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Zarbafian S, Moghadasi M, Roshandelpoor A, Nan F, Li K, Vakli P, Vajda S, Kozakov D, Paschalidis IC. Protein docking refinement by convex underestimation in the low-dimensional subspace of encounter complexes. Sci Rep 2018; 8:5896. [PMID: 29650980 PMCID: PMC5955889 DOI: 10.1038/s41598-018-23982-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 03/21/2018] [Indexed: 01/18/2023] Open
Abstract
We propose a novel stochastic global optimization algorithm with applications to the refinement stage of protein docking prediction methods. Our approach can process conformations sampled from multiple clusters, each roughly corresponding to a different binding energy funnel. These clusters are obtained using a density-based clustering method. In each cluster, we identify a smooth “permissive” subspace which avoids high-energy barriers and then underestimate the binding energy function using general convex polynomials in this subspace. We use the underestimator to bias sampling towards its global minimum. Sampling and subspace underestimation are repeated several times and the conformations sampled at the last iteration form a refined ensemble. We report computational results on a comprehensive benchmark of 224 protein complexes, establishing that our refined ensemble significantly improves the quality of the conformations of the original set given to the algorithm. We also devise a method to enhance the ensemble from which near-native models are selected.
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Affiliation(s)
- Shahrooz Zarbafian
- Department of Mechanical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Mohammad Moghadasi
- Division of Systems Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Athar Roshandelpoor
- Division of Systems Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Feng Nan
- Division of Systems Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Keyong Li
- Division of Systems Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Pirooz Vakli
- Division of Systems Engineering, Boston University, Boston, Massachusetts, United States of America.,Department of Mechanical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America.
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics and Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, United States of America.
| | - Ioannis Ch Paschalidis
- Division of Systems Engineering, Boston University, Boston, Massachusetts, United States of America. .,Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America. .,Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts, United States of America. .,8 Saint Mary's St., Boston, MA, 02215, United States of America.
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