Mindaugas Margelevičius

Comparative modeling in CASP6 using consensus approach to template selection, sequence‐structure alignment, and structure assessment

Along with over 150 other groups we have tested our template‐based protein structure prediction approach by submitting models for 30 target proteins to the sixth round of the Critical Assessment of Protein Structure Prediction Methods (CASP6, http://predictioncenter.org). Most of our modeled proteins fall into the comparative or homology modeling (CM) category, and some are fold recognition (FR) targets. The key feature of our structure prediction strategy in CASP6 was an attempt to optimally select structural templates and to make accurate sequence–structure alignments. Template selection was based mainly on consensus results of multiple sequence searches. Likewise, the consensus of multiple alignment variants (or lack of it) was used to initially delineate reliable and unreliable alignment regions. Structure evaluation approaches were then used to identify the correct sequence–structure mapping. Our results suggest that in many cases use of multiple templates is advantageous. Selecting correct alignments even within the context of a three‐dimensional structure remains a challenge. Together with more effective energy evaluation methods the simultaneous relaxation/refinement of a “frozen” backbone inherited from the template is likely needed to see a clear progress in tackling this problem. Our analysis also suggests that human input has little to contribute to automatic methods in modeling high homology targets. On the other hand, human expertise can be very valuable in modeling distantly related proteins and critical in cases of unexpected evolutionary changes in protein structure. Proteins 2005;Suppl 7:99–105.

Detection of distant evolutionary relationships between protein families using theory of sequence profile-profile comparison

BackgroundDetection of common evolutionary origin (homology) is a primary means of inferring protein structure and function. At present, comparison of protein families represented as sequence profiles is arguably the most effective homology detection strategy. However, finding the best way to represent evolutionary information of a protein sequence family in the profile, to compare profiles and to estimate the biological significance of such comparisons, remains an active area of research.ResultsHere, we present a new homology detection method based on sequence profile-profile comparison. The method has a number of new features including position-dependent gap penalties and a global score system. Position-dependent gap penalties provide a more biologically relevant way to represent and align protein families as sequence profiles. The global score system enables an analytical solution of the statistical parameters needed to estimate the statistical significance of profile-profile similarities. The new method, together with other state-of-the-art profile-based methods (HHsearch, COMPASS and PSI-BLAST), is benchmarked in all-against-all comparison of a challenging set of SCOP domains that share at most 20% sequence identity. For benchmarking, we use a reference (gold standard) free model-based evaluation framework. Evaluation results show that at the level of protein domains our method compares favorably to all other tested methods. We also provide examples of the new method outperforming structure-based similarity detection and alignment. The implementation of the new method both as a standalone software package and as a web server is available at http://www.ibt.lt/bioinformatics/coma.ConclusionDue to a number of developments, the new profile-profile comparison method shows an improved ability to match distantly related protein domains. Therefore, the method should be useful for annotation and homology modeling of uncharacterized proteins.

PSI-BLAST-ISS: an intermediate sequence search tool for estimation of the position-specific alignment reliability

BackgroundProtein sequence alignments have become indispensable for virtually any evolutionary, structural or functional study involving proteins. Modern sequence search and comparison methods combined with rapidly increasing sequence data often can reliably match even distantly related proteins that share little sequence similarity. However, even highly significant matches generally may have incorrectly aligned regions. Therefore when exact residue correspondence is used to transfer biological information from one aligned sequence to another, it is critical to know which alignment regions are reliable and which may contain alignment errors.ResultsPSI-BLAST-ISS is a standalone Unix-based tool designed to delineate reliable regions of sequence alignments as well as to suggest potential variants in unreliable regions. The region-specific reliability is assessed by producing multiple sequence alignments in different sequence contexts followed by the analysis of the consistency of alignment variants. The PSI-BLAST-ISS output enables the user to simultaneously analyze alignment reliability between query and multiple homologous sequences. In addition, PSI-BLAST-ISS can be used to detect distantly related homologous proteins. The software is freely available at: http://www.ibt.lt/bioinformatics/iss.ConclusionPSI-BLAST-ISS is an effective reliability assessment tool that can be useful in applications such as comparative modelling or analysis of individual sequence regions. It favorably compares with the existing similar software both in the performance and functional features.

COMA server for protein distant homology search

SUMMARYnDetection of distant homology is a widely used computational approach for studying protein evolution, structure and function. Here, we report a homology search web server based on sequence profile-profile comparison. The user may perform searches in one of several regularly updated profile databases using either a single sequence or a multiple sequence alignment as an input. The same profile databases can also be downloaded for local use. The capabilities of the server are illustrated with the identification of new members of the highly diverse PD-(D/E)XK nuclease superfamily.nnnAVAILABILITYnhttp://www.ibt.lt/bioinformatics/coma/

Identification of new homologs of PD-(D/E)XK nucleases by support vector machines trained on data derived from profile–profile alignments

Abstract PD-(D/E)XK nucleases, initially represented by only Type II restriction enzymes, now comprise a large and extremely diverse superfamily of proteins. They participate in many different nucleic acids transactions including DNA degradation, recombination, repair and RNA processing. Different PD-(D/E)XK families, although sharing a structurally conserved core, typically display little or no detectable sequence similarity except for the active site motifs. This makes the identification of new superfamily members using standard homology search techniques challenging. To tackle this problem, we developed a method for the detection of PD-(D/E)XK families based on the binary classification of profile–profile alignments using support vector machines (SVMs). Using a number of both superfamily-specific and general features, SVMs were trained to identify true positive alignments of PD-(D/E)XK representatives. With this method we identified several PFAM families of uncharacterized proteins as putative new members of the PD-(D/E)XK superfamily. In addition, we assigned several unclassified restriction enzymes to the PD-(D/E)XK type. Results show that the new method is able to make confident assignments even for alignments that have statistically insignificant scores. We also implemented the method as a freely accessible web server at http://www.ibt.lt/bioinformatics/software/pdexk/.

Voroprot: an interactive tool for the analysis and visualization of complex geometric features of protein structure

UNLABELLEDnWe present Voroprot, an interactive cross-platform software tool that provides a unique set of capabilities for exploring geometric features of protein structure. Voroprot allows the construction and visualization of the Apollonius diagram (also known as the additively weighted Voronoi diagram), the Apollonius graph, protein alpha shapes, interatomic contact surfaces, solvent accessible surfaces, pockets and cavities inside protein structure.nnnAVAILABILITYnVoroprot is available for Windows, Linux and Mac OS X operating systems and can be downloaded from http://www.ibt.lt/bioinformatics/voroprot/.

The use of automatic tools and human expertise in template-based modeling of CASP8 target proteins.

Here, we describe our template‐based protein modeling approach and its performance during the eighth community‐wide experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP8, http://predictioncenter.org/casp8). In CASP8, our modeling approach was supplemented by the newly developed distant homology detection method based on sequence profile–profile comparison. Detection of structural homologs that could be used as modeling templates was largely achieved by automated profile‐based searches. However, the other two major steps in template‐based modeling (TBM) (selection of the best template(s) and construction of the optimal sequence‐structure alignment) to a large degree relied on the combination of automatic tools and manual input. The analysis of 64 domains categorized by CASP8 assessors as TBM domains revealed that we missed correct structural templates for only four of them. The use of multiple templates or their fragments enabled us to improve over the structure of the single best PDB template in about 1/3 of our models for TBM domains. Our results for sequence‐structure alignments are mixed. Although many models have optimal or near optimal sequence mapping, a large fraction contains one or more misaligned regions. Strikingly, in spite of this, our TBM models have the best overall alignment accuracy scores. This clearly suggests that the correct mapping of protein sequence onto three‐dimensional structure remains one of the big challenges in protein structure prediction. Proteins 2009.

Re-searcher: a system for recurrent detection of homologous protein sequences

BackgroundSequence searches are routinely employed to detect and annotate related proteins. However, a rapid growth of databases necessitates a frequent repetition of sequence searches and subsequent analysis of obtained results. Although there are several automatic systems available for executing periodical sequence searches and reporting results, they all suffer either from a lack of sensitivity, restrictive database choice or limited flexibility in setting up search strategies. Here, a new sequence search and reporting software package designed to address these shortcomings is described.ResultsRe-searcher is an open-source highly configurable system for recurrent detection and reporting of new homologs for the sequence of interest in specified protein sequence databases. Searches are performed using PSI-BLAST at desired time intervals either within NCBI or local databases. In addition to searches against individual databases, the system can perform PDB-BLAST-like combined searches, when PSI-BLAST profile generated during search against the first database is used to search the second database. The system supports multiple users enabling each to separately keep track of multiple queries and query-specific results.ConclusionsRe-searcher features a large number of options enabling automatic periodic detection of both close and distant homologs. At the same time it has a simple and intuitive interface, making the analysis of results even for a large number of queries a straightforward task.

The PPI3D web server for searching, analyzing and modeling protein-protein interactions in the context of 3D structures.

Summary: The PPI3D web server is focused on searching and analyzing the structural data on protein‐protein interactions. Reducing the data redundancy by clustering and analyzing the properties of interaction interfaces using Voronoi tessellation makes this software a highly effective tool for addressing different questions related to protein interactions. Availability and Implementation: The server is freely accessible at http://bioinformatics.lt/software/ppi3d/. Contact: ceslovas.venclovas@bti.vu.lt Supplementary information: Supplementary data are available at Bioinformatics online.

Bayesian nonparametrics in protein remote homology search

MOTIVATIONnWide application of modeling of three-dimensional protein structures in biomedical research motivates developing protein sequence alignment computer tools featuring high alignment accuracy and sensitivity to remotely homologous proteins. In this paper, we aim at improving the quality of alignments between sequence profiles, encoded multiple sequence alignments. Modeling profile contexts, fixed-length profile fragments, is engaged to achieve this goal.nnnRESULTSnWe develop a hierarchical Dirichlet process mixture model to describe the distribution of profile contexts, which is able to capture dependencies between amino acids in each context position. The model represents an attempt at modeling profile fragments at several hierarchical levels, within the profile and among profiles. Even modeling unit-length contexts leads to greater improvements than processing 13-length contexts previously. We develop a new profile comparison method, called COMER, integrating the model. A benchmark with three other profile-to-profile comparison methods shows an increase in both sensitivity and alignment quality.nnnAVAILABILITY AND IMPLEMENTATIONnCOMER is open-source software licensed under the GNU GPLv3, available at https://sourceforge.net/projects/comernnnCONTACTnmindaugas.margelevicius@bti.vu.ltnnnSUPPLEMENTARY INFORMATIONnSupplementary data are available at Bioinformatics online.