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Optimizing an Empirical Scoring Function for Transmembrane Protein Structure Determination

Computational Sciences and Mathematics Research Department, Sandia National Laboratories, PO Box 969 MS 9159, Livermore, California 94551-0969, USA
Computational Sciences and Mathematics Research Department, Sandia National Laboratories, PO Box 969 MS 9159, Livermore, California 94551-0969, USA
Biosystems Research Department, Sandia National Laboratories, PO Box 969 MS 9951, Livermore, California 94551-0969, USA
Biosystems Research Department, Sandia National Laboratories, PO Box 969 MS 9951, Livermore, California 94551-0969, USA
gagray{at}sandia.gov
tgkolda{at}sandia.gov
klsale{at}sandia.gov
mmyoung{at}sandia.gov

We examine the problem of transmembrane protein structure determination. Like many questions that arise in biological research, this problem cannot be addressed generally by traditional laboratory experimentation alone. Instead, an approach that integrates experiment and computation is required. We formulate the transmembrane protein structure determination problem as a bound-constrained optimization problem using a special empirical scoring function, called Bundler, as the objective function. In this paper, we describe the optimization problem and its mathematical properties, and we examine results obtained using two different derivative-free optimization algorithms.

Key words: optimization; computational biology; nonlinear programming; parallel algorithm; protein structure; Bundler scoring function
History: received June 2003; revised February 2004; accepted May 2004.