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A critical assessment of combined ligand- and structure-based approaches to HERG channel blocker modeling.

ABSTRACT: Blockade of human ether-à-go-go related gene (hERG) channel prolongs the duration of the cardiac action potential and is a common reason for drug failure in preclinical safety trials. Therefore, it is of great importance to develop robust in silico tools to predict potential hERG blockers in the early stages of drug discovery and development. Herein we described comprehensive approaches to assess the discrimination of hERG-active and -inactive compounds by combining quantitative structure-activity relationship (QSAR) modeling, pharmacophore analysis, and molecular docking. Our consensus models demonstrated high-predictive capacity and improved enrichment and could correctly classify 91.8% of 147 hERG blockers from 351 inactives. To further enhance our modeling effort, hERG homology models were constructed, and molecular docking studies were conducted, resulting in high correlations (R² = 0.81) between predicted and experimental pIC??s. We expect our unique models can be applied to efficient screening for hERG blockades, and our extensive understanding of the hERG-inhibitor interactions will facilitate the rational design of drugs devoid of hERG channel activity and hence with reduced cardiac toxicities.

SUBMITTER: Du-Cuny L

PROVIDER: S-EPMC3894065 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature

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A critical assessment of combined ligand- and structure-based approaches to HERG channel blocker modeling.

Du-Cuny Lei L Chen Lu L Zhang Shuxing S

Journal of chemical information and modeling 20111013 11

Blockade of human ether-à-go-go related gene (hERG) channel prolongs the duration of the cardiac action potential and is a common reason for drug failure in preclinical safety trials. Therefore, it is of great importance to develop robust in silico tools to predict potential hERG blockers in the early stages of drug discovery and development. Herein we described comprehensive approaches to assess the discrimination of hERG-active and -inactive compounds by combining quantitative structure-activi ...[more]

PMID: 21902220

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Project description:The human ether-a-go-go-related voltage-gated cardiac ion channel (commonly known as hERG) conducts the rapid outward repolarizing potassium current in cardiomyocytes (IKr). Inadvertent blockade of this channel by drug-like molecules represents a key challenge in pharmaceutical R&D due to frequent overlap between the structure-activity relationships of hERG and many primary targets. Building on our previous work, together with recent cryo-EM structures of hERG, we set about to better understand the energetic and structural basis of promiscuous blocker-hERG binding in the context of Biodynamics theory. We propose a two-step blocker binding process consisting of: The initial capture step: diffusion of a single fully solvated blocker copy into a large cavity lined by the intra-cellular cyclic nucleotide binding homology domain (CNBHD). Occupation of this cavity is a necessary but insufficient condition for ion current disruption.The IKr disruption step: translocation of the captured blocker along the channel axis, such that: The head group, consisting of a quasi-rod-shaped moiety, projects into the open pore, accompanied by partial de-solvation of the binding interface.One tail moiety packs along a kink between the S6 helix and proximal C-linker helix adjacent to the intra-cellular entrance of the pore, likewise accompanied by mutual de-solvation of the binding interface (noting that the association barrier is comprised largely of the total head + tail group de-solvation cost).Blockers containing a highly planar moiety that projects into a putative constriction zone within the closed channel become trapped upon closing, as do blockers terminating prior to this region.A single captured blocker copy may conceivably associate and dissociate to/from the pore many times before exiting the CNBHD cavity. Lastly, we highlight possible flaws in the current hERG safety index (SI), and propose an alternate in vivo-relevant strategy factoring in: Benefit/risk.The predicted arrhythmogenic fractional hERG occupancy (based on action potential (AP) simulations of the undiseased human ventricular cardiomyocyte).Alteration of the safety threshold due to underlying disease.Risk of exposure escalation toward the predicted arrhythmic limit due to patient-to-patient pharmacokinetic (PK) variability, drug-drug interactions, overdose, and use for off-label indications in which the hERG safety parameters may differ from their on-label counterparts.

Project description:The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ? 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner.

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A critical assessment of combined ligand- and structure-based approaches to HERG channel blocker modeling.

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A critical assessment of combined ligand- and structure-based approaches to HERG channel blocker modeling.

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