Computational combinatorial chemistry for de novo ligand design: Review and assessment

Computational combinatorial chemistry divides the ligand design problem into three parts: the search for optimal positions and orientations of functional groups in the binding site, the connection of such optimally placed fragments to form candidate ligands, and the estimation of their binding constants. In this review, approaches to each of these problems are described. The present limitations of methodologies are indicated and efforts to improve them are outlined. Applications to HIV-1 aspartic proteinase, which is a target for the development of AIDS therapeutic agents, and human thrombin, a multifunctional enzyme that has a central role in both haemostasis and thrombosis, are presented. The relation between combinatorial methods for drug discovery on the computer and in the laboratory is addressed.

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