Computational Techniques for Analytical Chemistry and Bioanalysis
Chapter 7: Bridging the Gap Between Atomistic Molecular Dynamics Simulations and Wet-lab Experimental Techniques: Applications to Membrane Proteins
Published:08 Dec 2020
Special Collection: 2020 ebook collection
Lucie Delemotte, 2020. "Bridging the Gap Between Atomistic Molecular Dynamics Simulations and Wet-lab Experimental Techniques: Applications to Membrane Proteins", Computational Techniques for Analytical Chemistry and Bioanalysis, Philippe B Wilson, Martin Grootveld
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Molecular dynamics (MD) simulations provide atomistic insights into not only the structure, but also the dynamics and ensemble properties of (bio-)molecular systems, hence providing a direct link to functional characterization using wet-lab experiments. The models, algorithms and hardware needed to conduct MD simulations have matured, meaning that reliable estimates of ensemble properties can now be obtained. However, the choice of model and protocol is non-trivial and cannot be fully automated yet, therefore an understanding of the models, the algorithms and the insights that can be obtained, and of how they can be combined with the output of other techniques, is necessary. This chapter provides a description of the MD algorithm, including extensions of the methodology to generate conformational ensembles representing functional states. The insights that MD simulations can provide into membrane protein functions are then illustrated using case studies. They are classified according to whether they provide testable hypotheses, provide molecular-level interpretation of experimental observables, or they exploit experimental data to drive the sampling of simulations towards biological timescales.