Validation of EGSITE2, a Mixed Integer Program for Deducing Objective Site Models from Experimental Binding Data

Journal of Medicinal Chemistry
1997.0

Abstract

EGSITE2 represents a substantial advance in a long series of methods for calculating receptor site models given only specific binding data. Compared to our most recently reported technique, EGSITE [Schnitker et al. J. Comput.-Aided Mol. Des. 1997, 11, 93-110] the user no longer has to simplify the structures of the molecules in the training set by clustering the atoms into a few superatoms. The only remaining source of subjectivity is the user's choice of compounds for the training set, which can be surprisingly few in number. Then EGSITE2 automatically produces typically several different models that explain the observed binding without outliers. The models are remarkably simple but have substantial predictive power for any sort of test compound, with an estimation of the uncertainty of the prediction. Validation of the method is reported for four standard test cases: triazines and pyrimidines binding to dihydrofolate reductase, steroids binding to corticosteroid-binding globulin and to testosterone-binding globulin, and peptides binding to angiotensin-converting enzyme.

Knowledge Graph

Similar Paper

Validation of EGSITE2, a Mixed Integer Program for Deducing Objective Site Models from Experimental Binding Data
Journal of Medicinal Chemistry 1997.0
A general distance-geometry three-dimensional receptor model for diverse dihydrofolate reductase inhibitors
Journal of Medicinal Chemistry 1984.0
Genetically Evolved Receptor Models: A Computational Approach to Construction of Receptor Models
Journal of Medicinal Chemistry 1994.0
Analysis of cocaine receptor site ligand binding by three-dimensional Voronoi site modeling approach
Journal of Medicinal Chemistry 1993.0
Mapping the turkey erythrocyte .beta.-receptor: a distance geometry approach
Journal of Medicinal Chemistry 1986.0
Use of physicochemical parameters in distance geometry and related three-dimensional quantitative structure-activity relationships: A demonstration using Escherichia coli dihydrofolate reductase inhibitors
Journal of Medicinal Chemistry 1985.0
Incorporation of Rapid Thermodynamic Data in Fragment-Based Drug Discovery
Journal of Medicinal Chemistry 2013.0
Combined distance geometry analysis of dihydrofolate reductase inhibition by quinazolines and triazines
Journal of Medicinal Chemistry 1983.0
Discovery of Kinase Inhibitors by High-Throughput Docking and Scoring Based on a Transferable Linear Interaction Energy Model
Journal of Medicinal Chemistry 2008.0
Modulation of Binding Strength in Several Classes of Active Site Inhibitors of Acetylcholinesterase Studied by Comparative Binding Energy Analysis
Journal of Medicinal Chemistry 2004.0