The HIVToolbox 2 web system integrates sequence, structure, function and mutation analysis.

There is enormous interest in studying HIV pathogenesis for improving the treatment of patients with HIV infection. HIV infection has become one of the best-studied systems for understanding how a virus can hijack a cell. To help facilitate discovery, we previously built HIVToolbox, a web system for visual data mining. The original HIVToolbox integrated information for HIV protein sequence, structure, functional sites, and sequence conservation. This web system has been used for almost 40,000 searches. We report improvements to HIVToolbox including new functions and workflows, data updates, and updates for ease of use. HIVToolbox2, is an improvement over HIVToolbox with new functions. HIVToolbox2 has new functionalities focused on HIV pathogenesis including drug-binding sites, drug-resistance mutations, and immune epitopes. The integrated, interactive view enables visual mining to generate hypotheses that are not readily revealed by other approaches. Most HIV proteins form multimers, and there are posttranslational modification and protein-protein interaction sites at many of these multimerization interfaces. Analysis of protease drug binding sites reveals an anatomy of drug resistance with different types of drug-resistance mutations regionally localized on the surface of protease. Some of these drug-resistance mutations have a high prevalence in specific HIV-1 M subtypes. Finally, consolidation of Tat functional sites reveals a hotspot region where there appear to be 30 interactions or posttranslational modifications. A cursory analysis with HIVToolbox2 has helped to identify several global patterns for HIV proteins. An initial analysis with this tool identifies homomultimerization of almost all HIV proteins, functional sites that overlap with multimerization sites, a global drug resistance anatomy for HIV protease, and specific distributions of some DRMs in specific HIV M subtypes. HIVToolbox2 is an open-access web application available at [http://hivtoolbox2.bio-toolkit.com].

The Geogenomic Mutational Atlas of Pathogens (GoMAP) web system.

We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼ 502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/

Secondary structure, a missing component of sequence-based minimotif definitions.

Minimotifs are short contiguous segments of proteins that have a known biological function. The hundreds of thousands of minimotifs discovered thus far are an important part of the theoretical understanding of the specificity of protein-protein interactions, posttranslational modifications, and signal transduction that occur in cells. However, a longstanding problem is that the different abstractions of the sequence definitions do not accurately capture the specificity, despite decades of effort by many labs. We present evidence that structure is an essential component of minimotif specificity, yet is not used in minimotif definitions. Our analysis of several known minimotifs as case studies, analysis of occurrences of minimotifs in structured and disordered regions of proteins, and review of the literature support a new model for minimotif definitions that includes sequence, structure, and function.

Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences.

Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins and causes of disease.