VarSite: disease variants and protein structure

VarSite is a web server mapping known disease-associated variants from UniProt and ClinVar, together with natural variants from gnomAD, onto protein 3D structures in the Protein Data Bank (PDB). The analyses are primarily image-based and provide both an overview for each human protein, as well as a report for any specific variant of interest. The information can be useful in assessing whether a given variant might be pathogenic or benign. The structural annotations for each position in the protein include protein secondary structure, interactions with ligand, metal, DNA/RNA, or other protein, and various measures of a given variant's possible impact on the protein's function. The 3D locations of the disease-associated variants can be viewed interactively via the 3dmol.js JavaScript viewer, as well as in RasMol and PyMOL. Users can search for specific variants, or sets of variants, by providing the DNA coordinates of the base change(s) of interest. Additionally, various agglomerative analyses are given, such as the mapping of disease and natural variants onto specific Pfam or CATH domains. The server is freely accessible to all at: https://www.ebi.ac.uk/thornton-srv/databases/VarSite. This article is protected by copyright. All rights reserved

1,000 structures and more from the MCSG

Background: The Midwest Center for Structural Genomics (MCSG) is one of the large-scale centres of the Protein Structure Initiative (PSI). During the first two phases of the PSI the MCSG has solved over a thousand protein structures. A criticism of structural genomics is that target selection strategies mean that some structures are solved without having a known function and thus are of little biomedical significance. Structures of unknown function have stimulated the development of methods for function prediction from structure.Results: We show that the MCSG has met the stated goals of the PSI and use online resources and readily available function prediction methods to provide functional annotations for more than 90% of the MCSG structures. The structure-to-function prediction method ProFunc provides likely functions for many of the MCSG structures that cannot be annotated by sequence-based methods.Conclusions: Although the focus of the PSI was structural coverage, many of the structures solved by the MCSG can also be associated with functional classes and biological roles of possible biomedical value

Molecular Modeling of the Interaction Between Stem Cell Peptide and Immune Receptor in Plants

© Springer Science+Business Media, LLC, part of Springer Nature 2020. Molecular docking enables comprehensive exploration of interactions between chemical moieties and proteins. Modeling and docking approaches are useful to determine the three-dimensional (3D) structure of experimentally uncrystallized proteins and subsequently their interactions with various inhibitors and activators or peptides. Here, we describe a protocol for carrying out molecular modeling and docking of stem cell peptide CLV3p on plant innate immune receptor FLS2

SSMap: A new UniProt-PDB mapping resource for the curation of structural-related information in the UniProt/Swiss-Prot Knowledgebase

<p>Abstract</p> <p>Background</p> <p>Sequences and structures provide valuable complementary information on protein features and functions. However, it is not always straightforward for users to gather information concurrently from the sequence and structure levels. The UniProt knowledgebase (UniProtKB) strives to help users on this undertaking by providing complete cross-references to Protein Data Bank (PDB) as well as coherent feature annotation using available structural information. In this study, SSMap – a new UniProt-PDB residue-residue level mapping – was generated. The primary objective of this mapping is not only to facilitate the two tasks mentioned above, but also to palliate a number of shortcomings of existent mappings. SSMap is the first isoform sequence-specific mapping resource and is up-to-date for UniProtKB annotation tasks. The method employed by SSMap differs from the other mapping resources in that it stresses on the correct reconstruction of the PDB sequence from structures, and on the correct attribution of a UniProtKB entry to each PDB chain by using a series of post-processing steps.</p> <p>Results</p> <p>SSMap was compared to other existing mapping resources in terms of the correctness of the attribution of PDB chains to UniProtKB entries, and of the quality of the pairwise alignments supporting the residue-residue mapping. It was found that SSMap shared about 80% of the mappings with other mapping sources. New and alternative mappings proposed by SSMap were mostly good as assessed by manual verification of data subsets. As for local pairwise alignments, it was shown that major discrepancies (both in terms of alignment lengths and boundaries), when present, were often due to differences in methodologies used for the mappings.</p> <p>Conclusion</p> <p>SSMap provides an independent, good quality UniProt-PDB mapping. The systematic comparison conducted in this study allows the further identification of general problems in UniProt-PDB mappings so that both the coverage and the quality of the mappings can be systematically improved for the benefit of the scientific community. SSMap mapping is currently used to provide PDB cross-references in UniProtKB.</p

PocketMatch: A new algorithm to compare binding sites in protein structures

Background: Recognizing similarities and deriving relationships among protein molecules is a fundamental&#xd;&#xa;requirement in present-day biology. Similarities can be present at various levels which can be detected through comparison of protein sequences or their structural folds. In some cases similarities obscure at these levels could be present merely in the substructures at their binding sites. Inferring functional similarities between protein molecules by comparing their binding sites is still largely exploratory and not as yet a routine protocol. One of&#xd;&#xa;the main reasons for this is the limitation in the choice of appropriate analytical tools that can compare binding sites with high sensitivity. To benefit from the enormous amount of structural data that is being rapidly accumulated, it is essential to have high throughput tools that enable large scale binding site comparison.&#xd;&#xa;&#xd;&#xa;Results: Here we present a new algorithm PocketMatch for comparison of binding sites in a frame invariant&#xd;&#xa;manner. Each binding site is represented by 90 lists of sorted distances capturing shape and chemical nature of the site. The sorted arrays are then aligned using an incremental alignment method and scored to obtain PMScores for pairs of sites. A comprehensive sensitivity analysis and an extensive validation of the algorithm have been carried out. Perturbation studies where the geometry of a given site was retained but the residue types were changed randomly, indicated that chance similarities were virtually non-existent. Our analysis also demonstrates that shape information alone is insufficient to discriminate between diverse binding sites, unless&#xd;&#xa;combined with chemical nature of amino acids.&#xd;&#xa;&#xd;&#xa;Conclusions: A new algorithm has been developed to compare binding sites in accurate, efficient and&#xd;&#xa;high-throughput manner. Though the representation used is conceptually simplistic, we demonstrate that along&#xd;&#xa;with the new alignment strategy used, it is sufficient to enable binding comparison with high sensitivity. Novel methodology has also been presented for validating the algorithm for accuracy and sensitivity with respect to geometry and chemical nature of the site. The method is also fast and takes about 1/250th second for one comparison on a single processor. A parallel version on BlueGene has also been implemented

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues

In silico assessment of potential druggable pockets on the surface of α1-Antitrypsin conformers

The search for druggable pockets on the surface of a protein is often performed on a single conformer, treated as a rigid body. Transient druggable pockets may be missed in this approach. Here, we describe a methodology for systematic in silico analysis of surface clefts across multiple conformers of the metastable protein α1-antitrypsin (A1AT). Pathological mutations disturb the conformational landscape of A1AT, triggering polymerisation that leads to emphysema and hepatic cirrhosis. Computational screens for small molecule inhibitors of polymerisation have generally focused on one major druggable site visible in all crystal structures of native A1AT. In an alternative approach, we scan all surface clefts observed in crystal structures of A1AT and in 100 computationally produced conformers, mimicking the native solution ensemble. We assess the persistence, variability and druggability of these pockets. Finally, we employ molecular docking using publicly available libraries of small molecules to explore scaffold preferences for each site. Our approach identifies a number of novel target sites for drug design. In particular one transient site shows favourable characteristics for druggability due to high enclosure and hydrophobicity. Hits against this and other druggable sites achieve docking scores corresponding to a Kd in the µM–nM range, comparing favourably with a recently identified promising lead. Preliminary ThermoFluor studies support the docking predictions. In conclusion, our strategy shows considerable promise compared with the conventional single pocket/single conformer approach to in silico screening. Our best-scoring ligands warrant further experimental investigation

Motivated proteins: a web application for studying small three-dimensional protein motifs

&lt;b&gt;BACKGROUND:&lt;/b&gt; Small loop-shaped motifs are common constituents of the three-dimensional structure of proteins. Typically they comprise between three and seven amino acid residues, and are defined by a combination of dihedral angles and hydrogen bonding partners. The most abundant of these are alphabeta-motifs, asx-motifs, asx-turns, beta-bulges, beta-bulge loops, beta-turns, nests, niches, Schellmann loops, ST-motifs, ST-staples and ST-turns.We have constructed a database of such motifs from a range of high-quality protein structures and built a web application as a visual interface to this. &lt;b&gt;DESCRIPTION:&lt;/b&gt; The web application, Motivated Proteins, provides access to these 12 motifs (with 48 sub-categories) in a database of over 400 representative proteins. Queries can be made for specific categories or sub-categories of motif, motifs in the vicinity of ligands, motifs which include part of an enzyme active site, overlapping motifs, or motifs which include a particular amino acid sequence. Individual proteins can be specified, or, where appropriate, motifs for all proteins listed. The results of queries are presented in textual form as an (X)HTML table, and may be saved as parsable plain text or XML. Motifs can be viewed and manipulated either individually or in the context of the protein in the Jmol applet structural viewer. Cartoons of the motifs imposed on a linear representation of protein secondary structure are also provided. Summary information for the motifs is available, as are histograms of amino acid distribution, and graphs of dihedral angles at individual positions in the motifs. &lt;b&gt;CONCLUSION:&lt;/b&gt; Motivated Proteins is a publicly and freely accessible web application that enables protein scientists to study small three-dimensional motifs without requiring knowledge of either Structured Query Language or the underlying database schem

The structure of a resuscitation-promoting factor domain from Mycobacterium tuberculosis shows homology to lysozymes

Resuscitation-promoting factor (RPF) proteins reactivate stationary-phase cultures of (G+C)-rich Gram-positive bacteria including the causative agent of tuberculosis, Mycobacterium tuberculosis. We report the solution structure of the RPF domain from M. tuberculosis Rv1009 (RpfB) solved by heteronuclear multidimensional NMR. Structural homology with various glycoside hydrolases suggested that RpfB cleaved oligosaccharides. Biochemical studies indicate that a conserved active site glutamate is important for resuscitation activity. These data, as well as the presence of a clear binding pocket for a large molecule, indicate that oligosaccharide cleavage is probably the signal for revival from dormancy

Structural and functional characterization of Pseudomonas aeruginosa CupB chaperones

Pseudomonas aeruginosa, an important human pathogen, is estimated to be responsible for,10% of nosocomial infections worldwide. The pathogenesis of P. aeruginosa starts from its colonization in the damaged tissue or medical devices (e. g. catheters, prothesis and implanted heart valve etc.) facilitated by several extracellular adhesive factors including fimbrial pili. Several clusters containing fimbrial genes have been previously identified on the P. aeruginosa chromosome and named cup [1]. The assembly of the CupB pili is thought to be coordinated by two chaperones, CupB2 and CupB4. However, due to the lack of structural and biochemical data, their chaperone activities remain speculative. In this study, we report the 2.5 A crystal structure of P. aeruginosa CupB2. Based on the structure, we further tested the binding specificity of CupB2 and CupB4 towards CupB1 (the presumed major pilus subunit) and CupB6 (the putative adhesin) using limited trypsin digestion and strep-tactin pull-down assay. The structural and biochemical data suggest that CupB2 and CupB4 might play different, but not redundant, roles in CupB secretion. CupB2 is likely to be the chaperone of CupB1, and CupB4 could be the chaperone of CupB4:CupB5:CupB6, in which the interaction of CupB4 and CupB6 might be mediated via CupB5