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Recursive deconvolution of combinatorial chemical libraries

E Erb1, K D Janda, S Brenner

  • 1Department of Molecular Biology, Scripps Research Institute, La Jolla, CA 92037.

Proceedings of the National Academy of Sciences of the United States of America
|November 22, 1994
PubMed
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A new recursive strategy efficiently identifies active compounds in chemical libraries. This method successfully discovered novel binders to a beta-endorphin antibody, alongside the known native binder.

Area of Science:

  • Chemical Biology
  • Combinatorial Chemistry
  • Drug Discovery

Background:

  • Identifying active compounds within large chemical libraries is crucial for drug discovery.
  • Traditional methods for library deconvolution can be complex and resource-intensive.

Purpose of the Study:

  • To present a novel recursive strategy for efficiently solving and identifying active members within a chemical library.
  • To demonstrate the application of this strategy in discovering novel binders to a beta-endorphin antibody.

Main Methods:

  • A pentapeptide combinatorial library (1024 members) was synthesized using a modified split synthesis approach.
  • A recursive deconvolution strategy involving coupling, cataloging, and randomization was employed.
  • Enzyme-linked immunosorbent assay (ELISA) was used to screen and quantify antibody binding.

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Main Results:

  • The recursive deconvolution successfully identified the known native binder (NH2-Tyr-Gly-Gly-Phe-Leu) to the beta-endorphin antibody.
  • Two additional novel pentapeptide members exhibiting significant binding were discovered.
  • The method proved effective without requiring molecular tags or multiple split synthesis steps.

Conclusions:

  • The presented recursive deconvolution strategy is an efficient and versatile method for identifying active compounds in combinatorial libraries.
  • This approach simplifies the deconvolution process and can be applied to various library types, including nonlinear small-molecule and linear oligomeric libraries.