A Computational Capability for Fast and Reliable Characterization of Protein Complexes

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Protein-protein interactions are at the heart of biological activities. They constitute the basic components of many biological processes such as signal transduction, cell-cycle control, metabolism, and general cellular machines. Characterization of protein-protein interactions in protein complexes in a cell, in a systematic manner, represents a highly challenging and important problem to functional genomics and proteomics in the post-genome sequencing era. An integrated computational capability for characterization of protein complexes in a cell will be developed, through (a) analyzing mass spectrometry data and chemical cross-linking information and (b) protein docking prediction under geometric constraints derived from these experimental data. Initially this capability will be tested and validated on a selected set of protein complexes from yeast, as a proof of principle. When fully developed, this capability will be used for genome-scale cataloging of protein complexes in yeast (and other genomes in general). The specific aims of this proposed project are: (i) development of improved computational methods for locating and identifying cross-links, particularly inter-molecular ones, from mass spectrometry data; (ii) development of new computational methods for identification of protein complexes and their component proteins, through analysis of cross-linking and other experimental data; (iii) development of new computational methods for data-constrained docking of two proteins that will significantly improve the existing docking methods in both prediction accuracy and application generality; (iv) development of new computational methods for data-constrained multi-party protein docking; and (v) applications of the developed methods to a selected set of protein complexes for their complex structure characterization. The proposed computational capability will significantly improve the ability to interrogate protein-protein interactions in a way not possible before, and open new doors for the emerging fields of functional genomics and proteomics.Investigation of these computational capabilities for characterization of protein complexes will provide a number of opportunities for graduate students and postdoctoral trainees who are interested in moving into the emerging field of computational biology/bioinformatics from other disciplines. A number of postdoctoral trainees will be hired to implement some of the key components of this research, and Ph.D. students will be recruited to work on this project as part of their thesis projects. In addition, a computational biology course will be offered to the graduate students of the joint ORNL/UTK Graduate Program in Genome Science and Technology, in the Fall semester of 2002. Some well-defined but challenging issues encountered in this project will be used as student term projects through this course. The challenging scientific problems to be solved in this project will expose the graduate students and postdoctoral trainees to the core issues of bioinformatics, i.e., intelligent and meaningful interpretation of massive amount of biological data and computational modeling of biological structures/processes, providing an excellent opportunity for hands-on training. New scientific findings through the implementation of this project will be made publicly accessible through journal publications and conference presentations. Computer software to be developed in this project will be made freely available to the academic and government organizations through the Internet. All the biological data generated in this project will be organized as databases, and also be made freely and publicly available through the Internet.