High-Throughput Computational and Experimental Techniques in Structural Genomics

M. R. Chance
<span title="2004-10-15">2004</span> <i title="Cold Spring Harbor Laboratory"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nwro4atxwbec5pfkpfslaxbdae" style="color: black;">Genome Research</a> </i> &nbsp;
Structural genomics has as its goal the provision of structural information for all possible ORF sequences through a combination of experimental and computational approaches. The access to genome sequences and cloning resources from an ever-widening array of organisms is driving high-throughput structural studies by the New York Structural Genomics Research Consortium. In this report, we outline the progress of the Consortium in establishing its pipeline for structural genomics, and some of the
more &raquo; ... experimental and bioinformatics efforts leading to structural annotation of proteins. The Consortium has established a pipeline for structural biology studies, automated modeling of ORF sequences using solved (template) structures, and a novel high-throughput approach (metallomics) to examining the metal binding to purified protein targets. The Consortium has so far produced 493 purified proteins from >1077 expression vectors. A total of 95 have resulted in crystal structures, and 81 are deposited in the Protein Data Bank (PDB). Comparative modeling of these structures has generated >40,000 structural models. We also initiated a high-throughput metal analysis of the purified proteins; this has determined that 10%-15% of the targets contain a stoichiometric structural or catalytic transition metal atom. The progress of the structural genomics centers in the U.S. and around the world suggests that the goal of providing useful structural information on most all ORF domains will be realized. This projected resource will provide structural biology information important to understanding the function of most proteins of the cell. 6 Corresponding author. E-MAIL mrc@aecom.yu.edu; FAX (718) 430-8587. Article and publication are at http://www.genome.org/cgi/
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