Authors: Lill, Markus A.; Dobler, Max; Vedani, Angelo

Source: Current Computer - Aided Drug Design, Volume 1, Number 3, July 2005 , pp. 307-324(18)

Publisher: Bentham Science Publishers

Abstract:

Quantitative structure-activity relationships (QSAR) are often employed to establish a correlation between structural features of potential drug candidates and their binding affinity towards a macromolecular target. In 3D-QSAR, the structures of the involved molecules are represented by three-dimensional entities, allowing to quantify electrostatic forces, hydrogen bonds and hydrophobic interactions at the atomic level. Models based on 3D-QSAR typically represent a binding site surrogate with physico-chemical properties mapped onto its surface or a grid surrounding the ligand molecules, superimposed in 3D space. Unfortunately such a single construct interacts with all ligands simultaneously, thus disabling the simulation of induced fit (receptor-to-ligand adaptation) - a fundamental shortcoming of the technology. As this entity represents all but a receptor surrogate, the bioactive conformation, orientation and protonation state of the ligand molecules might be guessed at best. Multidimensional QSAR represents a subtle extension of 3D-QSAR attempting to overcome both shortcomings.

In this account, we review different concepts and demonstrate their use to predict binding affinities of chemically diverse sets of ligand molecules binding to G-protein coupled and nuclear receptors. By employing multi-dimensional QSAR on partially diverse and large data sets, predicitive r2 of 0.837 (neurokinin-1), 0.859 (bradykinin B2 receptor) and 0.907 (estrogen receptor) were for example obtained using the Raptor and Quasar software.

Keywords: multidimensional qsar; induced-fit simulation; gpcr; nuclear receptors

Document Type: Review article

Affiliations: 1: Biographics Laboratory 3R, Friedensgasse 35, 4056 Basel, Switzerland.

Publication date: 2005-07-01

More about this publication?

• Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, etc., providing excellent rationales for drug development.

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