COMPASS server for remote homology inference

COMPASS is a method for homology detection and local alignment construction based on the comparison of multiple sequence alignments (MSAs). The method derives numerical profiles from given MSAs, constructs local profile-profile alignments and analytically estimates E-values for the detected similarities. Until now, COMPASS was only available for download and local installation. Here, we present a new web server featuring the latest version of COMPASS, which provides (i) increased sensitivity and selectivity of homology detection; (ii) longer, more complete alignments; and (iii) faster computational speed. After submission of the query MSA or single sequence, the server performs searches versus a user-specified database. The server includes detailed and intuitive control of the search parameters. A flexible output format, structured similarly to BLAST and PSI-BLAST, provides an easy way to read and analyze the detected profile similarities. Brief help sections are available for all input parameters and output options, along with detailed documentation. To illustrate the value of this tool for protein structure-functional prediction, we present two examples of detecting distant homologs for uncharacterized protein families. Available at http://prodata.swmed.edu/compas

iMOTdb—a comprehensive collection of spatially interacting motifs in proteins

Realization of conserved residues that represent a protein family is crucial for clearer understanding of biological function as well as for the better recognition of additional members in sequence databases. Functionally important residues are recognized well due to their high degree of conservation in closely related sequences and are annotated in functional motif databases. Structural motifs are central to the integrity of the fold and require careful analysis for their identification. We report the availability of a database of spatially interacting motifs in single protein structures as well as those among distantly related protein structures that belong to a superfamily. Spatial interactions amongst conserved motifs are automatically measured using sequence similarity scores and distance calculations. Interactions between pairs of conserved motifs are described in the form of pseudoenergies. iMOTdb database provides information for 854 488 motifs corresponding to 60 849 protein structural domains and 22 648 protein structural entries

Integron Gene Cassettes: A Repository of Novel Protein Folds with Distinct Interaction Sites

Mobile gene cassettes captured within integron arrays encompass a vast and diverse pool of genetic novelty. In most cases, functional annotation of gene cassettes directly recovered by cassette-PCR is obscured by their characteristically high sequence novelty. This inhibits identification of those specific functions or biological features that might constitute preferential factors for lateral gene transfer via the integron system. A structural genomics approach incorporating x-ray crystallography has been utilised on a selection of cassettes to investigate evolutionary relationships hidden at the sequence level. Gene cassettes were accessed from marine sediments (pristine and contaminated sites), as well as a range of Vibrio spp. We present six crystal structures, a remarkably high proportion of our survey of soluble proteins, which were found to possess novel folds. These entirely new structures are diverse, encompassing all-α, α+β and α/β fold classes, and many contain clear binding pocket features for small molecule substrates. The new structures emphasise the large repertoire of protein families encoded within the integron cassette metagenome and which remain to be characterised. Oligomeric association is a notable recurring property common to these new integron-derived proteins. In some cases, the protein-protein contact sites utilised in homomeric assembly could instead form suitable contact points for heterogeneous regulator/activator proteins or domains. Such functional features are ideal for a flexible molecular componentry needed to ensure responsive and adaptive bacterial functions.13 page(s

PASS2: an automated database of protein alignments organised as structural superfamilies

BACKGROUND: The functional selection and three-dimensional structural constraints of proteins in nature often relates to the retention of significant sequence similarity between proteins of similar fold and function despite poor sequence identity. Organization of structure-based sequence alignments for distantly related proteins, provides a map of the conserved and critical regions of the protein universe that is useful for the analysis of folding principles, for the evolutionary unification of protein families and for maximizing the information return from experimental structure determination. The Protein Alignment organised as Structural Superfamily (PASS2) database represents continuously updated, structural alignments for evolutionary related, sequentially distant proteins. DESCRIPTION: An automated and updated version of PASS2 is, in direct correspondence with SCOP 1.63, consisting of sequences having identity below 40% among themselves. Protein domains have been grouped into 628 multi-member superfamilies and 566 single member superfamilies. Structure-based sequence alignments for the superfamilies have been obtained using COMPARER, while initial equivalencies have been derived from a preliminary superposition using LSQMAN or STAMP 4.0. The final sequence alignments have been annotated for structural features using JOY4.0. The database is supplemented with sequence relatives belonging to different genomes, conserved spatially interacting and structural motifs, probabilistic hidden markov models of superfamilies based on the alignments and useful links to other databases. Probabilistic models and sensitive position specific profiles obtained from reliable superfamily alignments aid annotation of remote homologues and are useful tools in structural and functional genomics. PASS2 presents the phylogeny of its members both based on sequence and structural dissimilarities. Clustering of members allows us to understand diversification of the family members. The search engine has been improved for simpler browsing of the database. CONCLUSIONS: The database resolves alignments among the structural domains consisting of evolutionarily diverged set of sequences. Availability of reliable sequence alignments of distantly related proteins despite poor sequence identity and single-member superfamilies permit better sampling of structures in libraries for fold recognition of new sequences and for the understanding of protein structure-function relationships of individual superfamilies. PASS2 is accessible a

Computational Approaches to Drug Profiling and Drug-Protein Interactions

Despite substantial increases in R&D spending within the pharmaceutical industry, denovo drug design has become a time-consuming endeavour. High attrition rates led to a long period of stagnation in drug approvals. Due to the extreme costs associated with introducing a drug to the market, locating and understanding the reasons for clinical failure is key to future productivity. As part of this PhD, three main contributions were made in this respect. First, the web platform, LigNFam enables users to interactively explore similarity relationships between ‘drug like’ molecules and the proteins they bind. Secondly, two deep-learning-based binding site comparison tools were developed, competing with the state-of-the-art over benchmark datasets. The models have the ability to predict offtarget interactions and potential candidates for target-based drug repurposing. Finally, the open-source ScaffoldGraph software was presented for the analysis of hierarchical scaffold relationships and has already been used in multiple projects, including integration into a virtual screening pipeline to increase the tractability of ultra-large screening experiments. Together, and with existing tools, the contributions made will aid in the understanding of drug-protein relationships, particularly in the fields of off-target prediction and drug repurposing, helping to design better drugs faster

Analysis by RNA-seq of transcriptomic changes elicited by heat shock in Leishmania major

Besides their medical relevance, Leishmania is an adequate model for studying post-transcriptional mechanisms of gene expression. In this microorganism, mRNA degradation/stabilization mechanisms together with translational control and post-translational modifications of proteins are the major drivers of gene expression. Leishmania parasites develop as promastigotes in sandflies and as amastigotes in mammalians, and during host transmission, the parasite experiences a sudden temperature increase. Here, changes in the transcriptome of Leishmania major promastigotes after a moderate heat shock were analysed by RNA-seq. Several of the up-regulated transcripts code for heat shock proteins, other for proteins previously reported to be amastigote-specific and many for hypothetical proteins. Many of the transcripts experiencing a decrease in their steady-state levels code for transporters, proteins involved in RNA metabolism or translational factors. In addition, putative long noncoding RNAs were identified among the differentially expressed transcripts. Finally, temperature-dependent changes in the selection of the spliced leader addition sites were inferred from the RNA-seq data, and particular cases were further validated by RT-PCR and Northern blotting. This study provides new insights into the post-transcriptional mechanisms by which Leishmania modulate gene expressionThis work was supported by grants (to B.A. and J.M.R.) from Ministerio de Economía, Industria y Competitividad, project number SAF2017-86965-R (co-funded with FEDER funds), and by the Network of Tropical Diseases Research RICET (RD16/0027/0008), co-funded with FEDER funds. The CBMSO receives institutional grants from the Fundación Ramón Areces and from the Fundación Banco de Santande

Visible Volume: a Robust Measure for Protein Structure Characterization

We propose a new characterization of protein structure based on the natural tetrahedral geometry of the β carbon and a new geometric measure of structural similarity, called visible volume. In our model, the side-chains are replaced by an ideal tetrahedron, the orientation of which is fixed with respect to the backbone and corresponds to the preferred rotamer directions. Visible volume is a measure of the non-occluded empty space surrounding each residue position after the side-chains have been removed. It is a robust, parameter-free, locally-computed quantity that accounts for many of the spatial constraints that are of relevance to the corresponding position in the native structure. When computing visible volume, we ignore the nature of both the residue observed at each site and the ones surrounding it. We focus instead on the space that, together, these residues could occupy. By doing so, we are able to quantify a new kind of invariance beyond the apparent variations in protein families, namely, the conservation of the physical space available at structurally equivalent positions for side-chain packing. Corresponding positions in native structures are likely to be of interest in protein structure prediction, protein design, and homology modeling. Visible volume is related to the degree of exposure of a residue position and to the actual rotamers in native proteins. In this article, we discuss the properties of this new measure, namely, its robustness with respect to both crystallographic uncertainties and naturally occurring variations in atomic coordinates, and the remarkable fact that it is essentially independent of the choice of the parameters used in calculating it. We also show how visible volume can be used to align protein structures, to identify structurally equivalent positions that are conserved in a family of proteins, and to single out positions in a protein that are likely to be of biological interest. These properties qualify visible volume as a powerful tool in a variety of applications, from the detailed analysis of protein structure to homology modeling, protein structural alignment, and the definition of better scoring functions for threading purposes.National Library of Medicine (LM05205-13