Refined Docking as a Valuable Tool for Lead Optimization: Application to Histamine H₃ Receptor Antagonists

Abstract

Drug-discovery projects frequently employ structure-based information through protein modeling and ligand docking, and there is a plethora of reports relating successful use of them in virtual screening. Hit/lead optimization, which represents the next step and the longest for the medicinal chemist, is very rarely considered. This is not surprising because lead optimization is a much more complex task. Here, a homology model of the histamine H(3) receptor was built and tested for its ability to discriminate ligands above a defined threshold of affinity. In addition, drug safety is also evaluated during lead optimization, and "antitargets" are studied. So, we have used the same benchmarking procedure with the HERG channel and CYP2D6 enzyme, for which a minimal affinity is strongly desired. For targets and antitargets, we report here an accuracy as high as at least 70%, for ligands being classified above or below the chosen threshold. Such a good result is beyond what could have been predicted, especially, since our test conditions were particularly stringent. First, we measured the accuracy by means of AUC of ROC plots, i. e. considering both false positive and false negatives. Second, we used as datasets extensive chemical libraries (nearly a thousand ligands for H(3)). All molecules considered were true H(3) receptor ligands with moderate to high affinity (from microM to nM range). Third, the database is issued from concrete SAR (Bioprojet H(3) BF2.649 library) and is not simply constituted by few active ligands buried in a chemical catalogue.

Structure-based discovery and binding site analysis of histamine receptor ligands

“…In an early study, a bovine rhodopsin based H3R model optimized by short MD simulations in a membrane environment was used for the optimization of H3 antagonist [29]. A docking-based threshold was defined that was able to discriminate known H3 ligands with 70% accuracy.…”

Histamine H3 Receptor Antagonists Go to Clinics

“…Still, antitargets have to be considered carefully. 126) Not only imidazole but also other N-heterocycles and unsaturated moieties show powerful CYP inhibition as shown in a series of cinnamic acid derivatives 127) targeted on the treatment of obesity and diabetes mellitus. 128) One of the most potent compounds, NNC 38-1202 (Ϫlog K i ϭ8.3), contains a 2-(pyrrolidinomethyl)pyrrolidino moiety.…”

“…219) Problems in clinical development eventually could arise from CYP2D6 or hERG channel inhibition. 24,126) First human data support a profit for narcoleptic patients: a pilot, placebo-controlled, single-blind, multi-center study, including 22 patients quoting an Epworth Sleepiness Scale (ESS) of 17.55 (max 24), reveals a significant reduction of EDS. Once a day treatment with 40 mg of tiprolisant during one week normalised ESS in nine patients (under 11), whereas the mean score of 21 patients was reduced to 11.81.…”

Reliability analysis and optimization of the consensus docking approach for the development of virtual screening studies

“…The widespread use of docking is due to the different purposes it can be employed for, which target different steps and issues of a drug discovery campaign. Ligand-protein docking represents the key tool to predict the most energetically favored disposition of a ligand bound to its corresponding protein target, and the predicted binding mode of hit and lead compounds can represent a valuable starting point for SAR analyzes and lead optimization studies aimed at improving ligand activity [1][2][3] . Docking is also largely used for hit identification, representing the main example of receptor-based virtual screening (VS) procedure: a docking-based approach is commonly reported in several successful VS studies, both alone and in combination with other computational strategies [4][5][6][7][8] .…”