM Density Maps and Residue Co-Evolution

Electron cryo-microscopy (cryo-EM) has emerged as a powerful method by which to obtain three-dimensional (3D) structures of macromolecular complexes at atomic or near-atomic resolution. However, de novo building of atomic models from near-atomic resolution (3–5 Å) cryo-EM density maps is a challenging task, in particular because poorly resolved side-chain densities hamper sequence assignment by automatic procedures at a lower resolution. Furthermore, segmentation of EM density maps into individual subunits remains a difficult problem when the structure of the subunits is not known, or when significant conformational rearrangement occurs between the isolated and associated form of the subunits. To tackle these issues, we have developed a graph-based method to thread most of the C-α trace of the protein backbone into the EM density map. The EM density is described as a weighted graph such that the resulting minimum spanning tree encompasses the high-density regions of the map. A pruning algorithm cleans the tree and finds the most probable positions of the C-α atoms, by using side-chain density when available, as a collection of C-α trace fragments. By complementing experimental EM maps with contact predictions from sequence co-evolutionary information, we demonstrate that this approach can correctly segment EM maps into individual subunits and assign amino acid sequences to backbone traces to generate atomic models.

Web-Based Protein Interactions Calculator Identifies Likely Proteome Coevolution with Alzheimer’s Disease-Associated Proteins

Protein–protein functional interactions arise from either transitory or permanent biomolecular associations and often lead to the coevolution of the interacting residues. Although mutual information has traditionally been used to identify coevolving residues within the same protein, its application between coevolving proteins remains largely uncharacterized. Therefore, we developed the Protein Interactions Calculator (PIC) to efficiently identify coevolving residues between two protein sequences using mutual information. We verified the algorithm using 2102 known human protein interactions and 233 known bacterial protein interactions, with a respective 1975 and 252 non-interacting protein controls. The average PIC score for known human protein interactions was 4.5 times higher than non-interacting proteins (p = 1.03 × 10⁻¹⁰⁸) and 1.94 times higher in bacteria (p = 1.22 × 10⁻³⁵). We then used the PIC scores to determine the probability that two proteins interact. Using those probabilities, we paired 37 Alzheimer’s disease-associated proteins with 8608 other proteins and determined the likelihood that each pair interacts, which we report through a web interface. The PIC had significantly higher sensitivity and residue-specific resolution not available in other algorithms. Therefore, we propose that the PIC can be used to prioritize potential protein interactions, which can lead to a better understanding of biological processes and additional therapeutic targets belonging to protein interaction groups.

iBIS2Analyzer: a web server for a phylogeny-driven coevolution analysis of protein families

Residue coevolution within and between proteins is used as a marker of physical interaction and/or residue functional cooperation. Pairs or groups of coevolving residues are extracted from multiple sequence alignments based on a variety of computational approaches. However, coevolution signals emerging in subsets of sequences might be lost if the full alignment is considered. iBIS2Analyzer is a web server dedicated to a phylogeny-driven coevolution analysis of protein families with different evolutionary pressure. It is based on the iterative version, iBIS², of the coevolution analysis method BIS, Blocks in Sequences. iBIS² is designed to iteratively select and analyse subtrees in phylogenetic trees, possibly large and comprising thousands of sequences. With iBIS2Analyzer, openly accessible at http://ibis2analyzer.lcqb.upmc.fr/, the user visualizes, compares and inspects clusters of coevolving residues by mapping them onto sequences, alignments or structures of choice, greatly simplifying downstream analysis steps. A rich and interactive graphic interface facilitates the biological interpretation of the results.

Secretory glycoprotein NS1 plays a crucial role in the particle formation of flaviviruses

Flaviviruses, which are globally distributed and cause a spectrum of potentially severe illnesses, pose a major threat to public health. Although Flaviviridae viruses, including flaviviruses, possess similar genome structures, only the flaviviruses encode the non-structural protein NS1, which resides in the endoplasmic reticulum (ER) and is secreted from cells after oligomerization. The ER-resident NS1 is known to be involved in viral genome replication, but the essential roles of secretory NS1 in the virus life cycle are not fully understood. Here we characterized the roles of secretory NS1 in the particle formation of flaviviruses. We first identified an amino acid residue essential for the NS1 secretion but not for viral genome replication by using protein-protein interaction network analyses and mutagenesis scanning. By using the recombinant flaviviruses carrying the identified NS1 mutation, we clarified that the mutant flaviviruses employed viral genome replication. We then constructed a recombinant NS1 with the identified mutation and demonstrated by physicochemical assays that the mutant NS1 was unable to form a proper oligomer or associate with liposomes. Finally, we showed that the functions of NS1 that were lost by the identified mutation could be compensated for by the in trans-expression of E^rns of pestiviruses and host exchangeable apolipoproteins, which participate in the infectious particle formation of pestiviruses and hepaciviruses in the family Flaviviridae, respectively. Collectively, our study suggests that secretory NS1 plays a role in the particle formation of flaviviruses through its interaction with the lipid membrane.

It is difficult to characterize the function of NS1 in the post-genome replication stages in the virus life cycle of flaviviruses. Here, by means of protein-protein interaction network analyses and mutagenesis scanning, we identified a unique mutation in NS1 by which the protein loses its secretory capacity while retaining its genome replication activity. Physicochemical assays using the mutant NS1 revealed that oligomerization of NS1 is responsible for the lipid association and secretion of NS1. In addition, we established a complementation assay that can evaluate the particle formation of Flaviviridae viruses. By using recombinant flaviviruses possessing the identified mutation in NS1, we clarified that NS1 is involved in particle formation. Our findings reveal that the flavivirus NS1 has at least two roles in the virus life cycles—namely, a role in infectious particle formation and a role in viral genome replication.

Evolution and co-evolution: insights into the divergence of plant heat shock factor genes

The Heat Shock Factor (Hsf) genes are widely distributed across the plant kingdom regulating the plant response to various abiotic stresses. In addition to natural selection, breeding and accelerated selection changed the structure and function of Hsf genes. 1076 Hsf genes from 30 genera from primitive algae to the most advanced plant species and major crop plants were used for phylogenetic analysis. The interspecific divergence was studied with 11 members of genus Oryza while intraspecific divergence was studied with sesame pan-genome adapted to diverse ecological niches. B2 genes in eudicots and monocots originated separately while A1 gave rise to the recently evolved Class-C genes and land colonization happened with evolution of A1 genes. An increase in the number of lineages in the Oryza clade with the evolution of AA genome indicated independent domestication and positive selection was observed in > 53% of loci whereas the highly conserved homologues were under purifying selection. The paralogous genes under positive selection exhibited more domain changes for diversified function and increased fitness. A significant co-evolving cluster involving amino acids Phenylalanine, Lysine and Valine played crucial role in maintaining hydrophobic core along with highly conserved Tryptophan residues. A mutation of Glutamic acid to Glutamine was observed in A8 genes of Lamiales affecting protein solvency. Breeding resulted in accumulation of mutations reducing the hydrophobicity of proteins and a further reduction in protein aggregation. This study identify genome duplications, non-neutral selection and co-evolving residues as causing drastic changes in the conserved domain of Hsf proteins.

Supplementary information

The online version contains supplementary material available at 10.1007/s12298-022-01183-7.

AutoCoEv—A High-Throughput In Silico Pipeline for Predicting Inter-Protein Coevolution

Protein–protein interactions govern cellular processes via complex regulatory networks, which are still far from being understood. Thus, identifying and understanding connections between proteins can significantly facilitate our comprehension of the mechanistic principles of protein functions. Coevolution between proteins is a sign of functional communication and, as such, provides a powerful approach to search for novel direct or indirect molecular partners. However, an evolutionary analysis of large arrays of proteins in silico is a highly time-consuming effort that has limited the usage of this method for protein pairs or small protein groups. Here, we developed AutoCoEv, a user-friendly, open source, computational pipeline for the search of coevolution between a large number of proteins. By driving 15 individual programs, culminating in CAPS2 as the software for detecting coevolution, AutoCoEv achieves a seamless automation and parallelization of the workflow. Importantly, we provide a patch to the CAPS2 source code to strengthen its statistical output, allowing for multiple comparison corrections and an enhanced analysis of the results. We apply the pipeline to inspect coevolution among 324 proteins identified to be located at the vicinity of the lipid rafts of B lymphocytes. We successfully detected multiple coevolutionary relations between the proteins, predicting many novel partners and previously unidentified clusters of functionally related molecules. We conclude that AutoCoEv, can be used to predict functional interactions from large datasets in a time- and cost-efficient manner.

The S100A7 nuclear interactors in autoimmune diseases: a coevolutionary study in mammals

S100A7, a member of the S100A family of Ca²⁺-binding proteins, is considered a key effector in immune response. In particular, S100A7 dysregulation has been associated with several diseases, including autoimmune disorders. At the nuclear level, S100A7 interacts with several protein-binding partners which are involved in transcriptional regulation and DNA repair. By using the BioGRID and GAAD databases, S100A7 nuclear interactors with a putative involvement in autoimmune diseases were retrieved. We selected fatty acid-binding protein 5 (FABP5), autoimmune regulator (AIRE), cystic fibrosis transmembrane conductance regulator (CFTR), chromodomain helicase DNA-binding protein 4 (CHD4), epidermal growth factor receptor (EGFR), estrogen receptor 1 (ESR1), histone deacetylase 2 (HDAC2), v-myc avian myelocytomatosis viral oncogene homolog (MYC), protection of telomeres protein 1 (POT1), telomeric repeat-binding factor (NIMA-interacting) 1 (TERF1), telomeric repeat-binding factor 2 (TERF2), and Zic family member 1 (ZIC1). Linear correlation coefficients between interprotein distances were calculated with MirrorTree. Coevolution clusters were also identified with the use of a recent version of the Blocks in Sequences (BIS2) algorithm implemented in the BIS2Analyzer web server. Analysis of pair positions identified interprotein coevolving clusters between S100A7 and the binding partners CFTR and TERF1. Such findings could guide further analysis to better elucidate the function of S100A7 and its binding partners and to design drugs targeting for these molecules in autoimmune diseases.

ATP-Binding Cassette Transporters: Snap-on Complexes?

ATP-binding cassette (ABC) transporters are one of the largest families of membrane proteins in prokaryotic organisms. Much is now understood about the structure of these transporters and many reviews have been written on that subject. In contrast, less has been written on the assembly of ABC transporter complexes and this will be a major focus of this book chapter. The complexes are formed from two cytoplasmic subunits that are highly conserved (in terms of their primary and three-dimensional structures) across the whole family. These ATP-binding subunits give rise to the name of the family. They must assemble with two transmembrane subunits that will typically form the permease component of the transporter. The transmembrane subunits have been found to be surprisingly diverse in structure when the whole family is examined, with seven distinct folds identified so far. Hence nucleotide-binding subunits appear to have been bolted on to a variety of transmembrane platforms during evolution, leading to a greater variety in function. Furthermore, many importers within the family utilise a further external substrate-binding component to trap scarce substrates and deliver them to the correct permease components. In this chapter, we will discuss whether assembly of the various ABC transporter subunits occurs with high fidelity within the crowded cellular environment and whether promiscuity in assembly of transmembrane and cytoplasmic components can occur. We also discuss the new AlphaFold protein structure prediction tool which predicts a new type of transmembrane domain fold within the ABC transporters that is associated with cation exporters of bacteria and plants.

Bilateral visual projections exist in non-teleost bony fish and predate the emergence of tetrapods

In most vertebrates, camera-style eyes contain retinal ganglion cell neurons that project to visual centers on both sides of the brain. However, in fish, ganglion cells were thought to innervate only the contralateral side, suggesting that bilateral visual projections appeared in tetrapods. Here we show that bilateral visual projections exist in non-teleost fishes and that the appearance of ipsilateral projections does not correlate with terrestrial transition or predatory behavior. We also report that the developmental program that specifies visual system laterality differs between fishes and mammals, as the Zic2 transcription factor, which specifies ipsilateral retinal ganglion cells in tetrapods, appears to be absent from fish ganglion cells. However, overexpression of human ZIC2 induces ipsilateral visual projections in zebrafish. Therefore, the existence of bilateral visual projections likely preceded the emergence of binocular vision in tetrapods.

Interaction between matrix metalloproteinase-9 (MMP-9) and neutrophil gelatinase-associated lipocalin (NGAL): A recent evolutionary event in primates

Matrix metalloproteases are known to represent an early step in the evolution of the immune system. Similarly, neutrophil gelatinase-associated lipocalin is known to be a key effector in immune response. MMP-9 interacts with NGAL, but their interaction mechanisms remain unclear. Functional interaction between proteins is ensured by coevolution. Protein coevolution was inferred by calculating the linear correlation coefficients between inter-protein distance matrices using MirrorTree. Among examined mammal species, we found a robust signal of MMP-9/NGAL coevolution exclusively within Primates (R = 0.96, p < 1e-06). Owing to the high conservation of these proteins among Mammals, we chose to utilize a recent version of Blocks in Sequences (BIS2) algorithm implemented in BIS2Analyzer webserver. Coevolution clusters between the two proteins were identified in MMP-9 fibronectin and hemopexin domains. Our results suggest that MMP-9/NGAL interaction is a recent evolutionary acquisition in Primates. Furthermore, MMP-9 hemopexin domain would represent a promising target for drug design against these molecules.

Comprehensive Study on Enhancing Low-Quality Position-Specific Scoring Matrix with Deep Learning for Accurate Protein Structure Property Prediction: Using Bagging Multiple Sequence Alignment Learning

Accurate predictions of protein structure properties, for example, secondary structure and solvent accessibility, are essential in analyzing the structure and function of a protein. Position-specific scoring matrix (PSSM) features are widely used in the structure property prediction. However, some proteins may have low-quality PSSM features due to insufficient homologous sequences, leading to limited prediction accuracy. To address this limitation, we propose an enhancing scheme for PSSM features. We introduce the "Bagging MSA" (multiple sequence alignment) method to calculate PSSM features used to train our model, adopt a convolutional network to capture local context features and bidirectional long short-term memory for long-term dependencies, and integrate them under an unsupervised framework. Structure property prediction models are then built upon such enhanced PSSM features for more accurate predictions. Moreover, we develop two frameworks to evaluate the effectiveness of the enhanced PSSM features, which also bring proposed method into real-world scenarios. Empirical evaluation of CB513, CASP11, and CASP12 data sets indicates that our unsupervised enhancing scheme indeed generates more informative PSSM features for structure property prediction.

Predicted Structural Variability of Mycobacterium tuberculosis PPE18 Protein With Immunological Implications Among Clinical Strains

Recent advancements in vaccinology have led to the development of the M72/AS01E subunit vaccine, of which the major component is the Mycobacterium tuberculosis (MTB) PPE18 protein. Previous studies have demonstrated the genetic variability of the gene encoding PPE18 protein and the resulting peptide changes in diverse clinical strains of MTB; however, none have modeled the structural changes resulting from these peptide changes and their immunological implications. In this study, we investigated the structural predictions of 29 variant PPE18 proteins previously reported. We found evidence that PPE18 is at least a two-domain protein, with a highly conserved first domain and a largely variable second domain that has different coevolutionary clusters. Further, we investigated putative epitope sites in the clinical variants of PPE18 using prediction software. We found a negative relationship between T-cell epitope number and residue variability, while B-cell epitope likelihood was positively correlated with residue variability. Moreover, we found far more residues in the second domain predicted to be B-cell epitopes compared with the first domain. These results suggest an important functional role of the first domain and a role in immune evasion for the second, which extends our knowledge base of the basic biology of the PPE18 protein and indicates the need for further study into non-traditional immunological responses to TB.

Context-dependent Cryptic Roles of Specific Residues in Substrate Selectivity of the UapA Purine Transporter

Members of the ubiquitous Nucleobase Ascorbate Transporter (NAT) family are H⁺ or Na⁺ symporters specific for the cellular uptake of either purines and pyrimidines or L-ascorbic acid. Despite the fact that several bacterial and fungal members have been extensively characterised at a genetic, biochemical or cellular level, and crystal structures of NAT members from Escherichia coli and Aspergillus nidulans have been determined pointing to a mechanism of transport, we have little insight on how substrate selectivity is determined. Here, we present systematic mutational analyses, rational combination of mutations, and novel genetic screens that reveal cryptic context-dependent roles of partially conserved residues in the so-called NAT signature motif in determining the specificity of the UapA transporter of A. nidulans. We show that specific NAT signature motif substitutions, alone and in combinations with each other or with distant mutations in residues known to affect substrate selectivity, lead to novel UapA versions possessing variable transport capacities and specificities for nucleobases. In particular, we show that a UapA version including the quadruple mutation T405S/F406Y/A407S/Q408E in the NAT signature motif (UapA-SYSE) becomes incapable of purine transport, but gains a novel pyrimidine-related profile, which can be further altered to a more promiscuous purine/pyrimidine profile when combined with replacements at distantly located residues, especially at F528. Our results reveal that UapA specificity is genetically highly modifiable and allow us to speculate on how the elevator-type mechanism of transport might account for this flexibility.

Variation in selection constraints on teleost TLRs with emphasis on their repertoire in the Walking catfish, Clarias batrachus

The high degree of conservation of toll-like receptors (TLRs), and yet their subtle variations for better adaptation of species in the host–pathogen arms race make them worthy candidates for understanding evolution. We have attempted to track the trend of TLR evolution in the most diverse vertebrate group—teleosts, where Clarias batrachus was given emphasis, considering its traits for terrestrial adaptation. Eleven C. batrachus TLRs (TLR1, 2, 3, 5, 7, 8 9, 13, 22, 25, 26) were identified in this study which clustered in proximity to its Siluriformes relative orthologues in the phylogenetic analysis of 228 TLRs from 25 teleosts. Ten TLRs (TLR1, 2, 3, 5, 7, 8 9, 13, 21, 22) with at least 15 member orthologues for each alignment were processed for selection pressure and coevolutionary analysis. TLR1, 7, 8 and 9 were found to be under positive selection in the alignment-wide test. TLR1 also showed maximum episodic diversification in its clades while the teleost group Eupercaria showed the maximum divergence in their TLR repertoire. Episodic diversification was evident in C. batrachus TLR1 and 7 alignments. These results present a strong evidence of a divergent TLR repertoire in teleosts which may be contributing towards species-specific variation in TLR functions.

COVTree: Coevolution in OVerlapped sequences by Tree analysis server

Overlapping genes are commonplace in viruses and play an important role in their function and evolution. For these genes, molecular coevolution may be seen as a mechanism to decrease the evolutionary constraints of amino acid positions in the overlapping regions and to tolerate or compensate unfavorable mutations. Tracing these mutational sites, could help to gain insight on the direct or indirect effect of the mutations in the corresponding overlapping proteins. In the past, coevolution analysis has been used to identify residue pairs and coevolutionary signatures within or between proteins that served as markers of physical interactions and/or functional relationships. Coevolution in OVerlapped sequences by Tree analysis (COVTree) is a web server providing the online analysis of coevolving amino-acid pairs in overlapping genes, where residues might be located inside or outside the overlapping region. COVTree is designed to handle protein families with various characteristics, among which those that typically display a small number of highly conserved sequences. It is based on BIS2, a fast version of the coevolution analysis tool Blocks in Sequences (BIS). COVTree provides a rich and interactive graphical interface to ease biological interpretation of the results and it is openly accessible at http://www.lcqb.upmc.fr/COVTree/.

CoevDB: a database of intramolecular coevolution among protein-coding genes of the bony vertebrates

The study of molecular coevolution, due to its potential to identify gene regions under functional or structural constraints, has recently been subject to numerous scientific inquiries. Particular efforts have been conducted to develop methods predicting the presence of coevolution in molecular sequences. Among these methods, a few aim to model the underlying evolutionary process of coevolution, which enable to differentiate the shared history of genes to coevolution and thus improve their accuracy. However, the usage of such methods remains sparse due to their expensive computational cost and the lack of resources alleviating this issue. Here we present CoevDB (http://phylodb.unil.ch/CoevDB), a database containing the result of a large-scale analysis of intramolecular coevolution of 8201 protein-coding genes of bony vertebrates. The web interface of CoevDB gives access to the results to 800 millions of statistical tests corresponding to all the pairs of sites analyzed. Several type of queries enable users to explore the database by either targeting specific genes or by discovering genes having promising estimations of coevolution.

S100A7/Ran-binding protein 9 coevolution in mammals

S100A7 has been suggested to interact with Ran-binding protein 9. Both proteins are nowadays considered key effectors in immune response. Functional interaction between proteins is ensured by coevolution. The mechanisms of vertebrate coevolution between S100A7 and RanBP9 remain unclear. Several approaches for studying coevolution have been developed. Protein coevolution was inferred by calculating the linear correlation coefficients between inter-protein distance matrices using Mirrortree. We found an overall moderate correlation value (R = 0.53, p < 1e-06). Moreover, owing to the high conservation of RanBP9 protein among vertebrates, we chose to utilize a recent version of Blocks in Sequences (BIS2) algorithm implemented in BIS2Analyzer webserver. A coevolution cluster was identified between the two proteins (p < 8.10e-05). In conclusion, our coevolutionary analysis suggests that amino acid variations may modulate S100A7/RanBP9 interaction with potential pathogenic effects. Such findings could guide further analysis to better elucidate the function of S100A7 and RanBP9 and to design drugs targeting for these molecules in diseases.

Disease-relevant mutations alter amino acid co-evolution networks in the second nucleotide binding domain of CFTR

Cystic Fibrosis (CF) is an inherited disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) ion channel. Mutations in CFTR cause impaired chloride ion transport in the epithelial tissues of patients leading to cardiopulmonary decline and pancreatic insufficiency in the most severely affected patients. CFTR is composed of twelve membrane-spanning domains, two nucleotide-binding domains (NBDs), and a regulatory domain. The most common mutation in CFTR is a deletion of phenylalanine at position 508 (ΔF508) in NBD1. Previous research has primarily concentrated on the structure and dynamics of the NBD1 domain; However numerous pathological mutations have also been found in the lesser-studied NBD2 domain. We have investigated the amino acid co-evolved network of interactions in NBD2, and the changes that occur in that network upon the introduction of CF and CF-related mutations (S1251N(T), S1235R, D1270N, N1303K(T)). Extensive coupling between the α- and β-subdomains were identified with residues in, or near Walker A, Walker B, H-loop and C-loop motifs. Alterations in the predicted residue network varied from moderate for the S1251T perturbation to more severe for N1303T. The S1235R and D1270N networks varied greatly compared to the wildtype, but these CF mutations only affect ion transport preference and do not severely disrupt CFTR function, suggesting dynamic flexibility in the network of interactions in NBD2. Our results also suggest that inappropriate interactions between the β-subdomain and Q-loop could be detrimental. We also identified mutations predicted to stabilize the NBD2 residue network upon introduction of the CF and CF-related mutations, and these predicted mutations are scored as benign by the MUTPRED2 algorithm. Our results suggest the level of disruption of the co-evolution predictions of the amino acid networks in NBD2 does not have a straightforward correlation with the severity of the CF phenotypes observed.

Large-Scale Comparison of Toxin and Antitoxins in Listeria monocytogenes

Toxin–antitoxin systems (TASs) are widely distributed in prokaryotes and encode pairs of genes involved in many bacterial biological processes and mechanisms, including pathogenesis. The TASs have not been extensively studied in Listeria monocytogenes (Lm), a pathogenic bacterium of the Firmicutes phylum causing infections in animals and humans. Using our recently published TASmania database, we focused on the known and new putative TASs in 352 Listeria monocytogenes genomes and identified the putative core gene TASs (cgTASs) with the Pasteur BIGSdb-Lm database and, by complementarity, the putative accessory gene TAS (acTASs). We combined the cgTASs with those of an additional 227 L. monocytogenes isolates from our previous studies containing metadata information. We discovered that the differences in 14 cgTAS alleles are sufficient to separate the four main lineages of Listeria monocytogenes. Analyzing these differences in more details, we uncovered potentially co-evolving residues in some pairs of proteins in cgTASs, probably essential for protein–protein interactions within the TAS complex.

Coevolution analysis of amino-acids reveals diversified drug-resistance solutions in viral sequences: a case study of hepatitis B virus

The study of mutational landscapes of viral proteins is fundamental for the understanding of the mechanisms of cross-resistance to drugs and the design of effective therapeutic strategies based on several drugs. Antiviral therapy with nucleos(t)ide analogues targeting the hepatitis B virus (HBV) polymerase protein (Pol) can inhibit disease progression by suppression of HBV replication and makes it an important case study. In HBV, treatment may fail due to the emergence of drug-resistant mutants. Primary and compensatory mutations have been associated with lamivudine resistance, whereas more complex mutational patterns are responsible for resistance to other HBV antiviral drugs. So far, all known drug-resistance mutations are located in one of the four Pol domains, called reverse transcriptase. We demonstrate that sequence covariation identifies drug-resistance mutations in viral sequences. A new algorithmic strategy, BIS2TreeAnalyzer, is designed to apply the coevolution analysis method BIS2, successfully used in the past on small sets of conserved sequences, to large sets of evolutionary related sequences. When applied to HBV, BIS2TreeAnalyzer highlights diversified viral solutions by discovering thirty-seven positions coevolving with residues known to be associated with drug resistance and located on the four Pol domains. These results suggest a sequential mechanism of emergence for some mutational patterns. They reveal complex combinations of positions involved in HBV drug resistance and contribute with new information to the landscape of HBV evolutionary solutions. The computational approach is general and can be applied to other viral sequences when compensatory mutations are presumed.

MISTIC2: comprehensive server to study coevolution in protein families

Correlated mutations between residue pairs in evolutionarily related proteins arise from constraints needed to maintain a functional and stable protein. Identifying these inter-related positions narrows down the search for structurally or functionally important sites. MISTIC is a server designed to assist users to calculate covariation in protein families and provide them with an interactive tool to visualize the results. Here, we present MISTIC2, an update to the previous server, that allows to calculate four covariation methods (MIp, mfDCA, plmDCA and gaussianDCA). The results visualization framework has been reworked for improved performance, compatibility and user experience. It includes a circos representation of the information contained in the alignment, an interactive covariation network, a 3D structure viewer and a sequence logo. Others components provide additional information such as residue annotations, a roc curve for assessing contact prediction, data tables and different ways of filtering the data and exporting figures. Comparison of different methods is easily done and scores combination is also possible. A newly implemented web service allows users to access MISTIC2 programmatically using an API to calculate covariation and retrieve results. MISTIC2 is available at: https://mistic2.leloir.org.ar.

Population Structure, Molecular Epidemiology, and β-Lactamase Diversity among Stenotrophomonas maltophilia Isolates in the United States

Stenotrophomonas maltophilia is a Gram-negative, nonfermenting, environmental bacillus that is an important cause of nosocomial infections, primarily associated with the respiratory tract in the immunocompromised population. Aiming to understand the population structure, microbiological characteristics and impact of allelic variation on β-lactamase structure and function, we collected 130 clinical isolates from across the United States. Identification of 90 different sequence types (STs), of which 63 are new allelic combinations, demonstrates the high diversity of this species. The majority of the isolates (45%) belong to genomic group 6. We also report excellent activity of the ceftazidime-avibactam and aztreonam combination, especially against strains recovered from blood and respiratory infections for which the susceptibility is higher than the susceptibility to trimethoprim-sulfamethoxazole, considered the "first-line" antibiotic to treat S. maltophilia Analysis of 73 blaL1 and 116 blaL2 genes identified 35 and 43 novel variants of L1 and L2 β-lactamases, respectively. Investigation of the derived amino acid sequences showed that substitutions are mostly conservative and scattered throughout the protein, preferentially affecting positions that do not compromise enzyme function but that may have an impact on substrate and inhibitor binding. Interestingly, we detected a probable association between a specific type of L1 and L2 and genomic group 6. Taken together, our results provide an overview of the molecular epidemiology of S. maltophilia clinical strains from the United States. In particular, the discovery of new L1 and L2 variants warrants further study to fully understand the relationship between them and the β-lactam resistance phenotype in this pathogen.IMPORTANCE Multiple antibiotic resistance mechanisms, including two β-lactamases, L1, a metallo-β-lactamase, and L2, a class A cephalosporinase, make S. maltophilia naturally multidrug resistant. Thus, infections caused by S. maltophilia pose a big therapeutic challenge. Our study aims to understand the microbiological and molecular characteristics of S. maltophilia isolates recovered from human sources. A highlight of the resistance profile of this collection is the excellent activity of the ceftazidime-avibactam and aztreonam combination. We hope this result prompts controlled and observational studies to add clinical data on the utility and safety of this therapy. We also identify 35 and 43 novel variants of L1 and L2, respectively, some of which harbor novel substitutions that could potentially affect substrate and/or inhibitor binding. We believe our results provide valuable knowledge to understand the epidemiology of this species and to advance mechanism-based inhibitor design to add to the limited arsenal of antibiotics active against this pathogen.

A Single Mutation Increases the Thermostability and Activity of Aspergillus terreus Amine Transaminase

Enhancing the thermostability of (R)-selective amine transaminases (AT-ATA) will expand its application in the asymmetric synthesis of chiral amines. In this study, mutual information and coevolution networks of ATAs were analyzed by the Mutual Information Server to Infer Coevolution (MISTIC). Subsequently, the amino acids most likely to influence the stability and function of the protein were investigated by alanine scanning and saturation mutagenesis. Four stabilized mutants (L118T, L118A, L118I, and L118V) were successfully obtained. The best mutant, L118T, exhibited an improved thermal stability with a 3.7-fold enhancement in its half-life (t_1/2) at 40 °C and a 5.3 °C increase in T₅₀¹⁰ compared to the values for the wild-type protein. By the differential scanning fluorimetry (DSF) analysis, the best mutant, L118T, showed a melting temperature (T_m) of 46.4 °C, which corresponded to a 5.0 °C increase relative to the wild-type AT-ATA (41.4 °C). Furthermore, the most stable mutant L118T displayed the highest catalytic efficiency among the four stabilized mutants.

Ancient Origin of the CARD-Coiled Coil/Bcl10/MALT1-Like Paracaspase Signaling Complex Indicates Unknown Critical Functions

The CARD–coiled coil (CC)/Bcl10/MALT1-like paracaspase (CBM) signaling complexes composed of a CARD–CC family member (CARD-9, -10, -11, or -14), Bcl10, and the type 1 paracaspase MALT1 (PCASP1) play a pivotal role in immunity, inflammation, and cancer. Targeting MALT1 proteolytic activity is of potential therapeutic interest. However, little is known about the evolutionary origin and the original functions of the CBM complex. Type 1 paracaspases originated before the last common ancestor of planulozoa (bilaterians and cnidarians). Notably in bilaterians, Ecdysozoa (e.g., nematodes and insects) lacks Bcl10, whereas other lineages have a Bcl10 homolog. A survey of invertebrate CARD–CC homologs revealed such homologs only in species with Bcl10, indicating an ancient common origin of the entire CBM complex. Furthermore, vertebrate-like Syk/Zap70 tyrosine kinase homologs with the ITAM-binding SH2 domain were only found in invertebrate organisms with CARD–CC/Bcl10, indicating that this pathway might be related to the original function of the CBM complex. Moreover, the type 1 paracaspase sequences from invertebrate organisms that have CARD–CC/Bcl10 are more similar to vertebrate paracaspases. Functional analysis of protein–protein interactions, NF-κB signaling, and CYLD cleavage for selected invertebrate type 1 paracaspase and Bcl10 homologs supports this scenario and indicates an ancient origin of the CARD–CC/Bcl10/paracaspase signaling complex. By contrast, many of the known MALT1-associated activities evolved fairly recently, indicating that unknown functions are at the basis of the protein conservation. As a proof-of-concept, we provide initial evidence for a CBM- and NF-κB-independent neuronal function of the Caenorhabditis elegans type 1 paracaspase malt-1. In conclusion, this study shows how evolutionary insights may point at alternative functions of MALT1.

A protein coevolution method uncovers critical features of the Hepatitis C Virus fusion mechanism

Amino-acid coevolution can be referred to mutational compensatory patterns preserving the function of a protein. Viral envelope glycoproteins, which mediate entry of enveloped viruses into their host cells, are shaped by coevolution signals that confer to viruses the plasticity to evade neutralizing antibodies without altering viral entry mechanisms. The functions and structures of the two envelope glycoproteins of the Hepatitis C Virus (HCV), E1 and E2, are poorly described. Especially, how these two proteins mediate the HCV fusion process between the viral and the cell membrane remains elusive. Here, as a proof of concept, we aimed to take advantage of an original coevolution method recently developed to shed light on the HCV fusion mechanism. When first applied to the well-characterized Dengue Virus (DENV) envelope glycoproteins, coevolution analysis was able to predict important structural features and rearrangements of these viral protein complexes. When applied to HCV E1E2, computational coevolution analysis predicted that E1 and E2 refold interdependently during fusion through rearrangements of the E2 Back Layer (BL). Consistently, a soluble BL-derived polypeptide inhibited HCV infection of hepatoma cell lines, primary human hepatocytes and humanized liver mice. We showed that this polypeptide specifically inhibited HCV fusogenic rearrangements, hence supporting the critical role of this domain during HCV fusion. By combining coevolution analysis and in vitro assays, we also uncovered functionally-significant coevolving signals between E1 and E2 BL/Stem regions that govern HCV fusion, demonstrating the accuracy of our coevolution predictions. Altogether, our work shed light on important structural features of the HCV fusion mechanism and contributes to advance our functional understanding of this process. This study also provides an important proof of concept that coevolution can be employed to explore viral protein mediated-processes, and can guide the development of innovative translational strategies against challenging human-tropic viruses.

Several virus-mediated molecular processes remain poorly described, which dampen the development of potent anti-viral therapies. Hence, new experimental strategies need to be undertaken to improve and accelerate our understanding of these processes. Here, as a proof of concept, we employ amino-acid coevolution as a tool to gain insights into the structural rearrangements of Hepatitis C Virus (HCV) envelope glycoproteins E1 and E2 during virus fusion with the cell membrane, and provide a basis for the inhibition of this process. Our coevolution analysis predicted that a specific domain of E2, the Back Layer (BL) is involved into significant conformational changes with E1 during the fusion of the HCV membrane with the cellular membrane. Consistently, a recombinant, soluble form of the BL was able to inhibit E1E2 fusogenic rearrangements and HCV infection. Moreover, predicted coevolution networks involving E1 and BL residues, as well as E1 and BL-adjacent residues, were found to modulate virus fusion. Our data shows that coevolution analysis is a powerful and underused approach that can provide significant insights into the functions and structural rearrangements of viral proteins. Importantly, this approach can also provide structural and molecular basis for the design of effective anti-viral drugs, and opens new perspectives to rapidly identify effective antiviral strategies against emerging and re-emerging viral pathogens.

The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families

The visualCMAT web-server was designed to assist experimental research in the fields of protein/enzyme biochemistry, protein engineering, and drug discovery by providing an intuitive and easy-to-use interface to the analysis of correlated mutations/co-evolving residues. Sequence and structural information describing homologous proteins are used to predict correlated substitutions by the Mutual information-based CMAT approach, classify them into spatially close co-evolving pairs, which either form a direct physical contact or interact with the same ligand (e.g. a substrate or a crystallographic water molecule), and long-range correlations, annotate and rank binding sites on the protein surface by the presence of statistically significant co-evolving positions. The results of the visualCMAT are organized for a convenient visual analysis and can be downloaded to a local computer as a content-rich all-in-one PyMol session file with multiple layers of annotation corresponding to bioinformatic, statistical and structural analyses of the predicted co-evolution, or further studied online using the built-in interactive analysis tools. The online interactivity is implemented in HTML5 and therefore neither plugins nor Java are required. The visualCMAT web-server is integrated with the Mustguseal web-server capable of constructing large structure-guided sequence alignments of protein families and superfamilies using all available information about their structures and sequences in public databases. The visualCMAT web-server can be used to understand the relationship between structure and function in proteins, implemented at selecting hotspots and compensatory mutations for rational design and directed evolution experiments to produce novel enzymes with improved properties, and employed at studying the mechanism of selective ligand's binding and allosteric communication between topologically independent sites in protein structures. The web-server is freely available at https://biokinet.belozersky.msu.ru/visualcmat and there are no login requirements.