Campus Units

Biochemistry, Biophysics and Molecular Biology, Roy J. Carver Department of, Baker Center for Bioinformatics and Biological Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2-15-2009

Journal or Book Title

Proteins: Structure, Function, and Bioinformatics

Volume

74

Issue

3

First Page

760

Last Page

776

DOI

10.1002/prot.22200

Abstract

Computational models provide insight into the structure-function relationship in proteins. These approaches, especially those based on normal mode analysis, can identify the accessible motion space around a given equilibrium structure. The large magnitude, collective motions identified by these methods are often well aligned with the general direction of the expected conformational transitions. However, these motions cannot realistically be extrapolated beyond the local neighborhood of the starting conformation. In this paper, the icNMA method is presented for traversing the energy landscape from a starting conformation to a desired goal conformation. This is accomplished by allowing the evolving geometry of the intermediate structures to define the local accessible motion space, and thus produce an appropriate displacement. Following the derivation of the icNMA method, a set of sample simulations are performed to probe the robustness of the model. A detailed analysis of β1,4-galactosyltransferase-T1 is also given, to highlight many of the capabilities of icNMA. Remarkably, during the transition, a helix is seen to be extended by an additional turn, emphasizing a new unknown role for secondary structures to absorb slack during transitions. The transition pathway for adenylate kinase, which has been frequently studied in the literature, is also discussed.

Comments

This is the peer reviewed version of the following article: Schuyler, Adam D., Robert L. Jernigan, Pradman K. Qasba, Boopathy Ramakrishnan, and Gregory S. Chirikjian. "Iterative cluster‐NMA: A tool for generating conformational transitions in proteins." Proteins: Structure, Function, and Bioinformatics 74, no. 3 (2009): 760-776. , which has been published in final form at DOI: 10.1002/prot.22200. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.

Copyright Owner

Wiley-Liss, Inc.

Language

en

File Format

application/pdf

Published Version

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