Abstract
Protein–ligand interactions taking place far away from the active site, during ligand binding or release, may determine molecular specificity and activity. However, obtaining information about these interactions with experimental or computational methods remains difficult. The computational tool presented in this article, MoMA-LigPath, is based on a mechanistic representation of the molecular system, considering partial flexibility, and on the application of a robotics-inspired algorithm to explore the conformational space. Such a purely geometric approach, together with the efficiency of the exploration algorithm, enables the simulation of ligand unbinding within short computing time. Ligand unbinding pathways generated by MoMA-LigPath are a first approximation that can provide useful information about protein–ligand interactions. When needed, this approximation can be subsequently refined and analyzed using state-of-the-art energy models and molecular modeling methods. MoMA-LigPath is available at http://moma.laas.fr. The web server is free and open to all users, with no login requirement.
Highlights
In the past, experimental and computational approaches aimed at investigating protein-ligand interactions have mostly focused on the molecular complex, when the ligand is docked in the active site of the protein
Monte-Carlo-based techniques have been proposed for the study of ligandbinding and diffusion [7]. They perform a more computationally-efficient exploration of the conformational space compared with techniques based on molecular dynamics simulations, and do not require additional, artificial forces in the molecular force field to accelerate simulations
This section briefly presents results obtained with MoMALigPath for the hexameric insulin-phenol complex, which is an interesting test system because of the likely existence of multiple pathways for phenol unbinding
Summary
Experimental and computational approaches aimed at investigating protein-ligand interactions have mostly focused on the molecular complex, when the ligand is docked in the active site of the protein. Steered Molecular Dynamics (SMD) [5] and Random Acceleration Molecular Dynamics (RAMD) [6] have become popular techniques for the simulation of ligand (un)binding. Both methods are based on the same principle: the application of an artificial force to accelerate the ligand diffusion inside the protein. Monte-Carlo-based techniques have been proposed for the study of ligand (un)binding and diffusion [7] They perform a more computationally-efficient exploration of the conformational space compared with techniques based on molecular dynamics simulations, and do not require additional, artificial forces in the molecular force field to accelerate simulations.
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