Deterministic global optimization and torsion angle dynamics for molecular structure prediction

The problem of protein folding has become the subject of intense theoretical and experimental study over the past few decades. This work presents a new method for protein structure prediction using distance and dihedral angle restraints derived from NMR data. Both the formulation and solution approa...

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Published inComputers & chemical engineering Vol. 24; no. 2; pp. 1761 - 1766
Main Authors Klepeis, J.L., Floudas, C.A.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 15.07.2000
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ISSN0098-1354
1873-4375
DOI10.1016/S0098-1354(00)00461-0

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Abstract The problem of protein folding has become the subject of intense theoretical and experimental study over the past few decades. This work presents a new method for protein structure prediction using distance and dihedral angle restraints derived from NMR data. Both the formulation and solution approach differ substantially from traditional molecular structure prediction techniques. The traditional formulation is recast as a constrained global optimization problem whose solution is obtained through the use of the αBB algorithm, a deterministic global optimizationa approach suitable for nonconvex constrained problems. To enhance the efficiency of this method, torsion angle dynamics is introduced as an integral part of the solution approach. The proposed algorithm is tested on the Compstatin structure prediction problem.
AbstractList The problem of protein folding has become the subject of intense theoretical and experimental study over the past few decades. This work presents a new method for protein structure prediction using distance and dihedral angle restraints derived from NMR data. Both the formulation and solution approach differ substantially from traditional molecular structure prediction techniques. The traditional formulation is recast as a constrained global optimization problem whose solution is obtained through the use of the αBB algorithm, a deterministic global optimizationa approach suitable for nonconvex constrained problems. To enhance the efficiency of this method, torsion angle dynamics is introduced as an integral part of the solution approach. The proposed algorithm is tested on the Compstatin structure prediction problem.
Author Klepeis, J.L.
Floudas, C.A.
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  email: floudas@titan.princeton.edu
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Keywords Global optimization
Torsion angle dynamics
Molecular structure prediction
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Snippet The problem of protein folding has become the subject of intense theoretical and experimental study over the past few decades. This work presents a new method...
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SubjectTerms Global optimization
Molecular structure prediction
Torsion angle dynamics
Title Deterministic global optimization and torsion angle dynamics for molecular structure prediction
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