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PMID: 8464064 Published · ppublish English Comparative Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Backbone-dependent rotamer library for proteins. Application to side-chain prediction.

Journal of molecular biology ·Vol. 230 ·No. 2 ·1993-03-20 ·Pages 543-74

Dunbrack RL, Karplus M

Abstract

A backbone-dependent rotamer library for amino acid side-chains is developed and used for constructing protein side-chain conformations from the main-chain co-ordinates. The rotamer library is obtained from 132 protein chains in the Brookhaven Protein Database. A grid of 20 degrees by 20 degrees blocks for the main-chain angles phi, psi is used in the rotamer library. Significant correlations are found between side-chain dihedral angle probabilities and backbone phi, psi values. These probabilities are used to place the side-chains on the known backbone in test applications for six proteins for which high-resolution crystal structures are available. A minimization scheme is used to reorient side-chains that conflict with the backbone or other side-chains after the initial placement. The initial placement yields 59% of both chi 1 and chi 2 values in the correct position (to within 40 degrees) for thermolysin to 81% for crambin. After refinement the values range from 61% (lysozyme) to 89% (crambin). It is evident from the results that a single protein does not adequately test a prediction scheme. The computation time required by the method scales linearly with the number of side-chains. An initial prediction from the library takes only a few seconds of computer time, while the iterative refinement takes on the order of hours. The method is automated and can easily be applied to aid experimental side-chain determinations and homology modeling. The high degree of correlation between backbone and side-chain conformations may introduce a simplification in the protein folding process by reducing the available conformational space.

MeSH Terms
Amino Acid Sequence Databases, Factual Enzymes/chemistry Models, Molecular Molecular Sequence Data Probability Protein Conformation Proteins/chemistry Software X-Ray Diffraction/methods
Chemicals
Enzymes Proteins
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Dunbrack R L
Department of Chemistry, Harvard University, Cambridge, MA 02138.
Karplus M
Article Info
Journal
Journal of molecular biology
Abbr.
J Mol Biol
ISSN
0022-2836
Published
1993-03-20
Pages
543-74
Language
English
Region
England
NLM ID
2985088R
Subset
IM
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