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

Summary

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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Inquiries concerning the CHARMM, MCSS, and HOOK programs should be addressed to M. Karplus (e-mail: marci@tammy.harvard.edu). Inquiries concerning the program CONNECT should be addressed to A. Caflisch at Department of Biochemistry, University of Zürich, CH-8057 Zürich, Switzerland.

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Caflisch, A., Karplus, M. Computational combinatorial chemistry for de novo ligand design: Review and assessment. Perspectives in Drug Discovery and Design 3, 51–84 (1995). https://doi.org/10.1007/BF02174467

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Keywords

  • Polymer
  • Thrombin
  • Therapeutic Agent
  • Design Problem
  • Drug Discovery