Abstract: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder with a prevalence of 0.9-2.6%. Twin studies showed a heritability of 38-90%, indicating strong genetic contributions. Yet it is unclear how many genes have been associated with ASD and how strong the evidence is. A comprehensive review and analysis of literature and data may bring a clearer big picture of autism genetics. We show that as many as 2193 genes, 2806 SNPs/VNTRs, 4544 copy number variations (CNVs) and 158 linkage regions have been associated with ASD by GWAS, genome-wide CNV studies, linkage analyses, low-scale genetic association studies, expression profiling and other low-scale experimental studies. To evaluate the evidence, we collected metadata about each study including clinical and demographic features, experimental design and statistical significance, and used a scoring and ranking approach to select a core data set of 434 high-confidence genes. The genes mapped to pathways including neuroactive ligand-receptor interaction, synapse transmission and axon guidance. To better understand the genes we parsed over 30 databases to retrieve extensive data about expression patterns, protein interactions, animal models and pharmacogenetics. We constructed a MySQL-based online database and share it with the broader autism research community at http://autismkb.cbi.pku.edu.cn, supporting sophisticated browsing and searching functionalities.

Abstract: Leprosy is an infectious disease caused by Mycobacterium leprae. The increasing drug and multi-drug resistance of M. leprae enforce the importance of finding new drug targets. Mycobacterium has unusually impermeable cell wall that contributes to considerable resistance to many drugs. Peptidoglycan is an important component of the cell wall of M. leprae. UDP-N-acetylmuramoyl-glycyl-D-glutamate-2, 6-diaminopimelate ligase (MurE) plays a crucial role in the peptidoglycan biosynthesis and hence it could be considered as a potential drug target for leprosy. Structure of this enzyme for M. leprae has not yet been elucidated. We modeled the three-dimensional structure of MurE from M. leprae using comparative modeling methods based on the X-ray crystal structure of MurE from E. coli and validated. The 3D-structure of M. leprae MurE enzyme was docked with its substrates meso-diaminopimelic acid (A2pm) and UDP-N-acetyl muramoyl-glycyl-D- glutamate (UMGG) and its product UDP-N-acetyl muramoyl-glycyl-D-glu-meso-A(2)pm (UTP) and also with ATP. The docked complexes reveal the amino acids responsible for binding the substrates. Superposition of these complex structures suggests that carboxylic acid group of UMGG is positioned in proximity to gamma-phosphate of the ATP to facilitate the formation of acylphosphate intermediate. The orientation of an amino group of A(2)pm facilitates the nucleophilic attack to form the product. Overall, the proposed model together with its binding features gained from docking studies could help to design a truly selective ligand inhibitor specific to MurE for the treatment of leprosy.

Abstract: The Yeast Metabolome Database (YMDB, http://www.ymdb.ca) is a richly annotated 'metabolomic' database containing detailed information about the metabolome of Saccharomyces cerevisiae. Modeled closely after the Human Metabolome Database, the YMDB contains >2000 metabolites with links to 995 different genes/proteins, including enzymes and transporters. The information in YMDB has been gathered from hundreds of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the YMDB also contains an extensive collection of experimental intracellular and extracellular metabolite concentration data compiled from detailed Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) metabolomic analyses performed in our lab. This is further supplemented with thousands of NMR and MS spectra collected on pure, reference yeast metabolites. Each metabolite entry in the YMDB contains an average of 80 separate data fields including comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, intracellular/extracellular concentrations, growth conditions and substrates, pathway information, enzyme data, gene/protein sequence data, as well as numerous hyperlinks to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of S. cervesiae's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers, but also to yeast biologists, systems biologists, the industrial fermentation industry, as well as the beer, wine and spirit industry.

Abstract: Gene3D http://gene3d.biochem.ucl.ac.uk is a comprehensive database of protein domain assignments for sequences from the major sequence databases. Domains are directly mapped from structures in the CATH database or predicted using a library of representative profile HMMs derived from CATH superfamilies. As previously described, Gene3D integrates many other protein family and function databases. These facilitate complex associations of molecular function, structure and evolution. Gene3D now includes a domain functional family (FunFam) level below the homologous superfamily level assignments. Additions have also been made to the interaction data. More significantly, to help with the visualization and interpretation of multi-genome scale data sets, we have developed a new, revamped website. Searching has been simplified with more sophisticated filtering of results, along with new tools based on Cytoscape Web, for visualizing protein-protein interaction networks, differences in domain composition between genomes and the taxonomic distribution of individual superfamilies.

Abstract: Peptidases, their substrates and inhibitors are of great relevance to biology, medicine and biotechnology. The MEROPS database (http://merops.sanger.ac.uk) aims to fulfil the need for an integrated source of information about these. The database has hierarchical classifications in which homologous sets of peptidases and protein inhibitors are grouped into protein species, which are grouped into families, which are in turn grouped into clans. The database has been expanded to include proteolytic enzymes other than peptidases. Special identifiers for peptidases from a variety of model organisms have been established so that orthologues can be detected in other species. A table of predicted active-site residue and metal ligand positions and the residue ranges of the peptidase domains in orthologues has been added to each peptidase summary. New displays of tertiary structures, which can be rotated or have the surfaces displayed, have been added to the structure pages. New indexes for gene names and peptidase substrates have been made available. Among the enhancements to existing features are the inclusion of small-molecule inhibitors in the tables of peptidase-inhibitor interactions, a table of known cleavage sites for each protein substrate, and tables showing the substrate-binding preferences of peptidases derived from combinatorial peptide substrate libraries.

Abstract: Nematode.net (http://nematode.net) has been a publicly available resource for studying nematodes for over a decade. In the past 3 years, we reorganized Nematode.net to provide more user-friendly navigation through the site, a necessity due to the explosion of data from next-generation sequencing platforms. Organism-centric portals containing dynamically generated data are available for over 56 different nematode species. Next-generation data has been added to the various data-mining portals hosted, including NemaBLAST and NemaBrowse. The NemaPath metabolic pathway viewer builds associations using KOs, rather than ECs to provide more accurate and fine-grained descriptions of proteins. Two new features for data analysis and comparative genomics have been added to the site. NemaSNP enables the user to perform population genetics studies in various nematode populations using next-generation sequencing data. HelmCoP (Helminth Control and Prevention) as an independent component of Nematode.net provides an integrated resource for storage, annotation and comparative genomics of helminth genomes to aid in learning more about nematode genomes, as well as drug, pesticide, vaccine and drug target discovery. With this update, Nematode.net will continue to realize its original goal to disseminate diverse bioinformatic data sets and provide analysis tools to the broad scientific community in a useful and user-friendly manner.

Abstract: Aging is the major biomedical challenge of this century. The percentage of elderly people, and consequently the incidence of age-related diseases such as heart disease, cancer, and neurodegenerative diseases, is projected to increase considerably in the coming decades. Findings from model organisms have revealed that aging is a surprisingly plastic process that can be manipulated by both genetic and environmental factors. Here we review a broad range of findings in model organisms, from environmental to genetic manipulations of aging, with a focus on those with underlying gene-environment interactions with potential for drug discovery and development. One well-studied dietary manipulation of aging is caloric restriction, which consists of restricting the food intake of organisms without triggering malnutrition and has been shown to retard aging in model organisms. Caloric restriction is already being used as a paradigm for developing compounds that mimic its life-extension effects and might therefore have therapeutic value. The potential for further advances in this field is immense; hundreds of genes in several pathways have recently emerged as regulators of aging and caloric restriction in model organisms. Some of these genes, such as IGF1R and FOXO3, have also been associated with human longevity in genetic association studies. The parallel emergence of network approaches offers prospects to develop multitarget drugs and combinatorial therapies. Understanding how the environment modulates aging-related genes may lead to human applications and disease therapies through diet, lifestyle, or pharmacological interventions. Unlocking the capacity to manipulate human aging would result in unprecedented health benefits.

Abstract: Understanding how each individual's genetics and physiology influences pharmaceutical response is crucial to the realization of personalized medicine and the discovery and validation of pharmacogenomic biomarkers is key to its success. However, integration of genotype and phenotype knowledge in medical information systems remains a critical challenge. The inability to easily and accurately integrate the results of biomolecular studies with patients' medical records and clinical reports prevents us from realizing the full potential of pharmacogenomic knowledge for both drug development and clinical practice. Herein, we describe approaches using Semantic Web technologies, in which pharmacogenomic knowledge relevant to drug development and medical decision support is represented in such a way that it can be efficiently accessed both by software and human experts. We suggest that this approach increases the utility of data, and that such computational technologies will become an essential part of personalized medicine, alongside diagnostics and pharmaceutical products.

Abstract: DNAtraffic (http://dnatraffic.ibb.waw.pl/) is dedicated to be a unique comprehensive and richly annotated database of genome dynamics during the cell life. It contains extensive data on the nomenclature, ontology, structure and function of proteins related to the DNA integrity mechanisms such as chromatin remodeling, histone modifications, DNA repair and damage response from eight organisms: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Escherichia coli and Arabidopsis thaliana. DNAtraffic contains comprehensive information on the diseases related to the assembled human proteins. DNAtraffic is richly annotated in the systemic information on the nomenclature, chemistry and structure of DNA damage and their sources, including environmental agents or commonly used drugs targeting nucleic acids and/or proteins involved in the maintenance of genome stability. One of the DNAtraffic database aim is to create the first platform of the combinatorial complexity of DNA network analysis. Database includes illustrations of pathways, damage, proteins and drugs. Since DNAtraffic is designed to cover a broad spectrum of scientific disciplines, it has to be extensively linked to numerous external data sources. Our database represents the result of the manual annotation work aimed at making the DNAtraffic much more useful for a wide range of systems biology applications.

Abstract: Progress in structure determination methods means that the set of experimentally determined 3D structures of proteins in complex with small molecules is growing exponentially. ProtChemSI exploits and extends this useful set of structures by both collecting and annotating the existing data as well as providing models of potential complexes inferred by protein or chemical structure similarity. The database currently includes 7704 proteins from 1803 organisms, 11,324 chemical compounds and 202, 289 complexes including 178,974 predicted. It is publicly available at http://pcidb.russelllab.org.