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Dynamic profile analysis to characterize dynamics-driven allosteric sites in enzymes
We examine the dynamic features of non-trivial allosteric binding sites to elucidate potential drug binding sites. These allosteric sites were previously found to be allosteric after determination of the protein-drug co-crystal structure. After comprehensive search in the Protein Data Bank, we ident...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Biophysical Society of Japan (BSJ)
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5042162/ https://www.ncbi.nlm.nih.gov/pubmed/27924265 http://dx.doi.org/10.2142/biophysico.13.0_117 |
Sumario: | We examine the dynamic features of non-trivial allosteric binding sites to elucidate potential drug binding sites. These allosteric sites were previously found to be allosteric after determination of the protein-drug co-crystal structure. After comprehensive search in the Protein Data Bank, we identify 10 complex structures with allosteric ligands whose structures are very similar to their functional forms. Then, possible pockets on the protein surface are searched as potential ligand binding sites. To mimic ligand binding to the pocket, complex models are generated to fill out each pocket with pseudo ligand blocks consisting of spheres. Normal mode analysis of the elastic network model is performed for the complex models and unbound structures to assess the change of protein dynamics induced by ligand binding. We examine nine profiles to describe the dynamic and positional characteristics of the pockets, and identify the change of fluctuation around the ligand, ΔMSF(bs), as the best profile for distinguishing the allosteric sites from the other sites in 8 structures. These cases should be considered as examples of dynamics-driven allostery, which accompanies significant changes in protein dynamics. ΔMSF(bs) is suggested to be used for the search of potential dynamics-driven allosteric sites in proteins for drug discovery. |
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