Fighting Obesity with a Sugar-Based Library: Discovery of Novel MCH-1R Antagonists by a New Computational–VAST Approach for Exploration of GPCR Binding Sites

Abstract

Obesity is an increasingly common disease. While antagonism of the melanin-concentrating hormone-1 receptor (MCH-1R) has been widely reported as a promising therapeutic avenue for obesity treatment, no MCH-1R antagonists have reached the market. Discovery and optimization of new chemical matter targeting MCH-1R is hindered by reduced HTS success rates and a lack of structural information about the MCH-1R binding site. X-ray crystallography and NMR, the major experimental sources of structural information, are very slow processes for membrane proteins and are not currently feasible for every GPCR or GPCR-ligand complex. This situation significantly limits the ability of these methods to impact the drug discovery process for GPCR targets in "real-time", and hence, there is an urgent need for other practical and cost-efficient alternatives. We present here a conceptually pioneering approach that integrates GPCR modeling with design, synthesis, and screening of a diverse library of sugar-based compounds from the VAST technology (versatile assembly on stable templates) to provide structural insights on the MCH-1R binding site. This approach creates a cost-efficient new avenue for structure-based drug discovery (SBDD) against GPCR targets. In our work, a primary VAST hit was used to construct a high-quality MCH-1R model. Following model validation, a structure-based virtual screen yielded a 14% hit rate and 10 novel chemotypes of potent MCH-1R antagonists, including EOAI3367472 (IC50 = 131 nM) and EOAI3367474 (IC50 = 213 nM).

Using the fragment molecular orbital method to investigate agonist–orexin-2 receptor interactions

“…The HGMP was developed by Evotec Ltd in conjunction with the University of Oxford to support SBDD programmes [30,31]. The HGMP generates a 3D model of GPCR structures and its complexes with small molecules by applying a set of computational methods.…”

“…The hierarchical GPCR modelling protocol (HGMP) has been developed to support GPCR SBDD programmes. HGMP has been successfully applied in GPCR drug discovery projects such as MCH-1R for obesity treatment [30], the orexin-1 and -2 receptors (OX 1 R and OX 2 R) for insomnia [31,32], the 5-HT 2C for the treatment of metabolic disorders [33,34] and in other confidential drug discovery programmes. Additionally, the HGMP technology was used in the solving of the two H 1 R crystals structures [4] bound to the second and third generation antihistamines: cetirizine and fexofenadine.…”

From Receptors to Ligands: Fragment-assisted Drug Design for GPCRs Applied to the Discovery of H3 and H4 Receptor Antagonists

“…The identified VS hits themselves can now be used as tools for the further refinement of the existing GPCR models. The LowModeMD simulation protocol used in our work [1,91], followed by flexible docking, has gone beyond the use of static models and allowed for a more detailed exploration of the H3 and H4 receptors. The structural insights gained from this process are critical for the discovery of a new generation of H3 and H4 antagonists.…”

“…As described before [55,87], our modeling method is less dependent on the initial template due to the fact that we apply post homology modeling optimisation procedures. The LowModeMD used by us allowed refinement of the GPCR models to a degree that is not possible with static homology modelling alone [1]. The structural insights gained from this process are critical for the discovery of a new generation of H3 and H4 antagonists.…”

“…X-ray crystallography and NMR, the major experimental sources of structural information, are very slow processes for membrane proteins, and are not currently feasible for every GPCR or GPCR-ligand complex. This situation significantly limits the ability of these methods to impact the drug discovery process for GPCR targets in "real-time" and hence there is an urgent need for other practical and cost-efficient alternatives [1]. We present here a practical approach that integrates GPCR modeling with fragment based screening, to provide structural insights on the GPCR binding sites followed by structure based virtual screen (VS).…”