MOTIVATION: The interpretation of cancer-related single-nucleotide variants (SNVs) considering the protein features they affect, such as known functional sites, protein-protein interfaces, or relation with already annotated mutations, might complement the annotation of genetic variants in the analysis of NGS data. Current tools that annotate mutations fall short on several aspects, including the ability to use protein structure information or the interpretation of mutations in protein complexes. RESULTS: We present the Structure-PPi system for the comprehensive analysis of coding SNVs based on 3D protein structures of protein complexes. The 3D repository used, Interactome3D, includes experimental and modeled structures for proteins and protein-protein complexes. Structure-PPi annotates SNVs with features extracted from UniProt, InterPro, APPRIS, dbNSFP and COSMIC databases. We illustrate the usefulness of Structure-PPi with the interpretation of 1 027 122 non-synonymous SNVs from COSMIC and the 1000G Project that provides a collection of ∼172 700 SNVs mapped onto the protein 3D structure of 8726 human proteins (43.2% of the 20 214 SwissProt-curated proteins in UniProtKB release 2014_06) and protein-protein interfaces with potential functional implications. AVAILABILITY AND IMPLEMENTATION: Structure-PPi, along with a user manual and examples, isavailable at http://structureppi.bioinfo.cnio.es/Structure, the code for local installations at https://github.com/Rbbt-Workflows

UNLABELLED: Biological pathways are important elements of systems biology and in the past decade, an increasing number of pathway databases have been set up to document the growing understanding of complex cellular processes. Although more genome-sequence data are becoming available, a large fraction of it remains functionally uncharacterized. Thus, it is important to be able to predict the mapping of poorly annotated proteins to original pathway models. RESULTS: We have developed a Relational Learning-based Extension (RLE) system to investigate pathway membership through a function prediction approach that mainly relies on combinations of simple properties attributed to each protein. RLE searches for proteins with molecular similarities to specific pathway components. Using RLE, we associated 383 uncharacterized proteins to 28 pre-defined human Reactome pathways, demonstrating relative confidence after proper evaluation. Indeed, in specific cases manual inspection of the database annotations and the related literature supported the proposed classifications. Examples of possible additional components of the Electron transport system, Telomere maintenance and Integrin cell surface interactions pathways are discussed in detail. AVAILABILITY: All the human predicted proteins in the 2009 and 2012 releases 30 and 40 of Reactome are available at http://rle.bioinfo.cnio.es.

Computational biology can be considered a supradisciplinary field of knowledge that merges biology, chemistry, physics, and computer science into a broad-based science that is important to furthering our understanding of the life sciences.Although a relatively new area of research, it is recognized as a crucial field for scientific advancement in developing countries.This Perspective introduces our vision of the role of computational biology in biomedical research and teaching in Cuba.Except where individuals are directly quoted, any opinions expressed herein should be considered those of the authors.(For author information, see Box 1.)The challenge for Cuba was to initiate this new field of research and development without existing expertise.In addition, we had to face the same problems experienced elsewhere in this field-most life scientists were not familiar with the potential of information processing tools, and conversely, computer scientists were unfamiliar with problems facing the life sciences, often brought about by large amounts of new data.Cuba also faced unique problems.As a result of the United States trade embargo, Cuban scientists buy most of their research supplies from Europe.This adds delays and can triple costs, especially for equipment or spare parts that are made only in the US and must be purchased from a third party.In addition, curbs on travel between the US and Cuba isolate Cuban scientists from colleagues and conferences in the United States.Finally, Internet access is also affected by this policy, and Cuban scientists lack fast and efficient access to scientific information from overseas.Despite these drawbacks, Cuban biotech products and activities from biomedical institutes within Cuba have been recognized by other authors [1-4].Further offsetting these drawbacks, our country has a high educational level, and Cuban universities produce hundreds of new scientists every year.The challenge then is to implement higher education using both the coherence of existing disciplinary education and the means to break down disciplinary walls for students interested in computational biology and other multidisciplinary fields.Since Cuba has scant resources for significant investments in scientific instrumentation, a science such as computational biology that relies mostly on computers, network connectivity, and human resources offers an excellent opportunity.The current challenges facing computational biology research in Cuba are: (1) getting results of direct interest and impact to motivate funding, (2) fostering young leading scientists to sustain present and future research, and (3) using limited infrastructure in the most efficient and productive way.Computational sciences in Cuba were first applied to physics and chemistry in the late 1960s at the University of Havana, with the use of quantum mechanics to model sugar cane derivative molecules [5].Such an early application of this technology, which was entirely absent in the majority of the world, indicated a new approach to scientific development in a Latin American country.Another important effort began in the early 1970s at the National Center for Scientific Research in the field of computational neurosciences, mostly with Cuban-designed and Cubanmanufactured hardware [6].Since then, after a heavy effort to build up human scientific potential, mostly with the influence and support of Eastern European countries, the problem of Cuba's limited computing potential was overcome and Cuban scientists gained valuable experience with microcomputers in the 1980s.Limitations to high-tech development during the 1970s originated from the obsolescence of devices built in the former Soviet bloc and a strong dependence on components from the same market, which hindered Cuba's national hardware production.Cuba was well-positioned to take advantage of the benefits of the microcomputer revolution of the 1980s.Applications of these new devices to the physical and biological sciences were frequent in that time and several computer programs were written or adapted to allow such applications [7,8].During the economic crisis of the 1990s, these developments continued in the established groups and appeared in new teams at the Cuban Center for Genetic Engineering and Biotechnology (CIGB) [9].

MOTIVATION: Homology modeling is rapidly becoming the method of choice for obtaining three-dimensional coordinates for proteins because genome projects produce sequences at a much higher rate than NMR and X-ray laboratories can solve the three-dimensional structures. The quality of protein models will not be immediately clear to novices and support with the evaluation seems to be needed. Expert users are sometimes interested in evaluating the quality of modeling programs rather than the quality of the models themselves. RESULTS: Three servers have been made available to the scientific community: a homology modeling server, a model quality evaluation server and a server that evaluates models built of proteins for which the structure is already known, thereby implicitly evaluating the quality of the modeling program. AVAILABILITY: The modeling-related servers and several structure analysis servers are freely available at http://swift.embl-heidelberg.de/servers/ CONTACT: [email protected]