Abstract
To incorporate protein polarization effects within a protein combinatorial optimization framework, we decompose the polarizable force field AMOEBA into low order terms. Including terms up to the third-order provides a fair approximation to the full energy while maintaining tractability. We represent the polarizable packing problem for protein G as a hypergraph and solve for optimal rotamers with the FASTER combinatorial optimization algorithm. These approximate energy models can be improved to high accuracy [root mean square deviation (rmsd) < 1 kJ mol -1] via ridge regression. The resulting trained approximations are used to efficiently identify new, low-energy solutions. The approach is general and should allow combinatorial optimization of other many-body problems. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011 Copyright © 2011 Wiley Periodicals, Inc.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1334-1344 |
| Number of pages | 11 |
| Journal | Journal of Computational Chemistry |
| Volume | 32 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jan 24 2011 |
| Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledged KAUST grant number(s): KUS-F1-028-03
Acknowledgements: Contract/grant sponsor: King Abdullah University of Science and Technology (KAUST); contract/grant numbers: KUS-F1-028-03The authors thank Frances H. Arnold for support. The authors thank Phillip A. Romero, Gevorg Grigoryan, and an anonymous reviewer for useful suggestions. A.H.N. was supported by the Caltech Summer Undergraduate Research Fellowship program (SURF).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.