Date Published:

2002

Abstract:

Computational methods are becoming increasingly used in the drug discovery process. In this Account, we review a novel computational method for lead discovery. This method, called CombiSMoG for ?combinatorial small molecule growth?, is based on two components:? a fast and accurate knowledge-based scoring function used to predict binding affinities of protein?ligand complexes, and a Monte Carlo combinatorial growth algorithm that generates large numbers of low-free-energy ligands in the binding site of a protein. We illustrate the advantages of the method by describing its application in the design of picomolar inhibitors for human carbonic anhydrase.

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