SHAMAN: A mixed solvent molecular dynamics protocol to identify small-molecules binding sites on RNA structural ensembles.

Abstract

The majority of in silico binding site identification tools for computational drug design employs static structures of the target. However, such structures do not contain information about transient opening of cavities that could act as binding sites, a phenomenon often enhanced by the presence of a ligand. To address this limitation, a technique that makes use of Molecular Dynamics (MD) simulations of the target with selected co-solvent probes was introduced. Free-energy grids built from the probes occupancy provide an effective description of transiently formed pockets not observed in the resolved conformation. This framework was applied only very recently to highly flexible RNA molecules. Here, we present a protocol to detect binding sites on RNAs, called SHAdow mixed-solvent MetAdyNamics (SHAMAN). In SHAMAN, a “mother” unbiased MD simulation of a target RNA is run in parallel with “daughter” simulations, one for each selected probe. RNAs in the daughter simulations are restrained, like shadows, to explore the conformational space of the mother and, concurrently, the sampling of the probes is accelerated by Metadynamics. SHAMAN was tested on a set of molecules of therapeutic interest, composed of riboswitches and viral RNAs, such as HIV1 TAR, IAV promotor and IRES RNAs. Selected probes included aromatic rings, like benzene and imidazole, and other moieties, like formamide and acetate. Starting from both ligand-bound and apo systems, we were able to detect experimentally resolved pockets and to rank them among the most populated by at least one probe. SHAMAN enables identifying pockets in RNA dynamic conformational ensembles and opens new possibilities for fragment-based drug design on flexible RNA using ensemble virtual screening techniques. The generic version of the shadowing technique is implemented in the open-source PLUMED library, freely available at www.plumed.org.