Predicting ligand binding poses for low-resolution membrane protein models: Perspectives from multiscale simulations

Schneider, Jakob; Giorgetti, Alejandro; Alfonso-Prieto, Mercedes; Carloni, Paolo; Musiani, Francesco; Korshunova, Ksenia

doi:10.1016/j.bbrc.2018.01.160

Journal Article

FZJ-2018-02179

Predicting ligand binding poses for low-resolution membrane protein models: Perspectives from multiscale simulations

Schneider, J.FZJ*RWTH* ; Korshunova, K.FZJ*RWTH* ; Musiani, F.Extern* ; Alfonso-Prieto, M. (Corresponding author)FZJ* ; Giorgetti, A.FZJ* ; Carloni, P. (Corresponding author)FZJ*RWTH*

2018
Academic Press Orlando, Fla.

Biochemical and biophysical research communications 498(2), 366 - 374 (2018) [10.1016/j.bbrc.2018.01.160] special issue: "Multiscale Modeling"

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Please use a persistent id in citations: http://hdl.handle.net/2128/19158 doi:10.1016/j.bbrc.2018.01.160

Abstract: Membrane receptors constitute major targets for pharmaceutical intervention. Drug design efforts rely on the identification of ligand binding poses. However, the limited experimental structural information available may make this extremely challenging, especially when only low-resolution homology models are accessible. In these cases, the predictions may be improved by molecular dynamics simulation approaches. Here we review recent developments of multiscale, hybrid molecular mechanics/coarse-grained (MM/CG) methods applied to membrane proteins. In particular, we focus on our in-house MM/CG approach. It is especially tailored for G-protein coupled receptors, the largest membrane receptor family in humans. We show that our MM/CG approach is able to capture the atomistic details of the receptor/ligand binding interactions, while keeping the computational cost low by representing the protein frame and the membrane environment in a highly simplified manner. We close this review by discussing ongoing improvements and challenges of the current implementation of our MM/CG code

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