Ensemble Docking to Difficult Targets in Early-Stage Drug Discovery: Methodology and Application to Fibroblast Growth Factor 23

Abstract

Ensemble docking is now commonly used in early-stage in silico drug discovery, and can be used to attack difficult problems such as finding lead compounds which can disrupt protein:protein interactions. We give an example of this methodology here, as applied to fibroblast growth factor 23 (FGF23), a protein hormone that is responsible for regulating phosphate homeostasis. The first small molecule antagonists of FGF23 were recently discovered by combining ensemble docking with extensive experimental target validation data¹. Here, we provide a detailed account of how ensemble-based high-throughput virtual screening was used to identify the antagonist compounds discovered in Ref. 1. Moreover, we perform further calculations, re-docking those antagonist compounds identified in Ref. 1 that performed well on drug-likeness filters, to predict possible binding regions. These predicted binding modes are rescored with the Molecular Mechanics Poisson Boltzmann surface area (MM/PBSA) approach to calculate the most likely binding site. Our findings suggest that the antagonist compounds antagonize FGF23 through the disruption of protein-protein interactions between FGF23 and fibroblast growth factor receptor (FGFR).

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An ensemble docking protocol is presented which is used to computationally propose compounds to anatagonize FGF23 activity. Further simulations propose a binding pocket and propose of mechanism of action for the experimentally verified FGF23 antagonist compounds.

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