title: An in silico algorithm for identifying stabilizing pockets in proteins: test case, the Y220C mutant of the p53 tumor suppressor protein.
abstract: The p53 tumor suppressor protein performs a critical role in stimulating apoptosis and cell cycle arrest in response to oncogenic stress. The function of p53 can be compromised by mutation, leading to increased risk of cancer; approximately 50% of cancers are associated with mutations in the p53 gene, the majority of which are in the core DNA-binding domain. The Y220C mutation of p53, for example, destabilizes the core domain by 4 kcal/mol, leading to rapid denaturation and aggregation. The associated loss of tumor suppressor functionality is associated with approximately 75 000 new cancer cases every year. Destabilized p53 mutants can be 'rescued' and their function restored; binding of a small molecule into a pocket on the surface of mutant p53 can stabilize its wild-type structure and restore its function. Here, we describe an in silico algorithm for identifying potential rescue pockets, including the algorithm's integration with the Dynameomics molecular dynamics data warehouse and the DIVE visual analytics engine. We discuss the results of the application of the method to the Y220C p53 mutant, entailing finding a putative rescue pocket through MD simulations followed by an in silico search for stabilizing ligands that dock into the putative rescue pocket. The top three compounds from this search were tested experimentally and one of them bound in the pocket, as shown by nuclear magnetic resonance, and weakly stabilized the mutant.
authors: Division of Biomedical and Health Informatics, Department of Biomedical Informatics and Medical Education, University of Washington, Box SLU-BIME 358047, 850 Republican St, Building C, Seattle, WA 98109-4714, USA.
authors: Dennis
authors: D
authors: Bromley
authors: MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK.
authors: Matthias R
authors: MR
authors: Bauer
authors: MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK.
authors: Alan R
authors: AR
authors: Fersht
authors: Division of Biomedical and Health Informatics, Department of Biomedical Informatics and Medical Education, University of Washington, Box SLU-BIME 358047, 850 Republican St, Building C, Seattle, WA 98109-4714, USA Department of Bioengineering, University of Washington, Box 355013, Seattle, WA 98195-5013, USA daggett@uw.edu.
authors: Valerie
authors: V
authors: Daggett
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D004247:DNA / Q000378:metabolism; D008024:Ligands; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D009154:Mutation; D000072417:Protein Domains; D055550:Protein Stability; D013696:Temperature; D016159:Tumor Suppressor Protein p53 / Q000737:chemistry* / Q000235:genetics* / Q000378:metabolism
chemical_list: D008024:Ligands; D016159:Tumor Suppressor Protein p53; D004247:DNA
keywords: cancer; docking; drug design; ligand; pharmacophore; small-molecule; visual analytics