ABI: A Toolbox for Large-Scale Analysis of Structural Molecular Data

William Marsh Rice University, Houston TX

Investigators

Abstract

A Toolbox for Large-Scale Analysis of Structural Molecular Data William Marsh Rice University is awarded a grant to design and implement an extensible and computationally efficient toolbox that integrates sequence information and existing molecular metadata with structural analysis of proteins. One of the most challenging tasks in modern biology is the interpretation of the massive amounts of data becoming available through recent genomics, proteomics and related advances. Proteins are the cell's worker molecules, so there is a tremendous interest to understand how they behave, relate to each other, and how they regulate physiological processes. At the core of the toolbox is a fast and scalable substructure matching method that finds correspondences of a three-dimensional set of atoms (a motif) to a set of protein structures. The goal is to provide biologists with a versatile 'Swiss army knife' for probing the relationship between protein structure and function. The toolbox will be built in a way that it will automatically draw metadata information from relevant online databases in order to be continuously up-to-date. The output will not only report and visualize the results but link to online sources for further evaluation and analysis. The broader impacts of this project will strengthen biological infrastructure by providing a versatile computational toolbox for the analysis of protein structure and function. The toolbox will be widely disseminated (1) as a web service, (2) as a downloadable package with a command line and Python module interface, and (3) as a plug-in for Chimera, a popular, free molecular modeling program. Besides working with their collaborators, the PIs will reach out to interest groups and related conferences for building a community of users for the proposed tool and encourage the contribution of novel workflows by the scientific community. Students involved in the project will be trained as part of a highly interdisciplinary team, and educational and research activities (through CRA-W, the Computer Research Association's Committee on the Status of Women in Computing Research) for undergraduate students are planned.