Literature DB >> 14499612

Identification of substrate binding sites in enzymes by computational solvent mapping.

Michael Silberstein1, Sheldon Dennis, Lawrence Brown, Tamas Kortvelyesi, Karl Clodfelter, Sandor Vajda.   

Abstract

Enzyme structures determined in organic solvents show that most organic molecules cluster in the active site, delineating the binding pocket. We have developed algorithms to perform solvent mapping computationally, rather than experimentally, by placing molecular probes (small molecules or functional groups) on a protein surface, and finding the regions with the most favorable binding free energy. The method then finds the consensus site that binds the highest number of different probes. The probe-protein interactions at this site are compared to the intermolecular interactions seen in the known complexes of the enzyme with various ligands (substrate analogs, products, and inhibitors). We have mapped thermolysin, for which experimental mapping results are also available, and six further enzymes that have no experimental mapping data, but whose binding sites are well characterized. With the exception of haloalkane dehalogenase, which binds very small substrates in a narrow channel, the consensus site found by the mapping is always a major subsite of the substrate-binding site. Furthermore, the probes at this location form hydrogen bonds and non-bonded interactions with the same residues that interact with the specific ligands of the enzyme. Thus, once the structure of an enzyme is known, computational solvent mapping can provide detailed and reliable information on its substrate-binding site. Calculations on ligand-bound and apo structures of enzymes show that the mapping results are not very sensitive to moderate variations in the protein coordinates.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 14499612     DOI: 10.1016/j.jmb.2003.08.019

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  27 in total

1.  Domain motion and interdomain hot spots in a multidomain enzyme.

Authors:  Gwo-Yu Chuang; Ritcha Mehra-Chaudhary; Chi-Ho Ngan; Brandon S Zerbe; Dima Kozakov; Sandor Vajda; Lesa J Beamer
Journal:  Protein Sci       Date:  2010-09       Impact factor: 6.725

2.  Relationship between hot spot residues and ligand binding hot spots in protein-protein interfaces.

Authors:  Brandon S Zerbe; David R Hall; Sandor Vajda; Adrian Whitty; Dima Kozakov
Journal:  J Chem Inf Model       Date:  2012-07-24       Impact factor: 4.956

3.  Optimal clustering for detecting near-native conformations in protein docking.

Authors:  Dima Kozakov; Karl H Clodfelter; Sandor Vajda; Carlos J Camacho
Journal:  Biophys J       Date:  2005-05-20       Impact factor: 4.033

4.  Localization of binding sites in protein structures by optimization of a composite scoring function.

Authors:  Andrea Rossi; Marc A Marti-Renom; Andrej Sali
Journal:  Protein Sci       Date:  2006-09-08       Impact factor: 6.725

5.  Enhanced performance in prediction of protein active sites with THEMATICS and support vector machines.

Authors:  Wenxu Tong; Ronald J Williams; Ying Wei; Leonel F Murga; Jaeju Ko; Mary Jo Ondrechen
Journal:  Protein Sci       Date:  2007-12-20       Impact factor: 6.725

Review 6.  The multi-copy simultaneous search methodology: a fundamental tool for structure-based drug design.

Authors:  Christian R Schubert; Collin M Stultz
Journal:  J Comput Aided Mol Des       Date:  2009-06-09       Impact factor: 3.686

7.  Comparison of structure-based and threading-based approaches to protein functional annotation.

Authors:  Michal Brylinski; Jeffrey Skolnick
Journal:  Proteins       Date:  2010-01

8.  The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins.

Authors:  Dima Kozakov; Laurie E Grove; David R Hall; Tanggis Bohnuud; Scott E Mottarella; Lingqi Luo; Bing Xia; Dmitri Beglov; Sandor Vajda
Journal:  Nat Protoc       Date:  2015-04-09       Impact factor: 13.491

9.  Fragment-based identification of druggable 'hot spots' of proteins using Fourier domain correlation techniques.

Authors:  Ryan Brenke; Dima Kozakov; Gwo-Yu Chuang; Dmitri Beglov; David Hall; Melissa R Landon; Carla Mattos; Sandor Vajda
Journal:  Bioinformatics       Date:  2009-01-28       Impact factor: 6.937

10.  Structural motifs recurring in different folds recognize the same ligand fragments.

Authors:  Gabriele Ausiello; Pier Federico Gherardini; Elena Gatti; Ottaviano Incani; Manuela Helmer-Citterich
Journal:  BMC Bioinformatics       Date:  2009-06-15       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.