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Determining protein structures from NOESY distance constraints by semidefinite programming.

ABSTRACT: 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.

SUBMITTER: Alipanahi B

PROVIDER: S-EPMC3619149 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Determining protein structures from NOESY distance constraints by semidefinite programming.

Alipanahi Babak B Krislock Nathan N Ghodsi Ali A Wolkowicz Henry H Donaldson Logan L Li Ming M

Journal of computational biology : a journal of computational molecular cell biology 20121031 4

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 na ...[more]

PMID: 23113706

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Project description:BackgroundTwo of the mostly unsolved but increasingly urgent problems for modern biologists are a) to quickly and easily analyse protein structures and b) to comprehensively mine the wealth of information, which is distributed along with the 3D co-ordinates by the Protein Data Bank (PDB). Tools which address this issue need to be highly flexible and powerful but at the same time must be freely available and easy to learn.ResultsWe present MolTalk, an elaborate programming language, which consists of the programming library libmoltalk implemented in Objective-C and the Smalltalk-based interpreter MolTalk. MolTalk combines the advantages of an easy to learn and programmable procedural scripting with the flexibility and power of a full programming language. An overview of currently available applications of MolTalk is given and with PDBChainSaw one such application is described in more detail. PDBChainSaw is a MolTalk-based parser and information extraction utility of PDB files. Weekly updates of the PDB are synchronised with PDBChainSaw and are available for free download from the MolTalk project page http://www.moltalk.org following the link to PDBChainSaw. For each chain in a protein structure, PDBChainSaw extracts the sequence from its co-ordinates and provides additional information from the PDB-file header section, such as scientific organism, compound name, and EC code.ConclusionMolTalk provides a rich set of methods to analyse and even modify experimentally determined or modelled protein structures. These methods vary in complexity and are thus suitable for beginners and advanced programmers alike. We envision MolTalk to be most valuable in the following applications:1) To analyse protein structures repetitively in large-scale, i.e. to benchmark protein structure prediction methods or to evaluate structural models. The quality of the resulting 3D-models can be assessed by e.g. calculating a Ramachandran-Sasisekharan plot.2) To quickly retrieve information for (a limited number of) macro-molecular structures, i.e. H-bonds, salt bridges, contacts between amino acids and ligands or at the interface between two chains.3) To programme more complex structural bioinformatics software and to implement demanding algorithms through its portability to Objective-C, e.g. iMolTalk.4) To be used as a front end to databases, e.g. PDBChainSaw.

Dataset Information

Determining protein structures from NOESY distance constraints by semidefinite programming.

Publications

Determining protein structures from NOESY distance constraints by semidefinite programming.

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