Extended-Ensemble Docking to Probe Evolution of Ligand Binding Sites in Proteins Undergoing Large-Scale Structural Changes for Their Function

Abstract

Proteins can sample a broad landscape as they undergo conformational transition between different functional states. As key players in almost all cellular processes, proteins are important drug targets. Considering the different conformational states of a protein is therefore central for a successful drug-design strategy. Here we introduce a novel docking protocol, termed as extended-ensemble docking, pertaining to proteins that undergo large-scale (global) conformational changes during their function. In its application to multidrug ABC-transporter P-glycoprotein (Pgp), extensive non-equilibrium molecular dynamics simulations employing system-specific collective variables capturing the alternate access mechanism of Pgp, are first used to construct the transition cycle of the transporter. An extended set of conformational states representing the full transition between the inward- and the outward-facing states of Pgp, is then used to seed high-throughput docking calculations of a set of known substrates, non-substrates, and modulators of the transporter. Large differences are observed in the predicted binding affinities to the conformational ensemble, with compounds showing stronger binding affinities to intermediate conformations compared to the starting crystal structure. Hierarchical clustering of the individual binding modes of the different compounds shows all ligands preferably bind to the large central cavity of the protein, formed at the apex of the transmembrane domain (TMD), whereas only small binding populations are observed in the previously described R and H sites present within the individual TMD leaflets. Based on the results, the central cavity is further divided into two major subsites: first subsite preferably binds smaller substrates and high-affinity inhibitors, whereas the second one shows preference for larger substrates and low-affinity modulators. These central sites along with the low-affinity interaction sites present within the individual TMD leaflets may respectively correspond to the proposed high- and low-affinity binding sites in Pgp. We propose further optimization strategy for developing more potent inhibitor of Pgp, based on increasing its specificity to the extended ensemble of the protein instead of using a single protein structure, as well as its selectivity for the high-affinity binding site. In contrast to earlier in-silico studies using single static structures of Pgp, our results show better agreement with experimental studies, pointing to the importance of incorporating the global conformational flexibility of proteins in future drug-discovery endeavors.