Enhanced Sampling of Protein Conformational Transitions via Dynamically Optimized Collective Variables
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AbstractProtein conformational transitions often involve many slow degrees of freedom. Their knowledge would give distinctive advantages since it provides chemical and mechanistic insight and accelerates the convergence of enhanced sampling techniques that rely on collective variables. In this study, we implemented a recently developed variational approach to conformational dynamics metadynamics to the conformational transition of the moderate size protein, L99A T4 Lysozyme. In order to find the slow modes of the system we combined data coming from NMR experiments as well as short MD simulations. A Metadynamics simulation based on these information reveals the presence of two intermediate states, at an affordable computational cost.
2018 ◽
2021 ◽
2021 ◽
Vol 118
(44)
◽
pp. e2113533118
2020 ◽
2018 ◽
Vol 15
(2)
◽
pp. 1393-1398
◽
2019 ◽
2020 ◽
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