Enhancing the hit-to-lead properties of lead optimization libraries

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Drug Discovery

Background:

• The pharmacophore hypothesis is crucial for understanding drug-target interactions.
• Multipharmacophore descriptors aid in designing diverse compound libraries.
• These descriptors can be applied to both diverse and focused library design.

Purpose of the Study:

• To present and validate the use of multipharmacophore descriptors for lead optimization libraries.
• To demonstrate the applicability of these descriptors for both diverse and focused library design.
• To explore the derivation of descriptors for predicting pharmacokinetic properties and improving drug absorption.

Main Methods:

• Development and application of multipharmacophore descriptors.
• Utilizing descriptors for diverse and focused library design and screening set selection.
• Deriving rapidly computable descriptors for drug transport properties (e.g., log P, molecular weight, polar surface area).
• Employing a Monte Carlo search procedure for near-combinatorial library selection.

Main Results:

• Multipharmacophore descriptors support the argument for biologically relevant diversity.
• The descriptors are portable across diverse library design, screening set selection, and focused library design.
• Simple, computable descriptors can predict drug transport properties.
• Consideration of log P, molecular weight, and polar surface area in library design improved absorption characteristics.

Conclusions:

• Multipharmacophore descriptors offer a consistent approach to library design.
• Derived descriptors enable the prediction and optimization of pharmacokinetic properties.
• Optimized library design using these methods leads to compounds with enhanced absorption characteristics.