MOPED: Method for optimizing physical energy parameters using decoys
| Autor: | Chaok Seok, John D. Chodera, J. B. Rosen, Ken A. Dill |
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| Rok vydání: | 2002 |
| Předmět: |
Computational model
Protein Conformation Computer science business.industry Gaussian Solvation Computational Biology Proteins General Chemistry Models Theoretical Force field (chemistry) Computational Mathematics Nonlinear system symbols.namesake Present method symbols Artificial intelligence Decoy business Algorithm Algorithms |
| Zdroj: | Journal of Computational Chemistry. 24:89-97 |
| ISSN: | 1096-987X 0192-8651 |
| DOI: | 10.1002/jcc.10124 |
| Popis: | We present a method called MOPED for optimizing energetic and structural parameters in computational models, including all-atom energy functions, when native structures and decoys are given. The present method goes beyond previous approaches in treating energy functions that are nonlinear in the parameters and continuous in the degrees of freedom. We illustrate the method by improving solvation parameters in the energy function EEF1, which consists of the CHARMM19 polar hydrogen force field augmented by a Gaussian solvation term. Although the published parameters for EEF1 correctly discriminate the native from decoys in the decoy sets of Levitt et al., they fail on several of the more difficult decoy sets of Baker et al. MOPED successfully finds improved parameters that allow EEF1 to discriminate native from decoy structures on all protein structures that do not have metals or prosthetic groups. |
| Databáze: | OpenAIRE |
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