PRO_SELECT: combining structure-based drug design and combinatorial chemistry for rapid lead discovery. 1. Technology

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Drug Discovery

Background:

• Accelerating the identification of novel drug candidates is crucial in pharmaceutical research.
• Traditional drug discovery pipelines can be time-consuming and resource-intensive.
• Integrating computational methods with synthetic chemistry offers a promising avenue for efficiency.

Purpose of the Study:

• To introduce PRO_SELECT, a novel methodology for accelerated lead discovery.
• To demonstrate the utility of PRO_SELECT in designing potential therapeutic agents.
• To combine structure-based drug design principles with combinatorial chemistry approaches.

Main Methods:

• PRO_SELECT utilizes a synthetically accessible template positioned within the target active site.
• Database searching identifies potential substituents based on synthetic accessibility and target interaction.
• Computational screening and an empirical scoring function rank substituents for optimal binding.
• Combinatorial enumeration generates libraries of prioritized, synthetically accessible molecules.

Main Results:

• The PRO_SELECT methodology successfully generated lists of potential substituents.
• Computational screening and scoring effectively ranked substituents based on predicted binding affinity.
• The approach facilitated the design of a library of molecules for further evaluation.
• Preliminary results for thrombin inhibitors demonstrated the method's applicability.

Conclusions:

• PRO_SELECT represents a novel paradigm for accelerated lead discovery.
• The methodology effectively integrates computational screening with synthetic chemistry considerations.
• PRO_SELECT offers a powerful strategy for generating prioritized molecular libraries for drug development.