Crystal structure-based virtual screening for fragment-like ligands of the human histamine H(1) receptor.

By C. de Graaf, Albert J. Kooistra, H. Vischer, Vsevolod Katritch, M. Kuijer, M. Shiroishi, S. Iwata, T. Shimamura, Raymond C. Stevens, I. D. de Esch and 1 more. 2011

216 citations recorded by the source corpus.

The recent crystal structure determinations of druggable class A G protein-coupled receptors (GPCRs) has opened up excellent opportunities in structure-based ligand discovery for this pharmaceutically important protein family. We have developed and validated a customized structure-based virtual fragment screening method against the recently determined human histamine H1 receptor (H1R) crystal structure. The method combines molecular docking simulations with a protein-ligand interaction fingerprint (IFP) scoring method. The optimized in silico screening approach was successfully applied to identify a chemically diverse set of novel fragment-like (≤ 22 heavy atoms) H1R ligands with an exceptionally high hit rate of 73%. Of the 26 tested fragments, 19 compounds had affinities ranging from 10 μM to 6 nM. The current study shows the potential of in silico screening against GPCR crystal structures to explore novel, fragment-like GPCR ligand space.

Subfields: Computational Theory and Mathematics, Molecular Biology, Evaluation & Benchmarks

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Ruben Abagyan

Citations in the corpus

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets (2015, methodology): “The fragment docking was assessed with a fingerprint scoring method that predicted 19 out of 26 fragment-like compounds to possess high binding affinity at the H1 receptor (73% hit rate) (39).”
Latest developments in molecular docking: 2010–2011 in review (2013, methodology): “[32] Library screening by fragment docking has been applied to proteases and kinases, [124] thermolysin, [125] and GPCRs. [126] Thus, recent literature reveals that fragment docking is a viable method to investigate fragment – receptor interactions, given suf ﬁ cient LE of fragments being docked.”
GPCR Network: a large-scale collaboration on GPCR structure and function (2012, background): “50 ) , dopamine D 3 receptor 51 and H 1 receptors 52 , as well as in lead optimization 21 .”
Integrating structural and mutagenesis data to elucidate GPCR ligand binding (2016, background): “Ligand interaction fingerprints offer one such interesting approach, which has been shown to be able to discriminate agonists from antagonists based on their receptor interactions, as well as increase the hit rate from virtual screening [47].”