Biochemistry, Biophysics and Molecular Biology, Roy J. Carver Department of, Baker Center for Bioinformatics and Biological Statistics
Journal or Book Title
Proteins: Structure, Function, and Bioinformatics
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.
Schuyler, Adam D.; Jernigan, Robert L.; Qasba, Pradman K.; Ramakrishnan, Boopathy; and Chirikjian, Gregory S., "Iterative cluster-NMA (icNMA): A tool for generating conformational transitions in proteins" (2009). Biochemistry, Biophysics and Molecular Biology Publications. 180.