Lessons learnt from assembling screening libraries for drug discovery for neglected diseases.

Area of Science:

• Medicinal Chemistry
• Drug Discovery
• Computational Chemistry

Background:

• Establishing drug discovery operations for neglected diseases requires efficient compound library creation.
• Large commercial compound collections necessitate strategic selection processes.

Purpose of the Study:

• To develop and implement a robust compound selection strategy for building diverse screening libraries.
• To curate in silico, general screening, and focused kinase inhibitor libraries for neglected disease research.
• To optimize compound selection for lead-like properties and facilitate structure-activity relationship studies.

Main Methods:

• Defined rules for unwanted chemical groups and established selection criteria for lead-like compounds.
• Conducted a literature and patent review to identify key recognition elements for kinase inhibitors.
• Assembled focused libraries based on identified kinase inhibitor core fragments.
• Performed computational and experimental characterization of the general screening library.

Main Results:

• Created an in silico library (222,552 compounds), a diverse general screening library (57,438 compounds), and a focused kinase inhibitor set (1,697 compounds).
• Selected compounds exhibit broad lead-like chemical space, high structural integrity, purity, and appropriate solubility for screening.
• The focused library successfully incorporates key recognition elements for kinase inhibitor discovery.

Conclusions:

• The developed compound selection strategy is effective for establishing drug discovery libraries, particularly in resource-limited academic settings.
• The curated libraries provide a valuable resource for hit discovery in neglected diseases, especially targeting kinases.
• The study highlights the importance of strategic compound selection for efficient and successful drug discovery programs.