Peptide and nonpeptide lead discovery using robotically synthesized soluble libraries

Area of Science:

• Medicinal Chemistry
• Synthetic Chemistry
• Drug Discovery

Background:

• Solid-phase combinatorial synthesis enables rapid generation of diverse molecular libraries.
• Automating key steps like 'mix and divide' is crucial for efficient library production.
• Characterizing complex libraries requires advanced analytical techniques.

Purpose of the Study:

• To analyze combinatorial synthesis methods for peptide and nonpeptide libraries.
• To describe the automation of the 'mix and divide' technique.
• To propose strategies for generating high molecular diversity and evaluating library analysis methods.

Main Methods:

• Solid-phase synthesis utilizing a 'mix and divide' approach.
• Selection of amino acids and scaffolds for high molecular diversity.
• Analysis of library content using capillary electrophoresis, mass spectrometry (MS, MS/MS), and NMR.
• Evaluation of iterative deconvolution (SURF) versus positional scanning.

Main Results:

• A set of amino acids and scaffolds for preparing variable polyamide libraries is proposed.
• The adequacy of resin bead quantities for library size and peptide ratios is discussed.
• Comparison of SURF deconvolution with positional scanning for evaluating coupling success.

Conclusions:

• Extending mix and divide methods and SURF deconvolution to nonpeptide libraries yields novel therapeutic leads.
• These optimized libraries can be further developed into potential therapeutics.
• Automation and advanced analytical methods enhance the efficiency and scope of combinatorial chemistry.