Combinatorial library design from reagent pharmacophore fingerprints

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Drug Discovery

Background:

• Combinatorial and parallel synthesis are key in early drug discovery.
• Computational methods are increasingly used to explore molecular diversity for new chemical entities.
• Targeted and focused screening libraries are in high demand.

Purpose of the Study:

• To introduce ProSAR, a complementary technique for designing chemical libraries.
• To effectively cover the accessible pharmacophore space around a given molecular scaffold.
• To facilitate the derivation of structure-activity relationships (SAR).

Main Methods:

• ProSAR selects reagents to optimize pharmacophore coverage for each R-group on a scaffold.
• Shannon entropy is optimized to quantify the information content of topological pharmacophore distributions.
• Compounds are enumerated with systematic variations of user-defined pharmacophores.

Main Results:

• The ProSAR method systematically explores pharmacophore space.
• It ensures optimal coverage of pharmacophoric features for R-groups.
• Enumerated compounds provide a strong basis for SAR studies.

Conclusions:

• ProSAR is an effective computational approach for chemical library design.
• It enhances the exploration of chemical space for drug discovery.
• The method aids in generating starting points for lead optimization and SAR development.