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A Novel Electron-Conformational Approach to Molecular Modeling for QSAR by Identification of Pharmacophore and Anti-Pharmacophore Shielding
Authors:I B Bersuker  S Bahceci  J E Boggs  R S Pearlman
Institution:1. Institute for Theoretical Chemistry, Department of Chemistry and Biochemistry , Austin, TX, 78712, USA;2. College of Pharmacy, The University of Texas at Austin , Austin, TX, 78712, USA;3. Institute for Theoretical Chemistry, Department of Chemistry and Biochemistry , Austin, TX, 78712, USA;4. College of Pharmacy, The University of Texas at Austin , Austin, TX, 78712, USA
Abstract:Abstract

A novel method of pharmacophore identification and activity prediction in structure-activity (structure-property) relationships is worked out as an essential extension and improvement of previous publications. In this method each conformation of the molecular systems in the training set of the SAR problem is presented by both electronic structure and geometry parameters arranged in a matrix form. Multiple comparisons of these matrices for the active and inactive compounds allows one to separate a smaller number of matrix elements that are common for all the active compounds and are not present in the same arrangement in the inactive ones. This submatrix of activity represents the pharmacophore (Pha).

By introducing the Anti-Pharmacophore Shielding (APS) defined as molecular groups and competing charges outside the Pha that hinder the proper docking of the Pha with the bioreceptor, the procedure of Pha identification is essentially reduced to the treatment of a smaller number of simplest in structure most active and inactive compounds. A simple empirical scheme is suggested to estimate the APS numerically, while the contributions of different conformations of the same compound are taken into account by means of Boltzmann distribution. This enables us to make approximate quantitative predictions of activities.

In application to rice blast activity we reached an approximately 100% (within experimental error) prediction probability of the activity qualitatively (yes, no), and with r 2 = 70% quantitatively.
Keywords:
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