Cross-validated R2-guided region selection for comparative molecular field analysis: a simple method to achieve...

Area of Science:

• Computational Chemistry
• Medicinal Chemistry
• Drug Discovery

Background:

• Comparative Molecular Field Analysis (CoMFA) is a key tool for Quantitative Structure-Activity Relationship (QSAR) studies.
• CoMFA predictability, measured by cross-validated correlation coefficient (q2), is sensitive to molecular orientation during superposition.
• This orientation dependence can lead to significant variations in q2 values, impacting reproducibility.

Purpose of the Study:

• To develop an optimized CoMFA method that yields orientation-independent and reproducible q2 values.
• To introduce a novel routine, cross-validated R2-guided region selection (q2-GRS), for enhancing CoMFA analysis.
• To validate the efficacy of the q2-GRS routine across diverse chemical datasets.

Main Methods:

• The q2-GRS routine subdivides the CoMFA lattice into smaller boxes.
• Independent analyses are performed within each box using probe atoms.
• Boxes with q2 values above a defined cutoff are selected, and CoMFA is repeated using the union of these selected boxes.

Main Results:

• The q2-GRS routine was tested on four datasets: cephalotaxine esters, 5-HT1A receptor ligands, HIV protease inhibitors, and steroids.
• In all cases, the q2-GRS method produced orientation-independent and high q2 values.
• The q2 values obtained using q2-GRS consistently exceeded those from conventional CoMFA.

Conclusions:

• The q2-GRS routine effectively addresses the orientation sensitivity issue in CoMFA.
• This method enhances the reliability and reproducibility of q2 values in CoMFA studies.
• q2-GRS is recommended for routine use in future CoMFA investigations to ensure consistent results.