Computer simulations aimed at structure prediction of supersecondary motifs in proteins

François Forcellino; Philippe Derreumaux

doi:10.1002/prot.1135

journal article Aug 22, 2001

Computer simulations aimed at structure prediction of supersecondary motifs in proteins

François Forcellino Philippe Derreumaux

Proteins: Structure, Function, and Bioinformatics Vol. 45 No. 2 pp. 159-166 · Wiley

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Abstract

AbstractIt is well established that protein structures are more conserved than protein sequences. One‐third of all known protein structures can be classified into ten protein folds, which themselves are composed mainly of α‐helical hairpin, β hairpin, and βαβ supersecondary structural elements. In this study, we explore the ability of a recent Monte Carlo–based procedure to generate the 3D structures of eight polypeptides that correspond to units of supersecondary structure and three‐stranded antiparallel beta sheet. Starting from extended or misfolded compact conformations, all Monte Carlo simulations show significant success in predicting the native topology using a simplified chain representation and an energy model optimized on other structures. Preliminary results on model peptides from nucleotide binding proteins suggest that this simple protein folding model can help clarify the relation between sequence and topology. Proteins 2001;45:159–166. © 2001 Wiley‐Liss, Inc.

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References

Details

Published: Aug 22, 2001
Vol/Issue: 45(2)
Pages: 159-166
License: View

Authors

Laboratoire de Biochimie Théorique, Institut de Biologie Physico-Chimique (IBPC), UPR9080 CNRS, Université Paris Diderot, Sorbonne Paris Cité, 13 rue Pierre et Marie Curie, 75005 Paris, France; Institut Universitaire de France, 75005 Paris, France

Cite This Article

François Forcellino, Philippe Derreumaux (2001). Computer simulations aimed at structure prediction of supersecondary motifs in proteins. Proteins: Structure, Function, and Bioinformatics, 45(2), 159-166. https://doi.org/10.1002/prot.1135

Computer simulations aimed at structure prediction of supersecondary motifs in proteins

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