Exploring the conformational space of a receptor for drug design: An ERα case study.

J Mol Graph Model

Centre de Biochimie Structurale (CBS), CNRS, INSERM, Univ Montpellier, 34090, Montpellier, France. Electronic address:

Published: November 2021

Protein flexibility is challenging for both experimentalists and modellers, especially in the field of drug design. Estrogen Receptor alpha (ERα) is an extensively studied Nuclear Receptor (NR) and a well-known therapeutic target with an important role in development and physiology. It is also a frequent off-target in standard toxicity tests for endocrine disruption. Here, we aim to evaluate the degree to which the conformational space and macromolecular flexibility of this well-characterized drug target can be described. Our approach exploits hundreds of crystallographic structures by means of molecular dynamics simulations and of virtual screening. The analysis of hundreds of crystal structures confirms the presence of two main conformational states, known as 'agonist' and 'antagonist', that mainly differ by the orientation of the C-terminal helix H12 which serves to close the binding pocket. ERα also shows some loop flexibility, as well as variable side-chain orientations in its active site. We scrutinized the extent to which standard molecular dynamics simulations or crystallographic refinement as ensemble recapitulate most of the variability features seen by the array of available crystal structures. In parallel, we investigated on the kind and extent of flexibility that are required to achieve convincing docking for all high-affinity ERα ligands present in BindingDB. Using either only one conformation with a few side-chains set flexible, or static structure ensembles in parallel during docking led to good quality and similar pose predictions. These results suggest that the several hundreds of crystal structures already known can properly describe the whole conformational universe of ERα's ligand binding domain. This opens the road for better drug design and affinity computation.

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http://dx.doi.org/10.1016/j.jmgm.2021.107974DOI Listing

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