SDU: A Semidefinite Programming-Based Underestimation Method for Stochastic Global Optimization in Protein Docking. Academic Article

abstract

• This paper introduces a new stochastic global optimization method targeting protein-protein docking problems, an important class of problems in computational structural biology. The method is based on finding general convex quadratic underestimators to the binding energy function that is funnel-like. Finding the optimum underestimator requires solving a semidefinite programming problem, hence the name semidefinite programming-based underestimation (SDU). The underestimator is used to bias sampling in the search region. It is established that under appropriate conditions SDU locates the global energy minimum with probability approaching one as the sample size grows. A detailed comparison of SDU with a related method of convex global underestimator (CGU), and computational results for protein-protein docking problems are provided.

authors

• Shen, Yang

published proceedings

• IEEE Trans Automat Contr

author list (cited authors)

• Paschalidis, I. C., Shen, Y., Vakili, P., & Vajda, S.

citation count

• 19

complete list of authors

• Paschalidis, Ioannis Ch||Shen, Yang||Vakili, Pirooz||Vajda, Sandor

publication date

• April 2007

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Automatic Control  Journal

keywords

• 40 Engineering
• 4007 Control Engineering, Mechatronics And Robotics

PubMed Central ID

• 19759849

Digital Object Identifier (DOI)

• 10.1109/TAC.2007.894518

start page

• 664

end page

• 676

volume

• 52

issue

• 4

URL

• http://dx.doi.org/10.1109/tac.2007.894518