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Alex M Aronov

Publications and source records attributed to Alex M Aronov.

6 recordsLinked to original sources
PubMed2006

Common pharmacophores for uncharged human ether-a-go-go-related gene (hERG) blockers.

In silico approaches are widely used to predict human ether-a-go-go-related gene (hERG) channel blockade. Published pharmacophore models of hERG blockers typically contain a basic nitrogen center flanked by aromatic or hydrophobic groups. However, hERG blockade has been observed in series lacking the basic nitrogen. By utilizing screening data for 194 potent uncharged hERG actives, we propose a pharmacophore for neutral hERG blockers, and provide guidance on eliminating hERG liability in an uncharged hERG active chemical series.

Benzimidazoles↗
PubMed2005

Predictive in silico modeling for hERG channel blockers.

hERG-mediated sudden death as a side effect of non-antiarrhythmic drugs has been receiving increased regulatory attention. Perhaps owing to the unique shape of the ligand-binding site and its hydrophobic character, the hERG channel has been shown to interact with pharmaceuticals of widely varying structure. Several in silico approaches have attempted to predict hERG channel blockade. Some of these approaches are aimed primarily at filtering out potential hERG blockers in the context of virtual libraries, others involve understanding structure-activity relationships governing hERG-drug interactions. This review summarizes the most recent efforts in this emerging field.

Cation Transport Proteins↗
PubMed2004

Toward a pharmacophore for kinase frequent hitters.

Small molecule protein kinase inhibitors are widely employed as biological reagents and as leads in the design of drugs for a variety of diseases. One of the hardest challenges in kinase inhibitor design is achieving target selectivity. By utilizing X-ray structural information for four promiscuous inhibitors, we propose a five-point pharmacophore for kinase frequent hitters, demonstrate its ability to discriminate between frequent hitters and selective ligands, and suggest a strategy for selective inhibitor design.

Crystallography, X-Ray↗
PubMed2004

A minimalist approach to fragment-based ligand design using common rings and linkers: application to kinase inhibitors.

We present a novel method for stepwise scaffold assembly that integrates fragment-by-fragment ligand design approaches with high-throughput virtual library screening (COREGEN). As an extension of our earlier studies of common features present in drug molecules, we investigate the hypothesis that most pharmaceutically interesting ligands can be expressed in terms of the ring-linker frameworks that comprise them. Analysis of 119 published kinase inhibitors from at least 18 different targets illustrates that a basis set of 4 rings and 8 linkers is sufficient to describe approximately 90% of ring and linker occurrences, respectively. A similar result was derived from a larger set of approximately 40,000 kinase inhibitors from curated patents. A method for ring-linker-based assembly of scaffold libraries that uses experimental information to guide the placement of anchor fragments is validated using a set of reported kinase inhibitors of Bcr-Abl, Cdk2, and Src. In every case, the predominant structural motif of reported ligand cores is reproduced and variations are suggested. To underscore generality of this approach, a novel scaffold for a cyclooxygenase-2 (COX-2) selective ligand is proposed.

Algorithms↗
PubMed2004

A model for identifying HERG K+ channel blockers.

Acquired long QT syndrome (LQTS) occurs frequently as a side effect of blockade of cardiac HERG K(+) channels by commonly used medications. A large number of structurally diverse compounds have been shown to inhibit K(+) current through HERG. There is considerable interest in developing in silico tools to filter out potential HERG blockers early in the drug discovery process. We describe a binary classification model that combines a 2D topological similarity filter with a 3D pharmacophore ensemble procedure to discriminate between HERG actives and inactives with an overall accuracy of 82%, with false negative and false positive rates of 29% and 15%, respectively. This model should be generally applicable in virtual library counterscreening against HERG.

False Negative Reactions↗