Improving ligand transport trajectory within flexible receptor in CaverDock
| Authors | |
|---|---|
| Year of publication | 2022 |
| Type | Article in Proceedings |
| Conference | SAC '22: Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing |
| MU Faculty or unit | |
| Citation | |
| web | https://dl.acm.org/doi/10.1145/3477314.3506988 |
| Doi | http://dx.doi.org/10.1145/3477314.3506988 |
| Keywords | CaverDock; ligand transport; flexible receptor; molecular docking; search heuristic; continuous space search |
| Description | The receptor-ligand interactions are an important part of many biologically relevant processes. The small ligand molecule needs to pass via a tunnel into a receptor before the interaction of interest begins. Both receptor-ligand interaction and ligand pathway need to be studied. CaverDock is a computational tool that simulates the transport of the ligand in a tunnel. However, in its first version, CaverDock allowed only limited flexibility of the receptor, biasing the measured energy of ligand transportation. In this paper, we introduce two essential extensions to CaverDock. First, we combine its force field with AMBER, which allows to relax receptor’s geometry in tunnel bottlenecks. Second, we improve CaverDock heuristics for ligand trajectory search to obtain multiple variants of ligand trajectories, ideally with lower energy compared to the result of CaverDock 1.0. We experimentally demonstrate that the new heuristic is superior to the original one and that the receptor relaxation improves precision of CaverDock results. |
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