Abstract
G protein-coupled receptors (GPCRs) play crucial roles in cell physiology and pathophysiology. There is increasing interest in using structural information for virtual screening (VS) of libraries and for structure-based drug design to identify novel agonist or antagonist leads. However, the sparse availability of experimentally determined GPCR/ligand complex structures with diverse ligands impedes the application of structure-based drug design (SBDD) programs directed to identifying new molecules with a select pharmacology. In this study, we apply ligand-directed modeling (LDM) to available GPCR X-ray structures to improve VS performance and selectivity towards molecules of specific pharmacological profile. The described method refines a GPCR binding pocket conformation using a single known ligand for that GPCR. The LDM method is a computationally efficient, iterative workflow consisting of protein sampling and ligand docking. We developed an extensive benchmark comparing LDM-refined binding pockets to GPCR X-ray crystal structures across seven different GPCRs bound to a range of ligands of different chemotypes and pharmacological profiles. LDM-refined models showed improvement in VS performance over origin X-ray crystal structures in 21 out of 24 cases. In all cases, the LDM-refined models had superior performance in enriching for the chemotype of the refinement ligand. This likely contributes to the LDM success in all cases of inhibitor-bound to agonist-bound binding pocket refinement, a key task for GPCR SBDD programs. Indeed, agonist ligands are required for a plethora of GPCRs for therapeutic intervention, however GPCR X-ray structures are mostly restricted to their inactive inhibitor-bound state.
Highlights
Gprotein-coupled receptors (GPCRs) are the largest protein superfamily in mammalian genomes [1,2], encompassing close to 800 human genes that play key roles in modulating tissue and cell physiology and homoeostasis [3]
A notable difference was identified with the M2R agonist-bound structure 4MQS-iperoxo (IXO), where the removal of loops with the exception of the extracellular loop 2 (ECL2)-distal region resulted in a large improvement in virtual screening (VS) performance, in both recovery and selectivity
Other more complex implementations of interaction fingerprint (IFP) were shown to perform better when used for scoring docked poses [83], we showed that the IFP implementation used in this study is useful for the identification of a GPCR binding pocket with good VS performance [72]
Summary
Gprotein-coupled receptors (GPCRs) are the largest protein superfamily in mammalian genomes [1,2], encompassing close to 800 human genes that play key roles in modulating tissue and cell physiology and homoeostasis [3]. GPCRs all share a common transmembrane (TM) fold [5] and the superfamily is organised into four main classes according to the A-F classification system [6,7] Their function is modulated by a wide variety of activity modulators, including peptide and non-peptide neurotransmitters and hormones, growth factors, ions, odorant and tastant molecules and even photons of light [8]. They are highly dynamic proteins that can adopt a range of conformations, some of which are sparsely populated in the ligand-free receptor. Binding of an agonist at the extracellular region of the TM domain of the GPCR induces a shift in the conformational equilibrium, pushing the receptor through a series of discrete conformational intermediates, leading to large rearrangements at the intracellular region that facilitate the interaction with intracellular effectors including heterotrimeric G proteins, arrestins, and G protein-coupled receptor kinases that lead to downstream signalling and regulation [9]
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