Refining homology models by combining replica-exchange molecular dynamics and statistical potentials

Year
2008
Type(s)
Authors
Zhu, J., Fan, H., Periole, X., Honig, B., Mark, A. E.
Source
Proteins-Structure Function and Bioinformatics 2008 72:1171-1188
Url
http://dx.doi.org/10.1002/prot.22005

 

Abstract

A protocol is presented for the global refinement of homology models of proteins. It combines the advantages of temperature‐based replica‐exchange molecular dynamics (REMD) for conformational sampling and the use of statistical potentials for model selection. The protocol was tested using 21 models. Of these 14 were models of 10 small proteins for which high‐resolution crystal structures were available, the remainder were targets of the recent CASPR exercise. It was found that REMD in combination with currently available force fields could sample near‐native conformational states starting from high‐quality homology models. Conformations in which the backbone RMSD of secondary structure elements (SSE‐RMSD) was lower than the starting value by 0.5–1.0 Å were found for 15 out of the 21 cases (average 0.82 Å). Furthermore, when a simple scoring function consisting of two statistical potentials was used to rank the structures, one or more structures with SSE‐RMSD of at least 0.2 Å lower than the starting value was found among the five best ranked structures in 11 out of the 21 cases. The average improvement in SSE‐RMSD for the best models was 0.42 Å. However, none of the scoring functions tested identified the structures with the lowest SSE‐RMSD as the best models although all identified the native conformation as the one with lowest energy. This suggests that while the proposed protocol proved effective for the refinement of high‐quality models of small proteins scoring functions remain one of the major limiting factors in structure refinement. This and other aspects by which the methodology could be further improved are discussed.

 

Technology Platform

Computational Biology

Research Topics

Protein Structure Prediction