MDexciteR: Enhanced Sampling Molecular Dynamics by Excited Normal Modes or Principal Components Obtained from Experiments - Université Paris-Saclay
Article Dans Une Revue Journal of Chemical Theory and Computation Année : 2023

MDexciteR: Enhanced Sampling Molecular Dynamics by Excited Normal Modes or Principal Components Obtained from Experiments

Résumé

Molecular dynamics with excited normal modes (MDeNM) is an enhanced sampling method for exploring conformational changes in proteins with minimal biases. The excitation corresponds to injecting kinetic energy along normal modes describing intrinsic collective motions. Herein, we developed a new automated open-source implementation, MDexciteR (https://github.com/mcosta27/MDexciteR), enabling the integration of MDeNM with two commonly used simulation programs with GPU support. Second, we generalized the method to include the excitation of principal components calculated from experimental ensembles. Finally, we evaluated whether the use of coarse-grained normal modes calculated with elastic network representations preserved the performance and accuracy of the method. The advantages and limitations of these new approaches are discussed based on results obtained for three different protein test cases: two globular and a protein/membrane system.
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Dates et versions

hal-04277555 , version 1 (09-11-2023)

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Mauricio Costa, Paulo R Batista, Antoniel Gomes, Leonardo S Bastos, Maxime Louet, et al.. MDexciteR: Enhanced Sampling Molecular Dynamics by Excited Normal Modes or Principal Components Obtained from Experiments. Journal of Chemical Theory and Computation, 2023, 19 (2), pp.412-425. ⟨10.1021/acs.jctc.2c00599⟩. ⟨hal-04277555⟩
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