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Construction of a Virtual High Throughput Screen by 4D-QSAR Analysis: Application to a Combinatorial Library of Glucose Inhibitors of Glycogen Phosphorylase b

1999; American Chemical Society; Volume: 39; Issue: 6 Linguagem: Inglês

10.1021/ci990032+

1520-5142

A. J. Hopfinger, Andrea Reaka, Prabha Venkatarangan, José S. Duca, Shen Wang,

Enzyme Catalysis and Immobilization

The 4D-QSAR model developed for a training set of 47 glucose analogue inhibitors of glycogen phosphorylase, and reported in the previous paper in this issue, was used as a basis for developing virtual high throughput screen, VHTS, models to screen a focused combinatorial virtual library of 225 additional inhibitors. Techniques to develop, evaluate, and apply VHTS models derived from 4D-QSAR models are presented. Application of the VHTS models to screen the virtual library results in the prediction of compounds which bind both more, and less, strongly to the enzyme than the best and worst binders of the training set. Analysis of the binding predictions across the virtual library reveals patterns of structure−activity information that can be useful to design new focused libraries. The possible use of overfit QSAR models, with respect to the training data set, as VHTS models is discussed and explored.