Molecular shape diversity of combinatorial libraries: a prerequisite for broad bioactivity

Area of Science:

• Computational chemistry
• Cheminformatics
• Drug discovery

Background:

• Assessing molecular shape diversity is crucial for drug discovery.
• Existing methods may not efficiently capture or compare shape space coverage.
• Understanding shape diversity's link to biological activity is key.

Purpose of the Study:

• To develop a rapid computational method for assessing and visualizing molecular shape diversity.
• To quantitatively analyze shape redundancy and interset similarity in compound collections.
• To correlate molecular shape diversity with biological activity.

Main Methods:

• Developed a computational method using normalized ratios of principal moments of inertia.
• Utilized two-dimensional triangular graphs to plot and compare shape space coverage.
• Applied shape analysis to compound libraries (e.g., combinatorial libraries, MDDR, GOLD-set).

Main Results:

• Shape space coverage is primarily determined by the central scaffold's nature and 3D geometry, not its size.
• Peripheral substituents and conformational aspects have minor influence on shape space coverage.
• Substantial shape space coverage in compound collections correlates with broad biological activity.

Conclusions:

• Molecular shape is intrinsically linked to biological activity.
• A high degree of shape diversity in screening collections enhances the potential to address diverse biological targets.
• The developed method provides a quantitative tool for analyzing and optimizing compound library design for drug discovery.