Integrated In Silico Fragment-Based Drug Design: Case Study with Allosteric Modulators on Metabotropic Glutamate Receptor 5

Abstract

GPCR allosteric modulators target at the allosteric binding pockets of G protein-coupled receptors (GPCRs) with indirect influence on the effects of an orthosteric ligand. Such modulators exhibit significant advantages compared to the corresponding orthosteric ligands, including better chemical tractability or physicochemical properties, improved selectivity, and reduced risk of oversensitization towards their receptors. Metabotropic glutamate receptor 5 (mGlu5), a member of class C GPCRs, is a promising therapeutic target for treating many central nervous system diseases. The crystal structure of mGlu5 in the complex with the negative allosteric modulator mavoglurant was recently reported, providing a fundamental model for designing new allosteric modulators. Computational fragment-based drug discovery represents a powerful scaffold-hopping and lead structure-optimization tool for drug design. In the present work, a set of integrated computational methodologies was first used, such as fragment library generation and retrosynthetic combinatorial analysis procedure (RECAP) for novel compound generation. Then, the compounds generated were assessed by benchmark dataset verification, docking studies, and QSAR model simulation. Subsequently, structurally diverse compounds, with reported or unreported scaffolds, can be observed from top 20 in silico synthesized compounds, which were predicted to be potential mGlu5 modulators. In silico compounds with reported scaffolds may fill SAR holes in known, patented series of mGlu5 modulators. And the generation of compounds without reported tests on mGluR indicates that our approach is doable for exploring and designing novel compounds. Our case study of designing allosteric modulators on mGlu5 demonstrated that the established computational fragment-based approach is a useful methodology for facilitating new compound design in the future.

Computational systems pharmacology analysis of cannabidiol: a combination of chemogenomics-knowledgebase network analysis and integrated in silico modeling and simulation

“…SYBYL-X 1.3 was used for the preparation of the crystal structure, including energy minimization and residue repair. SYBYL-X 1.3 and PyMol (http:// www.pymol.org) were used for molecular visualization, structural superimposition, and data analysis following our usual operation routine [33].…”

“…A conserved orthosteric binding pocket among rhodopsin-like GPCRs was defined by selecting corresponding surrounding residues. The Kollman all atom approach was used to calculate atomic charges for the protein [34] and the Gasteiger-Hückel approach for the ligand [35] following our usual operation routine [33]. The hydrogen atoms of the protein were allowed to move.…”

Profiling the Structural Determinants of Aryl Benzamide Derivatives as Negative Allosteric Modulators of mGluR5 by In Silico Study

“…Christopher et al [22] Up to now, two mGluR5 receptor binding regions (the orthosteric binding region in the VFT and the allosteric binding region in the 7TM) have been reported [24]. In fact, we find that the studies on the NAM site almost all focus on the transmembrane allosteric binding region [8,[19][20][21][22], which can be explained by the fact that the allosteric binding pocket is less conserved compared to the orthosteric binding region, thus helping the identification of selective ligands [9]. In structure, the 8 antagonists belong to the acetylenic chemotype and non-acetylenic chemotype, as shown in Figure 8.…”

“…Therefore, two structural motifs, i.e., amide and urea functional groups, are proposed as the replacements of alkyne linkages in mGluR5 NAMs [18]. So far, altogether eight known mGluR5 NAMs have entered and/or are about to enter clinical trials, i.e., Mavoglurant [19][20][21], Basimglurant [8,21], MTEP [8], HTL14242 [20], Dipraglurant [21], Fenobam [21,22], Thiazole-2-carboxamides (6bc, 6bj) [18]. It is worth mentioning that, for a long time, the important structural information on mGluR5 NAMs was to combine mutation studies with homology modeling and/or a series of ligand analogs.…”

SuCOS is Better than RMSD for Evaluating Fragment Elaboration and Docking Poses

“…Nevertheless, RMSD is still widely used for comparing non-identical molecules such as in virtual screening programs. [14][15][16][17][18] Thus, it is unclear which metric is best at quantifying the degree of binding mode conservation, especially in cases where a smaller ligand and its elaborated counterpart are compared. Previous studies have discussed the pitfalls of certain metrics and hence use multiple metrics alongside one another.…”