Scoring residue conservation

Structural and energetic analyses of SARS-CoV-2 N-terminal domain characterise sugar binding pockets and suggest putative impacts of variants on COVID-19 transmission

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 is an ongoing pandemic that causes significant health/socioeconomic burden. Variants of concern (VOCs) have emerged affecting transmissibility, disease severity and re-infection risk. Studies suggest that the - N-terminal domain (NTD) of the spike protein may have a role in facilitating virus entry via sialic-acid receptor binding. Furthermore, most VOCs include novel NTD variants. Despite global sequence and structure similarity, most sialic-acid binding pockets in NTD vary across coronaviruses. Our work suggests ongoing evolutionary tuning of the sugar-binding pockets and recent analyses have shown that NTD insertions in VOCs tend to lie close to loops. We extended the structural characterisation of these sugar-binding pockets and explored whether variants could enhance sialic acid-binding. We found that recent NTD insertions in VOCs (i.e., Gamma, Delta and Omicron variants) and emerging variants of interest (VOIs) (i.e., Iota, Lambda and Theta variants) frequently lie close to sugar-binding pockets. For some variants, including the recent Omicron VOC, we find increases in predicted sialic acid-binding energy, compared to the original SARS-CoV-2, which may contribute to increased transmission. These binding observations are supported by molecular dynamics simulations (MD). We examined the similarity of NTD across Betacoronaviruses to determine whether the sugar-binding pockets are sufficiently similar to be exploited in drug design. Whilst most pockets are too structurally variable, we detected a previously unknown highly structurally conserved pocket which can be investigated in pursuit of a generic pan-Betacoronavirus drug. Our structure-based analyses help rationalise the effects of VOCs and provide hypotheses for experiments. Our findings suggest a strong need for experimental monitoring of changes in NTD of VOCs.

Mollusc Crystallins: Physical and Chemical Properties and Phylogenetic Analysis

The purpose of the present study was to perform bioinformatic analysis of crystallin diversity in aquatic molluscs based on the sequences in the NCBI Protein database. The objectives were as follows: (1) analysis of some physical and chemical properties of mollusc crystallins, (2) comparison of mollusc crystallins with zebrafish and cubomedusa Tripedalia cystophora crystallins, and (3) determination of the most probable candidates for the role of gastropod eye crystallins. The calculated average GRAVY values revealed that the majority of the seven crystallin groups, except for μ- and ζ-crystallins, were hydrophilic proteins. The predominant predicted secondary structures of the crystallins in most cases were α-helices and coils. The highest values of refractive index increment (dn/dc) were typical for crystallins of aquatic organisms with known lens protein composition (zebrafish, cubomedusa, and octopuses) and for S-crystallin of Pomacea canaliculata. The evolutionary relationships between the studied crystallins, obtained from multiple sequence alignments using Clustal Omega and MUSCLE, and the normalized conservation index, calculated by Mirny, showed that the most conservative proteins were Ω-crystallins but the most diverse were S-crystallins. The phylogenetic analysis of crystallin was generally consistent with modern mollusc taxonomy. Thus, α- and S-, and, possibly, J1A-crystallins, can be assumed to be the most likely candidates for the role of gastropod lens crystallins.

Architecture of the yeast Pol III pre-termination complex and pausing mechanism on poly(dT) termination signals

RNA polymerase (Pol) III is specialized to transcribe short, abundant RNAs, for which it terminates transcription on polythymine (dT) stretches on the non-template (NT) strand. When Pol III reaches the termination signal, it pauses and forms the pre-termination complex (PTC). Here, we report cryoelectron microscopy (cryo-EM) structures of the yeast Pol III PTC and complementary functional states at resolutions of 2.7-3.9 Å. Pol III recognizes the poly(dT) termination signal with subunit C128 that forms a hydrogen-bond network with the NT strand and, thereby, induces pausing. Mutating key interacting residues interferes with transcription termination in vitro, impairs yeast growth, and causes global termination defects in vivo, confirming our structural results. Additional cryo-EM analysis reveals that C53-C37, a Pol III subcomplex and key termination factor, participates indirectly in Pol III termination. We propose a mechanistic model of Pol III transcription termination and rationalize why Pol III, unlike Pol I and Pol II, terminates on poly(dT) signals.

Rotavirus vaccine-derived cases in Belgium: Evidence for reversion of attenuating mutations and alternative causes of gastroenteritis

Since the introduction of live-attenuated rotavirus vaccines in Belgium in 2006, surveillance has routinely detected rotavirus vaccine-derived strains. However, their genomic landscape and potential role in gastroenteritis have not been thoroughly investigated. We compared VP7 and VP4 nucleotide sequences obtained from rotavirus surveillance with the Rotarix vaccine sequence. As a result, we identified 80 vaccine-derived strains in 5125 rotavirus-positive infants with gastroenteritis from 2007 to 2018. Using both viral metagenomics and reverse transcription qPCR, we evaluated the vaccine strains and screened for co-infecting enteropathogens. Among the 45 patients with known vaccination status, 39 were vaccinated and 87% received the vaccine less than a month before the gastroenteritis episode. Reconstruction of 30 near complete vaccine-derived genomes revealed 0-11 mutations per genome, with 88% of them being non-synonymous. This, in combination with several shared amino acid changes among strains, pointed at selection of minor variant(s) present in the vaccine. We also found that some of these substitutions were true revertants (e.g., F167L on VP4, and I45T on NSP4). Finally, co-infections with known (e.g., Clostridioides difficile and norovirus) and divergent or emerging (e.g., human parechovirus A1, salivirus A2) pathogens were detected, and we estimated that 35% of the infants likely had gastroenteritis due to a 'non-rotavirus' cause. Conversely, we could not rule out the vaccine-derived gastroenteritis in over half of the cases. Continued studies inspecting reversion to pathogenicity should monitor the long-time safety of live-attenuated rotavirus vaccines. All in all, the complementary approach with NGS and qPCR provided a better understanding of rotavirus vaccine strain evolution in the Belgian population and epidemiology of co-infecting enteropathogens in suspected rotavirus vaccine-derived gastroenteritis cases.

Characterizing and explaining the impact of disease-associated mutations in proteins without known structures or structural homologs

Mutations in human proteins lead to diseases. The structure of these proteins can help understand the mechanism of such diseases and develop therapeutics against them. With improved deep learning techniques, such as RoseTTAFold and AlphaFold, we can predict the structure of proteins even in the absence of structural homologs. We modeled and extracted the domains from 553 disease-associated human proteins without known protein structures or close homologs in the Protein Databank. We noticed that the model quality was higher and the Root mean square deviation (RMSD) lower between AlphaFold and RoseTTAFold models for domains that could be assigned to CATH families as compared to those which could only be assigned to Pfam families of unknown structure or could not be assigned to either. We predicted ligand-binding sites, protein-protein interfaces and conserved residues in these predicted structures. We then explored whether the disease-associated missense mutations were in the proximity of these predicted functional sites, whether they destabilized the protein structure based on ddG calculations or whether they were predicted to be pathogenic. We could explain 80% of these disease-associated mutations based on proximity to functional sites, structural destabilization or pathogenicity. When compared to polymorphisms, a larger percentage of disease-associated missense mutations were buried, closer to predicted functional sites, predicted as destabilizing and pathogenic. Usage of models from the two state-of-the-art techniques provide better confidence in our predictions, and we explain 93 additional mutations based on RoseTTAFold models which could not be explained based solely on AlphaFold models.

CCL22 mutations drive natural killer cell lymphoproliferative disease by deregulating microenvironmental crosstalk

Chronic lymphoproliferative disorder of natural killer cells (CLPD-NK) is characterized by clonal expansion of natural killer (NK) cells where the underlying genetic mechanisms are incompletely understood. In the present study, we report somatic mutations in the chemokine gene CCL22 as the hallmark of a distinct subset of CLPD-NK. CCL22 mutations were enriched at highly conserved residues, mutually exclusive of STAT3 mutations and associated with gene expression programs that resembled normal CD16^dim/CD56^bright NK cells. Mechanistically, the mutations resulted in ligand-biased chemokine receptor signaling, with decreased internalization of the G-protein-coupled receptor (GPCR) for CCL22, CCR4, via impaired β-arrestin recruitment. This resulted in increased cell chemotaxis in vitro, bidirectional crosstalk with the hematopoietic microenvironment and enhanced NK cell proliferation in vivo in transgenic human IL-15 mice. Somatic CCL22 mutations illustrate a unique mechanism of tumor formation in which gain-of-function chemokine mutations promote tumorigenesis by biased GPCR signaling and dysregulation of microenvironmental crosstalk.

Combined Theoretical, Bioinformatic, and Biochemical Analyses of RNA Editing by Adenine Base Editors

Adenine base editors (ABEs) have been subjected to multiple rounds of mutagenesis with the goal of optimizing their function as efficient and precise genome editing agents. Despite an ever-expanding data set of ABE mutants and their corresponding DNA or RNA-editing activity, the molecular mechanisms defining these changes remain to be elucidated. In this study, we provide a systematic interpretation of the nature of these mutations using an entropy-based classification model that relies on evolutionary data from extant protein sequences. Using this model in conjunction with experimental analyses, we identify two previously reported mutations that form an epistatic pair in the RNA-editing functional landscape of ABEs. Molecular dynamics simulations reveal the atomistic details of how these two mutations affect substrate-binding and catalytic activity, via both individual and cooperative effects, hence providing insights into the mechanisms through which these two mutations are epistatically coupled.

Structural and functional analysis of the D-alanyl carrier protein ligase DltA from Staphylococcus aureus Mu50

D-Alanylation of the teichoic acids of the Gram-positive bacterial cell wall plays crucial roles in bacterial physiology and virulence. Deprivation of D-alanine from the teichoic acids of Staphylococcus aureus impairs biofilm and colony formation, induces autolysis and ultimately renders methicillin-resistant S. aureus highly susceptible to antimicrobial agents and host defense peptides. Hence, the D-alanylation pathway has emerged as a promising antibacterial target against drug-resistant S. aureus. D-Alanylation of teichoic acids is mediated via the action of four proteins encoded by the dlt operon, DltABCD, all four of which are essential for the process. In order to develop novel antimicrobial agents against S. aureus, the D-alanyl carrier protein ligase DltA, which is the first protein in the D-alanylation pathway, was focused on. Here, the crystal structure of DltA from the methicillin-resistant S. aureus strain Mu50 is presented, which reveals the unique molecular details of the catalytic center and the role of the P-loop. Kinetic analysis shows that the enantioselectivity of S. aureus DltA is much higher than that of DltA from other species. In the presence of DltC, the enzymatic activity of DltA is increased by an order of magnitude, suggesting a new exploitable binding pocket. This discovery may pave the way for a new generation of treatments for drug-resistant S. aureus.

Ankfn1-mutant vestibular defects require loss of both ancestral and derived paralogs for penetrance in zebrafish

How and to what degree gene duplication events create regulatory innovation, redundancy, or neofunctionalization remain important questions in animal evolution and comparative genetics. Ankfn1 genes are single copy in most invertebrates, partially duplicated in jawed vertebrates, and only the derived copy retained in most mammals. Null mutations in the single mouse homolog have vestibular and neurological abnormalities. Null mutation of the single Drosophila homolog is typically lethal with severe sensorimotor deficits in rare survivors. The functions and potential redundancy of paralogs in species with two copies are not known. Here, we define a vestibular role for Ankfn1 homologs in zebrafish based on the simultaneous disruption of each locus. Zebrafish with both paralogs disrupted showed vestibular defects and early lethality from swim bladder inflation failure. One intact copy at either locus was sufficient to prevent major phenotypes. Our results show that vertebrate Ankfn1 genes are required for vestibular-related functions, with at least partial redundancy between ancestral and derived paralogs.

Computational prediction of protein functional sites-Applications in biotechnology and biomedicine

There are many computational approaches for predicting protein functional sites based on different sequence and structural features. These methods are essential to cope with the sequence deluge that is filling databases with uncharacterized protein sequences. They complement the more expensive and time-consuming experimental approaches by pointing them to possible candidate positions. In many cases they are jointly used to characterize the functional sites in proteins of biotechnological and biomedical interest and eventually modify them for different purposes. There is a clear trend towards approaches based on machine learning and those using structural information, due to the recent developments in these areas. Nevertheless, "classic" methods based on sequence and evolutionary features are still playing an important role as these features are strongly related to functionality. In this review, the main approaches for predicting general functional sites in a protein are discussed, with a focus on sequence-based approaches.

In-depth analysis of amino acid and nucleotide sequences of Hsp60: how conserved is this protein?

Chaperonin Hsp60, as a protein found in all organisms, is of great interest in medicine, since it is present in many tissues and can be used both as a drug and as an object of targeted therapy. Hence, Hsp60 deserves a fundamental comparative analysis to assess its evolutionary characteristics. It was found that the percent identity of Hsp60 amino acid sequences both within and between phyla was not high enough to identify Hsp60s as highly conserved proteins. However, their ATP binding sites are largely conserved. The amino acid composition of Hsp60s remained relatively constant. At the same time, the analysis of the nucleotide sequences showed that GC content in the Hsp60 genes was comparable to or greater than the genomic values, which may indicate a high resistance to mutations due to tight control of the nucleotide composition by DNA repair systems. Natural selection plays a dominant role in the evolution of Hsp60 genes. The degree of mutational pressure affecting the Hsp60 genes is quite low, and its direction does not depend on taxonomy. Interestingly, for the Hsp60 genes from Chordata, Arthropoda, and Proteobacteria the exact direction of mutational pressure could not be determined. However, upon further division into classes, it was found that the direction of the mutational pressure for Hsp60 genes from Fish differs from that for other chordates. The direction of the mutational pressure affects the synonymous codon usage bias. The number of high and low represented codons increases with increasing GC content, which can improve codon usage. Special server has been created for bioinformatics analysis of Hsp60: http://oka.protres.ru:4202/.

Prediction of Protein Sites and Physicochemical Properties Related to Functional Specificity

Specificity Determining Positions (SDPs) are protein sites responsible for functional specificity within a family of homologous proteins. These positions are extracted from a family’s multiple sequence alignment and complement the fully conserved positions as predictors of functional sites. SDP analysis is now routinely used for locating these specificity-related sites in families of proteins of biomedical or biotechnological interest with the aim of mutating them to switch specificities or design new ones. There are many different approaches for detecting these positions in multiple sequence alignments. Nevertheless, existing methods report the potential SDP positions but they do not provide any clue on the physicochemical basis behind the functional specificity, which has to be inferred a-posteriori by manually inspecting these positions in the alignment. In this work, a new methodology is presented that, concomitantly with the detection of the SDPs, automatically provides information on the amino-acid physicochemical properties more related to the change in specificity. This new method is applied to two different multiple sequence alignments of homologous of the well-studied RasH protein representing different cases of functional specificity and the results discussed in detail.

PDBsum extras: SARS-CoV-2 and AlphaFold models

The PDBsum web server provides structural analyses of the entries in the Protein Data Bank (PDB). Two recent additions are described here. The first is the detailed analysis of the SARS-CoV-2 virus protein structures in the PDB. These include the variants of concern, which are shown both on the sequences and 3D structures of the proteins. The second addition is the inclusion of the available AlphaFold models for human proteins. The pages allow a search of the protein against existing structures in the PDB via the Sequence Annotated by Structure (SAS) server, so one can easily compare the predicted model against experimentally determined structures. The server is freely accessible to all at http://www.ebi.ac.uk/pdbsum.

A Genome-Phenome Association study in native microbiomes identifies a mechanism for cytosine modification in DNA and RNA

Shotgun metagenomic sequencing is a powerful approach to study microbiomes in an unbiased manner and of increasing relevance for identifying novel enzymatic functions. However, the potential of metagenomics to relate from microbiome composition to function has thus far been underutilized. Here, we introduce the Metagenomics Genome-Phenome Association (MetaGPA) study framework, which allows linking genetic information in metagenomes with a dedicated functional phenotype. We applied MetaGPA to identify enzymes associated with cytosine modifications in environmental samples. From the 2365 genes that met our significance criteria, we confirm known pathways for cytosine modifications and proposed novel cytosine-modifying mechanisms. Specifically, we characterized and identified a novel nucleic acid-modifying enzyme, 5-hydroxymethylcytosine carbamoyltransferase, that catalyzes the formation of a previously unknown cytosine modification, 5-carbamoyloxymethylcytosine, in DNA and RNA. Our work introduces MetaGPA as a novel and versatile tool for advancing functional metagenomics.

Many industrial processes, such as starch processing and oil refinement, use chemicals that cause harm to the environment. These can often be switched to more sustainable biological processes that are powered by proteins called enzymes.

Enzymes are micro-factories that speed up biochemical reactions in most living things. Communities of microorganisms (also known as microbiomes) are an amazing but often untapped resource for discovering enzymes that can be harnessed for industrial purposes. To gain a better picture of the microbes present within a population, researchers often extract and sequence the genetic material of all microorganisms in an environmental sample, also known as the metagenome. While current methods for analyzing the metagenome are good at identifying new species, they often provide limited information about the microorganism’s functional role within the community. This makes it difficult to find new enzymes that may be useful for industry.

Here, Yang, Lin et al. have developed a new technique called Metagenomics Genome-Phenome Association, or MetaGPA for short. The method works in a similar way to genome-wide association studies (GWAS) which are used to identify genes involved in human disease. However, instead of disease associated genes in humans, MetaGPA finds microbial genes that are associated with a biological process useful for biotechnology.

Like GWAS, the new approach created by Yang, Lin et al. compares two groups: the first contains microorganisms that carry out a specific process, and the second contains all organisms in the microbiome. The metagenome of each group is extracted and a computational pipeline is then applied to identify genes, including those coding for enzymes, that are found more often in the group performing the desired task.

To test the technique, Yang, Lin et al. used MetGPA to find new enzymes involved in DNA modification. Microbiome samples were collected from coastal water and sewage, and the computational pipeline was applied to discover genes that are associated with this process. Further analysis revealed that one of the identified genes codes for an enzyme that introduces a previously unknown change to DNA.

MetaGPA could be applied to other processes and microbiomes, and, if successful, may help researchers to identify more diverse enzymes than is currently available. This could scale up the discovery of new enzymes that can be used to power industrial reactions.

TwinCons: Conservation score for uncovering deep sequence similarity and divergence

We have developed the program TwinCons, to detect noisy signals of deep ancestry of proteins or nucleic acids. As input, the program uses a composite alignment containing pre-defined groups, and mathematically determines a 'cost' of transforming one group to the other at each position of the alignment. The output distinguishes conserved, variable and signature positions. A signature is conserved within groups but differs between groups. The method automatically detects continuous characteristic stretches (segments) within alignments. TwinCons provides a convenient representation of conserved, variable and signature positions as a single score, enabling the structural mapping and visualization of these characteristics. Structure is more conserved than sequence. TwinCons highlights alternative sequences of conserved structures. Using TwinCons, we detected highly similar segments between proteins from the translation and transcription systems. TwinCons detects conserved residues within regions of high functional importance for the ribosomal RNA (rRNA) and demonstrates that signatures are not confined to specific regions but are distributed across the rRNA structure. The ability to evaluate both nucleic acid and protein alignments allows TwinCons to be used in combined sequence and structural analysis of signatures and conservation in rRNA and in ribosomal proteins (rProteins). TwinCons detects a strong sequence conservation signal between bacterial and archaeal rProteins related by circular permutation. This conserved sequence is structurally colocalized with conserved rRNA, indicated by TwinCons scores of rRNA alignments of bacterial and archaeal groups. This combined analysis revealed deep co-evolution of rRNA and rProtein buried within the deepest branching points in the tree of life.

Species-Level Resolution of Female Bladder Microbiota from 16S rRNA Amplicon Sequencing

The human bladder contains bacteria, even in the absence of infection. Interest in studying these bacteria and their association with bladder conditions is increasing. However, the chosen experimental method can limit the resolution of the taxonomy that can be assigned to the bacteria found in the bladder. 16S rRNA amplicon sequencing is commonly used to identify bacteria in urinary specimens, but it is typically restricted to genus-level identification. Our primary aim here was to determine if accurate species-level identification of bladder bacteria is possible using 16S rRNA amplicon sequencing. We evaluated the ability of different classification schemes, each consisting of combinations of a reference database, a 16S rRNA gene variable region, and a taxonomic classification algorithm to correctly classify bladder bacteria. We show that species-level identification is possible and that the reference database chosen is the most important component, followed by the 16S variable region sequenced. IMPORTANCE Accurate species-level identification from culture-independent techniques is of importance for microbial niches that are less well characterized, such as that of the bladder. 16S rRNA amplicon sequencing, a common culture-independent way to identify bacteria, is often critiqued for lacking species-level resolution. Here, we extensively evaluate classification schemes for species-level bacterial annotation of 16S amplicon data from bladder bacteria. Our results show that the proper choice of taxonomic database and variable region of the 16S rRNA gene sequence makes species level identification possible. We also show that this improvement can be achieved through the more careful application of existing methods and resources. Species-level information may deepen our understanding of associations between bacteria in the bladder and bladder conditions such as lower urinary tract symptoms and urinary tract infections.

A Conserved Nonribosomal Peptide Synthetase in Xenorhabdus bovienii Produces Citrulline-Functionalized Lipopeptides

The entomopathogenic bacterium Xenorhabdus bovienii exists in a mutualistic relationship with nematodes of the genus Steinernema. Free-living infective juveniles of Steinernema prey on insect larvae and regurgitate X. bovienii within the hemocoel of a host larva. X. bovienii subsequently produces a complex array of specialized metabolites and effector proteins that kill the insect and regulate various aspects of the trilateral symbiosis. While Xenorhabdus species are rich producers of secondary metabolites, many of their biosynthetic gene clusters remain uncharacterized. Here, we describe a nonribosomal peptide synthetase (NRPS) identified through comparative genomics analysis that is widely conserved in Xenorhabdus species. Heterologous expression of this NRPS gene from X. bovienii in E. coli led to the discovery of a family of lipo-tripeptides that chromatographically appear as pairs, containing either a C-terminal carboxylic acid or carboxamide. Coexpression of the NRPS with the leupeptin protease inhibitor pathway enhanced production, facilitating isolation and characterization efforts. The new lipo-tripeptides were also detected in wild-type X. bovienii cultures. These metabolites, termed bovienimides, share an uncommon C-terminal d-citrulline residue. The NRPS lacked a dedicated chain termination domain, resulting in product diversification and release from the assembly line through reactions with ammonia, water, or exogenous alcohols.

Identification and Evaluation of Recombinant Outer Membrane Proteins as Vaccine Candidates Against Klebsiella pneumoniae

Klebsiella pneumoniae found in the normal flora of the human oral and intestinal tract mainly causes hospital-acquired infections but can also cause community-acquired infections. To date, most clinical trials of vaccines against K. pneumoniae have ended in failure. Furthermore, no single conserved protein has been identified as an antigen candidate to accelerate vaccine development. In this study, we identified five outer membrane proteins of K. pneumoniae, namely, Kpn_Omp001, Kpn_Omp002, Kpn_Omp003, Kpn_Omp004, and Kpn_Omp005, by using reliable second-generation proteomics and bioinformatics. Mice vaccinated with these five KOMPs elicited significantly higher antigen-specific IgG, IgG1, and IgG2a. However, only Kpn_Omp001, Kpn_Omp002, and Kpn_Omp005 were able to induce a protective immune response with two K. pneumoniae infection models. These protective effects were accompanied by the involvement of different immune responses induced by KOMPs, which included KOMPs-specific IFN-γ-, IL4-, and IL17A-mediated immune responses. These findings indicate that Kpn_Omp001, Kpn_Omp002, and Kpn_Omp005 are three potential Th1, Th2, and Th17 candidate antigens, which could be developed into multivalent and serotype-independent vaccines against K. pneumoniae infection.

Using ConSurf to Detect Functionally Important Regions in RNA

The ConSurf web server (https://consurf.tau.ac.il/) for using evolutionary data to detect functional regions is useful for analyzing proteins. The analysis is based on the premise that functional regions, which may for example facilitate ligand binding and catalysis, often evolve slowly. The analysis requires finding enough effective, i.e., non-redundant, sufficiently remote homologs. Indeed, the ConSurf pipeline, which is based on state-of-the-art protein sequence databases and analysis tools, is highly valuable for protein analysis. ConSurf also allows evolutionary analysis of RNA, but the analysis often fails due to insufficient data, particularly the inability of the current pipeline to detect enough effective RNA homologs. This is because the RNA search tools and databases offered are not as good as those used for protein analysis. Fortunately, ConSurf also allows importing external collections of homologs in the form of a multiple sequence alignment (MSA). Leveraging this, here we describe various protocols for constructing MSAs for successful ConSurf analysis of RNA queries. We report the level of success of these protocols on an exemplary set comprising a dozen RNA molecules of diverse structure and function. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Standard ConSurf evolutionary conservation analysis of an RNA query. Basic Protocol 2: ConSurf evolutionary conservation analysis of an RNA query with external MSA. Support Protocol 1: Construction of an MSA for an RNA query using other online servers. Support Protocol 2: Construction of an MSA for an RNA query using nHMMER locally.

Evolution of a cytoplasmic determinant: evidence for the biochemical basis of functional evolution of the novel germ line regulator oskar

Germ line specification is essential in sexually reproducing organisms. Despite their critical role, the evolutionary history of the genes that specify animal germ cells is heterogeneous and dynamic. In many insects, the gene oskar is required for the specification of the germ line. However, the germ line role of oskar is thought to be a derived role resulting from co-option from an ancestral somatic role. To address how evolutionary changes in protein sequence could have led to changes in the function of Oskar protein that enabled it to regulate germ line specification, we searched for oskar orthologs in 1,565 publicly available insect genomic and transcriptomic data sets. The earliest-diverging lineage in which we identified an oskar ortholog was the order Zygentoma (silverfish and firebrats), suggesting that oskar originated before the origin of winged insects. We noted some order-specific trends in oskar sequence evolution, including whole gene duplications, clade-specific losses, and rapid divergence. An alignment of all known 379 Oskar sequences revealed new highly conserved residues as candidates that promote dimerization of the LOTUS domain. Moreover, we identified regions of the OSK domain with conserved predicted RNA binding potential. Furthermore, we show that despite a low overall amino acid conservation, the LOTUS domain shows higher conservation of predicted secondary structure than the OSK domain. Finally, we suggest new key amino acids in the LOTUS domain that may be involved in the previously reported Oskar−Vasa physical interaction that is required for its germ line role.

Computational Insights into the Interaction between Cytoadherence Receptor gC1qR and the DBLβ12 Domain of a Plasmodium falciparum PfEMP1 Ligand

Human receptor gC1qR is a 32 kD protein that mediates the cytoadherence of Plasmodium falciparum-infected erythrocytes (IEs) to human brain microvascular endothelial cells (HBMEC) and platelets. The cytoadherence of IEs to gC1qR has been associated with severe malaria symptoms. The cytoadherence to gC1qR is mediated by the Duffy binding-like β12 (DBLβ12) domain of Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1), PFD0020c. Here, we report the structural insights into the binding of the DBLβ12 domain of PfEMP1 with the human receptor gC1qR using computational methods. A molecular model of the DBLβ12 domain was generated and used for protein-protein docking with the host receptor gC1qR. The protein-protein docking revealed that the DBLβ12 asymmetrically interacts with two subunits of the gC1qR trimer at the solution face of gC1qR. A total of 21 amino acid residues of DBLβ12 interact with 26 amino acid residues in the gC1qR trimer through 99 nonbonding interactions and 4 hydrogen bonds. Comparative analysis of binding sites on the DBL domain fold for the two receptors gC1qR and ICAM1 showed that the two sites are distinct. This is the first study that provides structural insights into DBLβ12 binding with its receptor gC1qR and may help in designing novel antisevere malaria interventions.

Computational approaches to predict protein functional families and functional sites

Understanding the mechanisms of protein function is indispensable for many biological applications, such as protein engineering and drug design. However, experimental annotations are sparse, and therefore, theoretical strategies are needed to fill the gap. Here, we present the latest developments in building functional subclassifications of protein superfamilies and using evolutionary conservation to detect functional determinants, for example, catalytic-, binding- and specificity-determining residues important for delineating the functional families. We also briefly review other features exploited for functional site detection and new machine learning strategies for combining multiple features.

CATH functional families predict functional sites in proteins

MOTIVATION

Identification of functional sites in proteins is essential for functional characterization, variant interpretation and drug design. Several methods are available for predicting either a generic functional site, or specific types of functional site. Here, we present FunSite, a machine learning predictor that identifies catalytic, ligand-binding and protein-protein interaction functional sites using features derived from protein sequence and structure, and evolutionary data from CATH functional families (FunFams).

RESULTS

FunSite's prediction performance was rigorously benchmarked using cross-validation and a holdout dataset. FunSite outperformed other publicly available functional site prediction methods. We show that conserved residues in FunFams are enriched in functional sites. We found FunSite's performance depends greatly on the quality of functional site annotations and the information content of FunFams in the training data. Finally, we analyze which structural and evolutionary features are most predictive for functional sites.

AVAILABILITYAND IMPLEMENTATION

https://github.com/UCL/cath-funsite-predictor.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Protein residues determining interaction specificity in paralogous families

MOTIVATION

Predicting the residues controlling a protein's interaction specificity is important not only to better understand its interactions but also to design mutations aimed at fine-tuning or swapping them as well.

RESULTS

In this work, we present a methodology that combines sequence information (in the form of multiple sequence alignments) with interactome information to detect that kind of residues in paralogous families of proteins. The interactome is used to define pairwise similarities of interaction contexts for the proteins in the alignment. The method looks for alignment positions with patterns of amino-acid changes reflecting the similarities/differences in the interaction neighborhoods of the corresponding proteins. We tested this new methodology in a large set of human paralogous families with structurally characterized interactions, and discuss in detail the results for the RasH family. We show that this approach is a better predictor of interfacial residues than both, sequence conservation and an equivalent 'unsupervised' method that does not use interactome information.

AVAILABILITY AND IMPLEMENTATION

http://csbg.cnb.csic.es/pazos/Xdet/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Neutralizing antibody vaccine for pandemic and pre-emergent coronaviruses

Betacoronaviruses caused the outbreaks of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome, as well as the current pandemic of SARS coronavirus 2 (SARS-CoV-2)^1-4. Vaccines that elicit protective immunity against SARS-CoV-2 and betacoronaviruses that circulate in animals have the potential to prevent future pandemics. Here we show that the immunization of macaques with nanoparticles conjugated with the receptor-binding domain of SARS-CoV-2, and adjuvanted with 3M-052 and alum, elicits cross-neutralizing antibody responses against bat coronaviruses, SARS-CoV and SARS-CoV-2 (including the B.1.1.7, P.1 and B.1.351 variants). Vaccination of macaques with these nanoparticles resulted in a 50% inhibitory reciprocal serum dilution (ID₅₀) neutralization titre of 47,216 (geometric mean) for SARS-CoV-2, as well as in protection against SARS-CoV-2 in the upper and lower respiratory tracts. Nucleoside-modified mRNAs that encode a stabilized transmembrane spike or monomeric receptor-binding domain also induced cross-neutralizing antibody responses against SARS-CoV and bat coronaviruses, albeit at lower titres than achieved with the nanoparticles. These results demonstrate that current mRNA-based vaccines may provide some protection from future outbreaks of zoonotic betacoronaviruses, and provide a multimeric protein platform for the further development of vaccines against multiple (or all) betacoronaviruses.

Major histocompatibility complex (MHC) class I and class II proteins: impact of polymorphism on antigen presentation

The major histocompatibility complex (MHC) loci are amongst the most polymorphic regions in the genomes of vertebrates. In the human population, thousands of MHC gene variants (alleles) exist that translate into distinct allotypes equipped with overlapping but unique peptide binding profiles. Understanding the differential structural and dynamic properties of MHC alleles and their interaction with critical regulators of peptide exchange bears the potential for more personalized strategies of immune modulation in the context of HLA-associated diseases.

A selective transmembrane recognition mechanism by a membrane-anchored ubiquitin ligase adaptor

While it is well-known that E3 ubiquitin ligases can selectively ubiquitinate membrane proteins in response to specific environmental cues, the underlying mechanisms for the selectivity are poorly understood. In particular, the role of transmembrane regions, if any, in target recognition remains an open question. Here, we describe how Ssh4, a yeast E3 ligase adaptor, recognizes the PQ-loop lysine transporter Ypq1 only after lysine starvation. We show evidence of an interaction between two transmembrane helices of Ypq1 (TM5 and TM7) and the single transmembrane helix of Ssh4. This interaction is regulated by the conserved PQ motif. Strikingly, recent structural studies of the PQ-loop family have suggested that TM5 and TM7 undergo major conformational changes during substrate transport, implying that transport-associated conformational changes may determine the selectivity. These findings thus provide critical information concerning the regulatory mechanism through which transmembrane domains can be specifically recognized in response to changing environmental conditions.

Conserved residues Glu37 and Trp229 play an essential role in protein folding of β‐lactamase

Evolutionary robustness requires that the number of highly conserved amino acid residues in proteins is minimized. In enzymes, such conservation is observed for catalytic residues but also for some residues in the second shell or even further from the active site. β‐Lactamases evolve in response to changing antibiotic selection pressures and are thus expected to be evolutionarily robust, with a limited number of highly conserved amino acid residues. As part of the effort to understand the roles of conserved residues in class A β‐lactamases, we investigate the reasons leading to the conservation of two amino acid residues in the β‐lactamase BlaC, Glu37, and Trp229. Using site‐directed mutagenesis, we have generated point mutations of these residues and observed a drastic decrease in the levels of soluble protein produced in Escherichia coli, thus abolishing completely the resistance of bacteria against β‐lactam antibiotics. However, the purified proteins are structurally and kinetically very similar to the wild‐type enzyme, only differing by exhibiting a slightly lower melting temperature. We conclude that conservation of Glu37 and Trp229 is solely caused by an essential role in the folding process, and we propose that during folding Glu37 primes the formation of the central β‐sheet and Trp229 contributes to the hydrophobic collapse into a molten globule.

Arthropod Ectoparasites Have Potential to Bind SARS-CoV-2 via ACE

Coronavirus-like organisms have been previously identified in Arthropod ectoparasites (such as ticks and unfed cat flea). Yet, the question regarding the possible role of these arthropods as SARS-CoV-2 passive/biological transmission vectors is still poorly explored. In this study, we performed in silico structural and binding energy calculations to assess the risks associated with possible ectoparasite transmission. We found sufficient similarity between ectoparasite ACE and human ACE2 protein sequences to build good quality 3D-models of the SARS-CoV-2 Spike:ACE complex to assess the impacts of ectoparasite mutations on complex stability. For several species (e.g., water flea, deer tick, body louse), our analyses showed no significant destabilisation of the SARS-CoV-2 Spike:ACE complex, suggesting these species would bind the viral Spike protein. Our structural analyses also provide structural rationale for interactions between the viral Spike and the ectoparasite ACE proteins. Although we do not have experimental evidence of infection in these ectoparasites, the predicted stability of the complex suggests this is possible, raising concerns of a possible role in passive transmission of the virus to their human hosts.

Biological impact of mutually exclusive exon switching

Alternative splicing can expand the diversity of proteomes. Homologous mutually exclusive exons (MXEs) originate from the same ancestral exon and result in polypeptides with similar structural properties but altered sequence. Why would some genes switch homologous exons and what are their biological impact? Here, we analyse the extent of sequence, structural and functional variability in MXEs and report the first large scale, structure-based analysis of the biological impact of MXE events from different genomes. MXE-specific residues tend to map to single domains, are highly enriched in surface exposed residues and cluster at or near protein functional sites. Thus, MXE events are likely to maintain the protein fold, but alter specificity and selectivity of protein function. This comprehensive resource of MXE events and their annotations is available at: http://gene3d.biochem.ucl.ac.uk/mxemod/. These findings highlight how small, but significant changes at critical positions on a protein surface are exploited in evolution to alter function.

A Proteome-Wide Immunoinformatics Tool to Accelerate T-Cell Epitope Discovery and Vaccine Design in the Context of Emerging Infectious Diseases: An Ethnicity-Oriented Approach

Emerging infectious diseases (EIDs) caused by viruses are increasing in frequency, causing a high disease burden and mortality world-wide. The COVID-19 pandemic caused by the novel SARS-like coronavirus (SARS-CoV-2) underscores the need to innovate and accelerate the development of effective vaccination strategies against EIDs. Human leukocyte antigen (HLA) molecules play a central role in the immune system by determining the peptide repertoire displayed to the T-cell compartment. Genetic polymorphisms of the HLA system thus confer a strong variability in vaccine-induced immune responses and may complicate the selection of vaccine candidates, because the distribution and frequencies of HLA alleles are highly variable among different ethnic groups. Herein, we build on the emerging paradigm of rational epitope-based vaccine design, by describing an immunoinformatics tool (Predivac-3.0) for proteome-wide T-cell epitope discovery that accounts for ethnic-level variations in immune responsiveness. Predivac-3.0 implements both CD8+ and CD4+ T-cell epitope predictions based on HLA allele frequencies retrieved from the Allele Frequency Net Database. The tool was thoroughly assessed, proving comparable performances (AUC ~0.9) against four state-of-the-art pan-specific immunoinformatics methods capable of population-level analysis (NetMHCPan-4.0, Pickpocket, PSSMHCPan and SMM), as well as a strong accuracy on proteome-wide T-cell epitope predictions for HIV-specific immune responses in the Japanese population. The utility of the method was investigated for the COVID-19 pandemic, by performing in silico T-cell epitope mapping of the SARS-CoV-2 spike glycoprotein according to the ethnic context of the countries where the ChAdOx1 vaccine is currently initiating phase III clinical trials. Potentially immunodominant CD8+ and CD4+ T-cell epitopes and population coverages were predicted for each population (the Epitope Discovery mode), along with optimized sets of broadly recognized (promiscuous) T-cell epitopes maximizing coverage in the target populations (the Epitope Optimization mode). Population-specific epitope-rich regions (T-cell epitope clusters) were further predicted in protein antigens based on combined criteria of epitope density and population coverage. Overall, we conclude that Predivac-3.0 holds potential to contribute in the understanding of ethnic-level variations of vaccine-induced immune responsiveness and to guide the development of epitope-based next-generation vaccines against emerging pathogens, whose geographic distributions and populations in need of vaccinations are often well-defined for regional epidemics.

SARS-CoV-2 vaccination induces neutralizing antibodies against pandemic and pre-emergent SARS-related coronaviruses in monkeys

Betacoronaviruses (betaCoVs) caused the severe acute respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS) outbreaks, and now the SARS-CoV-2 pandemic. Vaccines that elicit protective immune responses against SARS-CoV-2 and betaCoVs circulating in animals have the potential to prevent future betaCoV pandemics. Here, we show that immunization of macaques with a multimeric SARS-CoV-2 receptor binding domain (RBD) nanoparticle adjuvanted with 3M-052-Alum elicited cross-neutralizing antibody responses against SARS-CoV-1, SARS-CoV-2, batCoVs and the UK B.1.1.7 SARS-CoV-2 mutant virus. Nanoparticle vaccination resulted in a SARS-CoV-2 reciprocal geometric mean neutralization titer of 47,216, and robust protection against SARS-CoV-2 in macaque upper and lower respiratory tracts. Importantly, nucleoside-modified mRNA encoding a stabilized transmembrane spike or monomeric RBD protein also induced SARS-CoV-1 and batCoV cross-neutralizing antibodies, albeit at lower titers. These results demonstrate current mRNA vaccines may provide some protection from future zoonotic betaCoV outbreaks, and provide a platform for further development of pan-betaCoV nanoparticle vaccines.

Orthogonal translation enables heterologous ribosome engineering in E. coli

The ribosome represents a promising avenue for synthetic biology, but its complexity and essentiality have hindered significant engineering efforts. Heterologous ribosomes, comprising rRNAs and r-proteins derived from different microorganisms, may offer opportunities for novel translational functions. Such heterologous ribosomes have previously been evaluated in E. coli via complementation of a genomic ribosome deficiency, but this method fails to guide the engineering of refractory ribosomes. Here, we implement orthogonal ribosome binding site (RBS):antiRBS pairs, in which engineered ribosomes are directed to researcher-defined transcripts, to inform requirements for heterologous ribosome functionality. We discover that optimized rRNA processing and supplementation with cognate r-proteins enhances heterologous ribosome function for rRNAs derived from organisms with ≥76.1% 16S rRNA identity to E. coli. Additionally, some heterologous ribosomes undergo reduced subunit exchange with E. coli-derived subunits. Cumulatively, this work provides a general framework for heterologous ribosome engineering in living cells.

Genomic signatures of the evolution of defence against its natural enemies in the poisonous and medicinal plant Datura stramonium (Solanaceae)

Tropane alkaloids and terpenoids are widely used in the medicine and pharmaceutic industry and evolved as chemical defenses against herbivores and pathogens in the annual herb Datura stramonium (Solanaceae). Here, we present the first draft genomes of two plants from contrasting environments of D. stramonium. Using these de novo assemblies, along with other previously published genomes from 11 Solanaceae species, we carried out comparative genomic analyses to provide insights on the genome evolution of D. stramonium within the Solanaceae family, and to elucidate adaptive genomic signatures to biotic and abiotic stresses in this plant. We also studied, in detail, the evolution of four genes of D. stramonium-Putrescine N-methyltransferase, Tropinone reductase I, Tropinone reductase II and Hyoscyamine-6S-dioxygenase-involved in the tropane alkaloid biosynthesis. Our analyses revealed that the genomes of D. stramonium show signatures of expansion, physicochemical divergence and/or positive selection on proteins related to the production of tropane alkaloids, terpenoids, and glycoalkaloids as well as on R defensive genes and other important proteins related with biotic and abiotic pressures such as defense against natural enemies and drought.

Short linear motif candidates in the cell entry system used by SARS-CoV-2 and their potential therapeutic implications

The first reported receptor for SARS-CoV-2 on host cells was the angiotensin-converting enzyme 2 (ACE2). However, the viral spike protein also has an RGD motif, suggesting that cell surface integrins may be co-receptors. We examined the sequences of ACE2 and integrins with the Eukaryotic Linear Motif (ELM) resource and identified candidate short linear motifs (SLiMs) in their short, unstructured, cytosolic tails with potential roles in endocytosis, membrane dynamics, autophagy, cytoskeleton, and cell signaling. These SLiM candidates are highly conserved in vertebrates and may interact with the μ2 subunit of the endocytosis-associated AP2 adaptor complex, as well as with various protein domains (namely, I-BAR, LC3, PDZ, PTB, and SH2) found in human signaling and regulatory proteins. Several motifs overlap in the tail sequences, suggesting that they may act as molecular switches, such as in response to tyrosine phosphorylation status. Candidate LC3-interacting region (LIR) motifs are present in the tails of integrin β3 and ACE2, suggesting that these proteins could directly recruit autophagy components. Our findings identify several molecular links and testable hypotheses that could uncover mechanisms of SARS-CoV-2 attachment, entry, and replication against which it may be possible to develop host-directed therapies that dampen viral infection and disease progression. Several of these SLiMs have now been validated to mediate the predicted peptide interactions.

Decoding Protein-protein Interactions: An Overview

Drug discovery has focused on the paradigm "one drug, one target" for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

CATH: increased structural coverage of functional space

CATH (https://www.cathdb.info) identifies domains in protein structures from wwPDB and classifies these into evolutionary superfamilies, thereby providing structural and functional annotations. There are two levels: CATH-B, a daily snapshot of the latest domain structures and superfamily assignments, and CATH+, with additional derived data, such as predicted sequence domains, and functionally coherent sequence subsets (Functional Families or FunFams). The latest CATH+ release, version 4.3, significantly increases coverage of structural and sequence data, with an addition of 65,351 fully-classified domains structures (+15%), providing 500 238 structural domains, and 151 million predicted sequence domains (+59%) assigned to 5481 superfamilies. The FunFam generation pipeline has been re-engineered to cope with the increased influx of data. Three times more sequences are captured in FunFams, with a concomitant increase in functional purity, information content and structural coverage. FunFam expansion increases the structural annotations provided for experimental GO terms (+59%). We also present CATH-FunVar web-pages displaying variations in protein sequences and their proximity to known or predicted functional sites. We present two case studies (1) putative cancer drivers and (2) SARS-CoV-2 proteins. Finally, we have improved links to and from CATH including SCOP, InterPro, Aquaria and 2DProt.

Conformation of the Intermediates in the Reaction Catalyzed by Protoporphyrinogen Oxidase: An In Silico Analysis

Protoporphyrinogen oxidase (PPO) is a critical enzyme across life as the last common step in the synthesis of many metalloporphyrins. The reaction mechanism of PPO was assessed in silico and the unstructured loop near the binding pocket was investigated. The substrate, intermediates, and product were docked in the catalytic domain of PPO using a modified Autodock method, introducing flexibility in the macrocycles. Sixteen PPO protein sequences across phyla were aligned and analyzed with Phyre2 and ProteinPredict to study the unstructured loop from residue 204–210 in the H. sapiens structure. Docking of the substrate, intermediates, and product all resulted in negative binding energies, though the substrate had a lower energy than the others by 40%. The α-H of C10 was found to be 1.4 angstroms closer to FAD than the β-H, explaining previous reports of the reaction occurring on the meso face of the substrate. A lack of homology in sequence or length in the unstructured loop indicates a lack of function for the protein reaction. This docking study supports a reaction mechanism proposed previously whereby all hydride abstractions occur on the C10 of the tetrapyrrole followed by tautomeric rearrangement to prepare the intermediate for the next reaction.

A tunable LIC1-adaptor interaction modulates dynein activity in a cargo-specific manner

Cytoplasmic dynein-1 (dynein) is the motor responsible for most retrograde transport of cargoes along microtubules in eukaryotic cells, including organelles, mRNA and viruses. Cargo selectivity and activation of processive motility depend on a group of so-called "activating adaptors" that link dynein to its general cofactor, dynactin, and cargoes. The mechanism by which these adaptors regulate dynein transport is poorly understood. Here, based on crystal structures, quantitative binding studies, and in vitro motility assays, we show that BICD2, CRACR2a, and HOOK3, representing three subfamilies of unrelated adaptors, interact with the same amphipathic helix of the dynein light intermediate chain-1 (LIC1). While the hydrophobic character of the interaction is conserved, the three adaptor subfamilies use different folds (coiled-coil, EF-hand, HOOK domain) and different surface contacts to bind the LIC1 helix with affinities ranging from 1.5 to 15.0 μM. We propose that a tunable LIC1-adaptor interaction modulates dynein's motility in a cargo-specific manner.

ERH facilitates microRNA maturation through the interaction with the N-terminus of DGCR8

The microprocessor complex cleaves the primary transcript of microRNA (pri-miRNA) to initiate miRNA maturation. Microprocessor is known to consist of RNase III DROSHA and dsRNA-binding DGCR8. Here, we identify Enhancer of Rudimentary Homolog (ERH) as a new component of Microprocessor. Through a crystal structure and biochemical experiments, we reveal that ERH uses its hydrophobic groove to bind to a conserved region in the N-terminus of DGCR8, in a 2:2 stoichiometry. Knock-down of ERH or deletion of the DGCR8 N-terminus results in a reduced processing of suboptimal pri-miRNAs in polycistronic miRNA clusters. ERH increases the processing of suboptimal pri-miR-451 in a manner dependent on its neighboring pri-miR-144. Thus, the ERH dimer may mediate 'cluster assistance' in which Microprocessor is loaded onto a poor substrate with help from a high-affinity substrate in the same cluster. Our study reveals a role of ERH in the miRNA biogenesis pathway.

Graph-theoretical formulation of the generalized epitope-based vaccine design problem

Epitope-based vaccines have revolutionized vaccine research in the last decades. Due to their complex nature, bioinformatics plays a pivotal role in their development. However, existing algorithms address only specific parts of the design process or are unable to provide formal guarantees on the quality of the solution. We present a unifying formalism of the general epitope vaccine design problem that tackles all phases of the design process simultaneously and combines all prevalent design principles. We then demonstrate how to formulate the developed formalism as an integer linear program, which guarantees optimality of the designs. This makes it possible to explore new regions of the vaccine design space, analyze the trade-offs between the design phases, and balance the many requirements of vaccines.

LIST-S2: taxonomy based sorting of deleterious missense mutations across species

The separation of deleterious from benign mutations remains a key challenge in the interpretation of genomic data. Computational methods used to sort mutations based on their potential deleteriousness rely largely on conservation measures derived from sequence alignments. Here, we introduce LIST-S2, a successor to our previously developed approach LIST, which aims to exploit local sequence identity and taxonomy distances in quantifying the conservation of human protein sequences. Unlike its predecessor, LIST-S2 is not limited to human sequences but can assess conservation and make predictions for sequences from any organism. Moreover, we provide a web-tool and downloadable software to compute and visualize the deleteriousness of mutations in user-provided sequences. This web-tool contains an HTML interface and a RESTful API to submit and manage sequences as well as a browsable set of precomputed predictions for a large number of UniProtKB protein sequences of common taxa. LIST-S2 is available at: https://list-s2.msl.ubc.ca/.

ProAffiMuSeq: sequence-based method to predict the binding free energy change of protein-protein complexes upon mutation using functional classification

MOTIVATION

Protein-protein interactions are essential for the cell and mediate various functions. However, mutations can disrupt these interactions and may cause diseases. Currently available computational methods require a complex structure as input for predicting the change in binding affinity. Further, they have not included the functional class information for the protein-protein complex. To address this, we have developed a method, ProAffiMuSeq, which predicts the change in binding free energy using sequence-based features and functional class.

RESULTS

Our method shows an average correlation between predicted and experimentally determined ΔΔG of 0.73 and mean absolute error (MAE) of 0.86 kcal/mol in 10-fold cross-validation and correlation of 0.75 with MAE of 0.94 kcal/mol in the test dataset. ProAffiMuSeq was also tested on an external validation set and showed results comparable to structure-based methods. Our method can be used for large-scale analysis of disease-causing mutations in protein-protein complexes without structural information.

AVAILABILITY AND IMPLEMENTATION

Users can access the method at https://web.iitm.ac.in/bioinfo2/proaffimuseq/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MPTherm-pred: Analysis and Prediction of Thermal Stability Changes upon Mutations in Transmembrane Proteins

The stability of membrane proteins differs from globular proteins due to the presence of nonpolar membrane-spanning regions. Using a dataset of 929 membrane protein mutations whose effects on thermal stability (ΔT_m) were experimentally determined, we found that the average ΔT_m due to 190 stabilizing and 232 destabilizing mutations occurring in membrane-spanning regions are 2.43(3.1) °C and -5.48(5.5) °C, respectively. The ΔT_m values for mutations occurring in solvent-exposed regions are 2.56(2.82) and - 6.8(7.2) °C. We have systematically analyzed the factors influencing the stability of mutants and observed that changes in hydrophobicity, number of contacts between Cα atoms and frequency of aliphatic residues are important determinants of the stability change induced by mutations occurring in membrane-spanning regions. We have developed structure- and sequence-based machine learning predictors of ΔT_m due to mutations specifically for membrane proteins. They showed a correlation and mean absolute error (MAE) of 0.72 and 2.85 °C, respectively, between experimental and predicted ΔT_m for mutations in membrane-spanning regions on 10-fold group-wise cross-validation. The average correlation and MAE for mutations in aqueous regions are 0.73 and 3.7 °C, respectively. These MAE values are about 50% lower than standard deviations from the mean ΔT_m values. The reliability of the method was affirmed on a test set of mutations occurring in evolutionary independent protein sequences. The developed MPTherm-pred server for predicting thermal stability changes upon mutations in membrane proteins is available at https://web.iitm.ac.in/bioinfo2/mpthermpred/. Our results provide insights into factors influencing the stability of membrane proteins and can aid in designing mutants that are more resistant to thermal stress.

Unlocking COVID therapeutic targets: A structure-based rationale against SARS-CoV-2, SARS-CoV and MERS-CoV Spike

There are no approved target therapeutics against SARS-CoV-2 or other beta-CoVs. The beta-CoV Spike protein is a promising target considering the critical role in viral infection and pathogenesis and its surface exposed features. We performed a structure-based strategy targeting highly conserved druggable regions resulting from a comprehensive large-scale sequence analysis and structural characterization of Spike domains across SARSr- and MERSr-CoVs. We have disclosed 28 main consensus druggable pockets within the Spike. The RBD and SD1 (S1 subunit); and the CR, HR1 and CH (S2 subunit) represent the most promising conserved druggable regions. Additionally, we have identified 181 new potential hot spot residues for the hSARSr-CoVs and 72 new hot spot residues for the SARSr- and MERSr-CoVs, which have not been described before in the literature. These sites/residues exhibit advantageous structural features for targeted molecular and pharmacological modulation. This study establishes the Spike as a promising anti-CoV target using an approach with a potential higher resilience to resistance development and directed to a broad spectrum of Beta-CoVs, including the new SARS-CoV-2 responsible for COVID-19. This research also provides a structure-based rationale for the design and discovery of chemical inhibitors, antibodies or other therapeutic modalities successfully targeting the Beta-CoV Spike protein.

Mutations in transmembrane proteins: diseases, evolutionary insights, prediction and comparison with globular proteins

Membrane proteins are unique in that they interact with lipid bilayers, making them indispensable for transporting molecules and relaying signals between and across cells. Due to the significance of the protein's functions, mutations often have profound effects on the fitness of the host. This is apparent both from experimental studies, which implicated numerous missense variants in diseases, as well as from evolutionary signals that allow elucidating the physicochemical constraints that intermembrane and aqueous environments bring. In this review, we report on the current state of knowledge acquired on missense variants (referred to as to single amino acid variants) affecting membrane proteins as well as the insights that can be extrapolated from data already available. This includes an overview of the annotations for membrane protein variants that have been collated within databases dedicated to the topic, bioinformatics approaches that leverage evolutionary information in order to shed light on previously uncharacterized membrane protein structures or interaction interfaces, tools for predicting the effects of mutations tailored specifically towards the characteristics of membrane proteins as well as two clinically relevant case studies explaining the implications of mutated membrane proteins in cancer and cardiomyopathy.

VarMap: a web tool for mapping genomic coordinates to protein sequence and structure and retrieving protein structural annotations

Motivation

Understanding the protein structural context and patterning on proteins of genomic variants can help to separate benign from pathogenic variants and reveal molecular consequences. However, mapping genomic coordinates to protein structures is non-trivial, complicated by alternative splicing and transcript evidence.

Results

Here we present VarMap, a web tool for mapping a list of chromosome coordinates to canonical UniProt sequences and associated protein 3D structures, including validation checks, and annotating them with structural information.

Availability and implementation

https://www.ebi.ac.uk/thornton-srv/databases/VarMap.

Supplementary information

Supplementary data are available at Bioinformatics online.