383158 Enhanced Sampling Methods Provide Insights into Macromolecular Interactions As Drug Targets

Wednesday, November 19, 2014: 9:53 AM
212 (Hilton Atlanta)

Biophysical theory, modeling, and simulation techniques rooted in statistical mechanics are playing an increasingly important role in elucidating molecular signatures of cellular processes. Given the large number of degrees-of-freedom in biomolecules, conventional simulation methods remain limited in providing information on conformational statistics, particularly metastable intermediates, at longer time-scales. A challenging biophysical problem is to understand the mechanisms by which small molecule drugs can surprisingly gain access to deeply buried protein cavities thereby deactivating a specific target protein or its interactions with other biomolecules. Interestingly, rare biomolecular events such as slow conformational changes in proteins can potentially play a major in role in facilitating drug access. In this work, we study using atomistic simulations the mechanism of action of a potent inhibitor of the regulators of G-protein signaling (RGS) proteins. Particularly, we report how the dynamical motions of a specific RGS protein (named RGS4) appear to play a critical role in exposing a buried cysteine residue that is required for drug action. The dynamic nature of RGS4 involving large-scale conformational changes in a pair of alpha-helices only became apparent upon use of all-atom explicit-solvent temperature-accelerated molecular dynamics (TAMD) simulations to carry out enhanced conformational sampling of apo-RGS4 structures. Modification of exposed cysteine residue by the drug molecule then prevents restoration of the native-like RGS-fold as well as RGS4/G-alpha interface that is required for functional activity. We also provide NMR chemical-shift data that corroborates predictions from our enhanced sampling simulations. These results have potential implications for understanding how the conformational dynamics among RGS proteins, revealed via novel simulation approaches, may play a key role in inhibitor sensitivity.

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