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Analysis of protein binding sites by computational solvent mapping.

ABSTRACT: Computational solvent mapping globally samples the surface of target proteins using molecular probes-small molecules or functional groups-to identify potentially favorable binding positions. The method is based on X-ray and NMR screening studies showing that the binding sites of proteins also bind a large variety of fragment-sized molecules. We have developed the multistage mapping algorithm FTMap (available as a server at http://ftmap.bu.edu/ ) based on the fast Fourier transform (FFT) correlation approach. Identifying regions of low free energy rather than individual low energy conformations, FTMap reproduces the available experimental mapping results. Applications to a variety of proteins show that the probes always cluster in important subsites of the binding site, and the amino acid residues that interact with many probes also bind the specific ligands of the protein. The "consensus" sites at which a number of different probes cluster are likely to be "druggable" sites, capable of binding drug-size ligands with high affinity. Due to its sensitivity to conformational changes, the method can also be used for comparing the binding sites in different structures of a protein.

SUBMITTER: Hall DR

PROVIDER: S-EPMC3526383 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Analysis of protein binding sites by computational solvent mapping.

Hall David R DR Kozakov Dima D Vajda Sandor S

Methods in molecular biology (Clifton, N.J.) 20120101

Computational solvent mapping globally samples the surface of target proteins using molecular probes-small molecules or functional groups-to identify potentially favorable binding positions. The method is based on X-ray and NMR screening studies showing that the binding sites of proteins also bind a large variety of fragment-sized molecules. We have developed the multistage mapping algorithm FTMap (available as a server at http://ftmap.bu.edu/ ...[more]

PMID: 22183527

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Project description:BackgroundCyclic AMP receptor protein (CRP), also known as catabolite gene activator protein (CAP), is an important transcriptional regulator widely distributed in many bacteria. The biological processes under the regulation of CRP are highly diverse among different groups of bacterial species. Elucidation of CRP regulons in cyanobacteria will further our understanding of the physiology and ecology of this important group of microorganisms. Previously, CRP has been experimentally studied in only two cyanobacterial strains: Synechocystis sp. PCC 6803 and Anabaena sp. PCC 7120; therefore, a systematic genome-scale study of the potential CRP target genes and binding sites in cyanobacterial genomes is urgently needed.ResultsWe have predicted and analyzed the CRP binding sites and regulons in 12 sequenced cyanobacterial genomes using a highly effective cis-regulatory binding site scanning algorithm. Our results show that cyanobacterial CRP binding sites are very similar to those in E. coli; however, the regulons are very different from that of E. coli. Furthermore, CRP regulons in different cyanobacterial species/ecotypes are also highly diversified, ranging from photosynthesis, carbon fixation and nitrogen assimilation, to chemotaxis and signal transduction. In addition, our prediction indicates that crp genes in modern cyanobacteria are likely inherited from a common ancestral gene in their last common ancestor, and have adapted various cellular functions in different environments, while some cyanobacteria lost their crp genes as well as CRP binding sites during the course of evolution.ConclusionThe CRP regulons in cyanobacteria are highly diversified, probably as a result of divergent evolution to adapt to various ecological niches. Cyanobacterial CRPs may function as lineage-specific regulators participating in various cellular processes, and are important in some lineages. However, they are dispensable in some other lineages. The loss of CRPs in these species leads to the rapid loss of their binding sites in the genomes.

Dataset Information

Analysis of protein binding sites by computational solvent mapping.

Publications

Analysis of protein binding sites by computational solvent mapping.

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