Global optimization in protein docking using clustering, underestimation and semidefinite programming

Roummel F. Marcia; Julie C. Mitchell; Stephen J. Wright

doi:10.1080/00207170701203756

Global optimization in protein docking using clustering, underestimation and semidefinite programming

Roummel F. Marcia, Julie C. Mitchell, Stephen J. Wright

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

The underestimation of data points by a convex quadratic function is a useful tool for approximating the location of the global minima of potential energy functions that arise in protein-ligand docking problems. Determining the parameters that define the underestimator can be formulated as a convex quadratically constrained quadratic program and solved efficiently using algorithms for semidefinite programming (SDP). In this paper, we formulate and solve the underestimation problem using SDP and present numerical results for active site prediction in protein docking.

Original language	English
Pages (from-to)	803-811
Number of pages	9
Journal	Optimization Methods and Software
Volume	22
Issue number	5
DOIs	https://doi.org/10.1080/00207170701203756
State	Published - Oct 2007
Externally published	Yes

Funding

The authors would like to thank Susan Lindsey and Erick Butzlaff for their contributions to DoME. This work was supported by the Department of Energy Grant DE-FG03-01ER25497 and the National Library of Medicine Training Grant 5T15LM007359-03.

Funders	Funder number
U.S. Department of Energy	DE-FG03-01ER25497
U.S. National Library of Medicine	5T15LM007359-03

Keywords

Convex underestimation
Global optimization
Protein docking
Semidefinite programming

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10.1080/00207170701203756

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abstract = "The underestimation of data points by a convex quadratic function is a useful tool for approximating the location of the global minima of potential energy functions that arise in protein-ligand docking problems. Determining the parameters that define the underestimator can be formulated as a convex quadratically constrained quadratic program and solved efficiently using algorithms for semidefinite programming (SDP). In this paper, we formulate and solve the underestimation problem using SDP and present numerical results for active site prediction in protein docking.",

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Global optimization in protein docking using clustering, underestimation and semidefinite programming

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Keywords

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