Capturing Protein-Ligand Recognition Pathways in Coarse-Grained Simulation

The Journal of Physical Chemistry Letters
Bhupendra R. Dandekar, Jagannath Mondal

Abstract

Protein-ligand recognition is dynamic and complex. A key approach in deciphering the mechanism underlying the recognition process is to capture the kinetic process of the ligand in its act of binding to its designated protein cavity. Toward this end, ultralong all-atom molecular dynamics simulation has recently emerged as a popular method of choice because of its ability to record these events at high spatial and temporal resolution. However, success via this route comes at an exorbitant computational cost. Herein, we demonstrate that coarse-grained models of the protein, when systematically optimized to maintain its tertiary fold, can capture the complete process of spontaneous protein-ligand binding from bulk media to the cavity at crystallographic precision and within wall clock time that is orders of magnitude shorter than that of all-atom simulations. The exhaustive sampling of ligand exploration in protein and solvent, harnessed by coarse-grained simulation, leads to elucidation of new ligand recognition pathways and discovery of non-native binding poses.

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Citations

Feb 9, 2021·The Journal of Physical Chemistry Letters·Khandekar Jishan Bari, Dube Dheeraj Prakashchand
Mar 7, 2021·Biophysical Journal·Bhupendra R DandekarJagannath Mondal
Apr 16, 2021·Frontiers in Molecular Biosciences·Paulo C T SouzaLuca Monticelli
Jul 9, 2021·Current Research in Structural Biology·Ariane Nunes-AlvesRebecca C Wade
Jan 1, 2021·The Journal of Physical Chemistry Letters·Navjeet Ahalawat, Jagannath Mondal
Sep 24, 2020·Journal of Chemical Information and Modeling·Joshua W WilkersonThomas A Knotts

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