MOTIVATION: Determination of drug absorption is an important component of the drug discovery and development process in that it plays a key role in the decision to promote drug candidates to clinical trials. We have developed a method that, on the basis of an analysis of the dynamic distribution of water molecules around a compound obtained by molecular dynamics simulations, can compute a parameter-free value that correlates very well with the compound permeability measured using the human colon adenocarcinoma (Caco-2) cell line assay. RESULTS: The method has been tested on twenty-three neutral drugs for which a consistent set of experimental data is available. We show here that our method reproduces the experimental data better than other existing tools. Furthermore it provides a detailed view of the relationship between the hydration and the permeability properties of molecules. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Predicting the structure of protein loops is very challenging, mainly because they are not necessarily subject to strong evolutionary pressure. This implies that, unlike the rest of the protein, standard homology modeling techniques are not very effective in modeling their structure. However, loops are often involved in protein function, hence inferring their structure is important for predicting protein structure as well as function. RESULTS: We describe a method, LoopIng, based on the Random Forest automated learning technique, which, given a target loop, selects a structural template for it from a database of loop candidates. Compared to the most recently available methods, LoopIng is able to achieve similar accuracy for short loops (4-10 residues) and significant enhancements for long loops (11-20 residues). The quality of the predictions is robust to errors that unavoidably affect the stem regions when these are modeled. The method returns a confidence score for the predicted template loops and has the advantage of being very fast (on average: 1 min/loop). AVAILABILITY AND IMPLEMENTATION: www.biocomputing.it/looping. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: Antibodies are rapidly becoming essential tools in the clinical practice, given their ability to recognize their cognate antigens with high specificity and affinity, and a high yield at reasonable costs in model animals. Unfortunately, when administered to human patients, xenogeneic antibodies can elicit unwanted and dangerous immunogenic responses. Antibody humanization methods are designed to produce molecules with a better safety profile still maintaining their ability to bind the antigen. This can be accomplished by grafting the non-human regions determining the antigen specificity into a suitable human template. Unfortunately, this procedure may results in a partial or complete loss of affinity of the grafted molecule that can be restored by back-mutating some of the residues of human origin to the corresponding murine ones. This trial-and-error procedure is hard and involves expensive and time-consuming experiments. Here we present tools for antibody humanization (Tabhu) a web server for antibody humanization. Tabhu includes tools for human template selection, grafting, back-mutation evaluation, antibody modelling and structural analysis, helping the user in all the critical steps of the humanization experiment protocol. AVAILABILITY: http://www.biocomputing.it/tabhu CONTACT: [email protected], [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: Protein-coding genes with multiple alternative polyadenylation sites can generate mRNA 3'UTR sequences of different lengths, thereby causing the loss or gain of regulatory elements, which can affect stability, localization and translation efficiency. 3USS is a web-server developed with the aim of giving experimentalists the possibility to automatically identify alternative 3 ': UTRs (shorter or longer with respect to a reference transcriptome), an option that is not available in standard RNA-seq data analysis procedures. The tool reports as putative novel the 3 ': UTRs not annotated in available databases. Furthermore, if data from two related samples are uploaded, common and specific alternative 3 ': UTRs are identified and reported by the server. AVAILABILITY AND IMPLEMENTATION: 3USS is freely available at http://www.biocomputing.it/3uss_server.

MOTIVATION: Antibodies are able to recognize a wide range of antigens through their complementary determining regions formed by six hypervariable loops. Predicting the 3D structure of these loops is essential for the analysis and reengineering of novel antibodies with enhanced affinity and specificity. The canonical structure model allows high accuracy prediction for five of the loops. The third loop of the heavy chain, H3, is the hardest to predict because of its diversity in structure, length and sequence composition. RESULTS: We describe a method, based on the Random Forest automatic learning technique, to select structural templates for H3 loops among a dataset of candidates. These can be used to predict the structure of the loop with a higher accuracy than that achieved by any of the presently available methods. The method also has the advantage of being extremely fast and returning a reliable estimate of the model quality. AVAILABILITY AND IMPLEMENTATION: The source code is freely available at http://www.biocomputing.it/H3Loopred/ .

SUMMARY: MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modexplorer. Website implemented in HTML and JavaScript with all major browsers supported. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The need for new drugs and new targets is particularly compelling in an era that is witnessing an alarming increase of drug resistance in human pathogens. The identification of new targets of known drugs is a promising approach, which has proven successful in several cases. Here, we describe a database that includes information on 5153 putative drug-target pairs for 150 human pathogens derived from available drug-target crystallographic complexes. AVAILABILITY AND IMPLEMENTATION: The TiPs database is freely available at http://biocomputing.it/tips. CONTACT: [email protected] or [email protected].

MOTIVATION: Antibodies or immunoglobulins are proteins of paramount importance in the immune system. They are extremely relevant as diagnostic, biotechnological and therapeutic tools. Their modular structure makes it easy to re-engineer them for specific purposes. Short of undergoing a trial and error process, these experiments, as well as others, need to rely on an understanding of the specific determinants of the antibody binding mode. RESULTS: In this article, we present a method to identify, on the basis of the antibody sequence alone, which residues of an antibody directly interact with its cognate antigen. The method, based on the random forest automatic learning techniques, reaches a recall and specificity as high as 80% and is implemented as a free and easy-to-use server, named prediction of Antibody Contacts. We believe that it can be of great help in re-design experiments as well as a guide for molecular docking experiments. The results that we obtained also allowed us to dissect which features of the antibody sequence contribute most to the involvement of specific residues in binding to the antigen. AVAILABILITY: http://www.biocomputing.it/proABC. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: MODalign is an interactive web-based tool aimed at helping protein structure modelers to inspect and manually modify the alignment between the sequences of a target protein and of its template(s). It interactively computes, displays and, upon modification of the target-template alignment, updates the multiple sequence alignments of the two protein families, their conservation score, secondary structure and solvent accessibility values, and local quality scores of the implied three-dimensional model(s). Although it has been designed to simplify the target-template alignment step in modeling, it is suitable for all cases where a sequence alignment needs to be inspected in the context of other biological information. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://modorama.biocomputing.it/modalign. Website implemented in HTML and JavaScript with all major browsers supported. CONTACT: [email protected].

BACKGROUND: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. RESULTS: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. CONCLUSIONS: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by non-academics: No.

MOTIVATION: Analysis of the human genome revealed that the amount of transcribed sequence is an order of magnitude greater than the number of predicted and well-characterized genes. A sizeable fraction of these transcripts is related to alternatively spliced forms of known protein coding genes. Inspection of the alternatively spliced transcripts identified in the pilot phase of the ENCODE project has clearly shown that often their structure might substantially differ from that of other isoforms of the same gene, and therefore that they might perform unrelated functions, or that they might even not correspond to a functional protein. Identifying these cases is obviously relevant for the functional assignment of gene products and for the interpretation of the effect of variations in the corresponding proteins. RESULTS: Here we describe a publicly available tool that, given a gene or a protein, retrieves and analyses all its annotated isoforms, provides users with three-dimensional models of the isoform(s) of his/her interest whenever possible and automatically assesses whether homology derived structural models correspond to plausible structures. This information is clearly relevant. When the homology model of some isoforms of a gene does not seem structurally plausible, the implications are that either they assume a structure unrelated to that of the other isoforms of the same gene with presumably significant functional differences, or do not correspond to functional products. We provide indications that the second hypothesis is likely to be true for a substantial fraction of the cases. AVAILABILITY: http://maistas.bioinformatica.crs4.it/.

[No abstract available]

MOTIVATION: Several international collaborations and local projects are producing extensive catalogues of genomic variations that are supplementing existing collections such as the OMIM catalogue. The flood of this type of data will keep increasing and, especially, it will be relevant to a wider user base, including not only molecular biologists, geneticists and bioinformaticians, but also clinical researchers. Mapping the observed variations, sometimes only described at the amino acid level, on a genome, identifying whether they affect a gene and-if so-whether they also affect different isoforms of the same gene, is a time consuming and often frustrating task. RESULTS: The PICMI server is an easy to use tool for quickly mapping one or more amino acid or nucleotide variations on a genome and its products, including alternatively spliced isoforms. AVAILABILITY: The server is available at www.biocomputing.it/picmi.

BACKGROUND: Bacterial infections represent a global health challenge. The identification of novel antibacterial targets for both therapy and vaccination is needed on a constant basis because resistance continues to spread worldwide at an alarming rate. Even infections that were once easy to treat are becoming difficult or, in some cases, impossible to cure. Ideal targets for both therapy and vaccination are bacterial proteins exposed on the surface of the organism, which are often involved in host-pathogen interaction. Their identification can greatly benefit from technologies such as bioinformatics, proteomics and DNA microarrays. RESULTS: Here we describe a pipeline named SLEP (Surface Localization Extracellular Proteins), based on an automated optimal combination and sequence of usage of reliable available tools for the computational identification of the surfome, i.e. of the subset of proteins exposed on the surface of a bacterial cell. CONCLUSIONS: The tool not only simplifies the usage of these methods, but it also improves the results by selecting the specifying order and combination of the instruments. The tool is freely available at http://www.caspur.it/slep.

This special issue contains the papers accepted for presentation at the 2009 ISMB/ECCB Conference (http://www.iscb.org/ismbeccb2009/); the joint conference of ‘Intelligent Systems for Molecular Biology’ and ‘European Conference on Computational Biology’ to be held in Stockholm, Sweden from June 27 to July 2, 2009. The papers contained in this volume are a selection of the 242 papers submitted to the conference. The papers were submitted to 11 distinct areas, with two co-chairs for most areas, who selected their area committees and oversaw the reviewing process. Several of the area chairs were new, and this year ‘Population Genomics’ was added to the 10 areas that made up the ISMB Conference in 2008. The areas, co-chairs and submission/acceptance information are listed in the following table. The area chairs were responsible for selecting the members of the Program Committee that consisted of more than 300 reviewers, assisted by a sizeable number of sub-reviewers. Most papers received three reviews and several received four or more reports. There was an intense discussion between referees and the area chairs. In a first round of evaluation, during a long phone discussion of area chairs, 37 papers were selected for acceptance, with another 16 papers selected to undergo a further evaluation by a broad range of area chairs; from those 16 papers, another 9 were accepted for the conference after a second phone discussion. For all the papers where the referee comments might have confused the authors, particularly for rejected papers, additional comments were added by the area chairs. In total, 46 papers were accepted (formally, conditionally accepted pending revision). After acceptance notices were sent, the authors had 2 weeks to modify their papers, incorporating suggestions from the reviews and responding to reviewers comments. These modified papers and the authors' responses were examined during the next week to spot any additional problems and to check how each paper was modified in response to the reviewers comments. Any modified paper that did not incorporate reviewers suggestions or defend that omission in the author's explanation could have been rejected at this point. We are happy to say that all 46 conditionally accepted papers were finally accepted for the conference. The final acceptance rate was 19%, a bit higher than in previous years, reflecting a lower number of submissions this year (242 submissions compared with 287 submissions, and 17.1% acceptance rate in 2008; 15.8% acceptance rate in 2007). The corresponding authors of submitted papers came from 29 countries, including 450 from North America, 271 from Europe and Israel, 164 from Asia and Australia and 14 from South America. We would like to thank the area chairs and reviewers for their efforts, dedication and quality of their professional work; all authors of submitted papers; Alfonso Valencia for sharing his experience from ISMB08; Andrei Voronkov for technical support with the EasyChair system; the team at Oxford University Press for type-setting the papers; the Conference Chairs, Gene Myers and Marie-France Sagot for their continuous support; and Steven Leard for helping us to deal with the all kinds of issues.

UNLABELLED: We describe a web server for the automatic prediction of immunoglobulin variable domains based on the canonical structure model. The server is user-friendly and flexible. It allows the user to select the templates for the frameworks and the loops using different strategies. The final output is a full-fledged 3D model of the variable domains of the target immunoglobulin. AVAILABILITY: The server is openly accessible to academic users at the address: http://arianna.bio.uniroma1.it/pigs. It does not require registration and there is no limit to the number of sequences that can be submitted.

BACKGROUND: The occurrence of very similar structural motifs brought about by different parts of non homologous proteins is often indicative of a common function. Indeed, relatively small local structures can mediate binding to a common partner, be it a protein, a nucleic acid, a cofactor or a substrate. While it is relatively easy to identify short amino acid or nucleotide sequence motifs in a given set of proteins or genes, and many methods do exist for this purpose, much more challenging is the identification of common local substructures, especially if they are formed by non consecutive residues in the sequence. RESULTS: Here we describe a publicly available tool, able to identify common structural motifs shared by different non homologous proteins in an unsupervised mode. The motifs can be as short as three residues and need not to be contiguous or even present in the same order in the sequence. Users can submit a set of protein structures deemed or not to share a common function (e.g. they bind similar ligands, or share a common epitope). The server finds and lists structural motifs composed of three or more spatially well conserved residues shared by at least three of the submitted structures. The method uses a local structural comparison algorithm to identify subsets of similar amino acids between each pair of input protein chains and a clustering procedure to group similarities shared among different structure pairs. CONCLUSIONS: FunClust is fast, completely sequence independent, and does not need an a priori knowledge of the motif to be found. The output consists of a list of aligned structural matches displayed in both tabular and graphical form. We show here examples of its usefulness by searching for the largest common structural motifs in test sets of non homologous proteins and showing that the identified motifs correspond to a known common functional feature.

BACKGROUND: Protein-protein interactions are at the basis of most cellular processes and crucial for many bio-technological applications. During the last few years the development of high-throughput technologies has produced several large-scale protein-protein interaction data sets for various organisms. It is important to develop tools for dissecting their content and analyse the information they embed by data-integration and computational methods. RESULTS: Interactions can be mediated by the presence of specific features, such as motifs, surface patches and domains. The co-occurrence of these features on proteins interacting with the same protein can indicate mutually exclusive interactions and, therefore, can be used for inferring the involvement of the proteins in common biological processes. We present here a publicly available server that allows the user to investigate protein interaction data in light of other biological information, such as their sequences, presence of specific domains, process and component ontologies. The server can be effectively used to construct a high-confidence set of mutually exclusive interactions by identifying similar features in groups of proteins sharing a common interaction partner. As an example, we describe here the identification of common motifs, function, cellular localization and domains in different datasets of yeast interactions. CONCLUSIONS: The server can be used to analyse user-supplied datasets, it contains pre-processed data for four yeast Protein Protein interaction datasets and the results of their statistical analysis. These show that the presence of common motifs in proteins interacting with the same partner is a valuable source of information, it can be used to investigate the properties of the interacting proteins and provides information that can be effectively integrated with other sources. As more experimental interaction data become available, this tool will become more and more useful to gain a more detailed picture of the interactome.

BACKGROUND: One of the most interesting problems in molecular immunology is epitope mapping, i.e. the identification of the regions of interaction between an antigen and an antibody. The solution to this problem, even if approximate, would help in designing experiments to precisely map the residues involved in the interaction and could be instrumental both in designing peptides able to mimic the interacting surface of the antigen and in understanding where immunologically important regions are located in its three-dimensional structure. From an experimental point of view, both genetically encoded and chemically synthesised peptide libraries can be used to identify sequences recognized by a given antibody. The problem then arises of which region of a folded protein the selected peptides correspond to. RESULTS: We have developed a method able to find the surface region of a protein that can be effectively mimicked by a peptide, given the structure of the protein and the maximum number of side chains deemed to be required for recognition. The method is implemented as a publicly available server. It can also find and report all peptide sequences of a specified length that can mimic the surface of a given protein and store them in a database. The immediate application of the server is the mapping of antibody epitopes, however the system is sufficiently flexible for allowing other questions to be asked, for example one can compare the peptides representing the surface of two proteins known to interact with the same macromolecule to find which is the most likely interacting region. CONCLUSION: We believe that the MEPS server, available at http://www.caspur.it/meps, will be a useful tool for immunologists and structural and computational biologists. We plan to use it ourselves to implement a database of "surface mimicking peptides" for all proteins of known structure and proteins that can be reliably modelled by comparative modelling.

UNLABELLED: Down syndrome (DS) is the most frequent form of mental retardation and is caused by chromosome 21 (HSA21) trisomy. Despite the number of known genes involved in DS and its high therapeutic interest, biological mechanisms leading to the DS phenotype are not fully clear. We present a functional hypothesis based on fold recognition and hidden Markov model techniques for four HSA21 genes located in the DS Candidate Region (DSCR). More specifically, we propose that they are members of a novel mitogen-activated protein kinase pathway with DYRK1A, SNF1LK and RIPK4 gene products being elements of the kinase cascade and the DSCR3 acting as structural scaffold for their interaction. This hypothesis finds support in various biochemical studies concerning the biological behavior and features of the involved HSA21 proteins. Our analysis calls for specifically designed experiments to validate our prediction and establish its relevance in terms of therapeutic approaches to the disease. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: The environmental sequencing of the Sargasso Sea has introduced a huge new resource of genomic information. Unlike the protein sequences held in the current searchable databases, the Sargasso Sea sequences originate from a single marine environment and have been sequenced from species that are not easily obtainable by laboratory cultivation. The resource also contains very many fragments of whole protein sequences, a side effect of the shotgun sequencing method.These sequences form a significant addendum to the current searchable databases but also present us with some intrinsic difficulties. While it is important to know whether it is possible to assign function to these sequences with the current methods and whether they will increase our capacity to explore sequence space, it is also interesting to know how current bioinformatics techniques will deal with the new sequences in the resource. RESULTS: The Sargasso Sea sequences seem to introduce a bias that decreases the potential of current methods to propose structure and function for new proteins. In particular the high proportion of sequence fragments in the resource seems to result in poor quality multiple alignments. CONCLUSION: These observations suggest that the new sequences should be used with care, especially if the information is to be used in large scale analyses. On a positive note, the results may just spark improvements in computational and experimental methods to take into account the fragments generated by environmental sequencing techniques.

Abstract Motivation: Genome-wide functional annotation either by manual or automatic means has raised considerable concerns regarding the accuracy of assignments and the reproducibility of methodologies. In addition, a performance evaluation of automated systems that attempt to tackle sequence analyses rapidly and reproducibly is generally missing. In order to quantify the accuracy and reproducibility of function assignments on a genome-wide scale, we have re-annotated the entire genome sequence of Chlamydia trachomatis (serovar D), in a collaborative manner. Results: We have encoded all annotations in a structured format to allow further comparison and data exchange and have used a scale that records the different levels of potential annotation errors according to their propensity to propagate in the database due to transitive function assignments. We conclude that genome annotation may entail a considerable amount of errors, ranging from simple typographical errors to complex sequence analysis problems. The most surprising result of this comparative study is that automatic systems might perform as well as the teams of experts annotating genome sequences. Availability and supplementary information: http://www.ebi.ac.uk/research/cgg/annotation/cteval/ Contact: [email protected] * To whom correspondence should be addressed. † INA-EKETA, GR-57001 Thessaloniki, Greece ‡ Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA § Aetion Technologies LLC, Worthington, OH 43085, USA ¶ Institut Curie, F-75248 Paris, France ∥ CNRS, UMR6543, F-06108 Nice, France ** Alma Bioinformatics, E-28760 Madrid, Spain †† Cap Gemini Ernst & Young, London SW1X 7LX, UK ‡‡ Univ. of Rome ‘La Sapienza’, I-00185 Rome, Italy §§ MWG-Biotech AG, Ebersberg, D-85560 Berlin, Germany ¶¶ Wellcome Trust Biocentre, Univ. of Dundee, Dundee DD1 5HN, UK