J. Comput. Biol. - Determining protein structures from NOESY distance constraints by semidefinite programming.

Tópicos

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Resumo

Contemporary practical methods for protein nuclear magnetic resonance (NMR) structure determination use molecular dynamics coupled with a simulated annealing schedule. The objective of these methods is to minimize the error of deviating from the nuclear overhauser effect (NOE) distance constraints. However, the corresponding objective function is highly nonconvex and, consequently, difficult to optimize. Euclidean distance matrix (EDM) methods based on semidefinite programming (SDP) provide a natural framework for these problems. However, the high complexity of SDP solvers and the often noisy distance constraints provide major challenges to this approach. The main contribution of this article is a new SDP formulation for the EDM approach that overcomes these two difficulties. We model the protein as a set of intersecting two- and three-dimensional cliques. Then, we adapt and extend a technique called semidefinite facial reduction to reduce the SDP problem size to approximately one quarter of the size of the original problem. The reduced SDP problem can be solved approximately 100 times faster, and it is also more resistant to numerical problems from erroneous and inexact distance bounds.

Resumo Limpo

contemporari practic method protein nuclear magnet reson nmr structur determin use molecular dynam coupl simul anneal schedul object method minim error deviat nuclear overhaus effect noe distanc constraint howev correspond object function high nonconvex consequ difficult optim euclidean distanc matrix edm method base semidefinit program sdp provid natur framework problem howev high complex sdp solver often noisi distanc constraint provid major challeng approach main contribut articl new sdp formul edm approach overcom two difficulti model protein set intersect two threedimension cliqu adapt extend techniqu call semidefinit facial reduct reduc sdp problem size approxim one quarter size origin problem reduc sdp problem can solv approxim time faster also resist numer problem erron inexact distanc bound

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