The Effect of Molecular Fields, Lattice Spacing and Analysis Options on CoMFA Predictive Ability
Ruchi R. Mittal, Ross Allan McKinnon, Michael Joseph Sorich · QSAR & Combinatorial Science · 2009
Abstract Comparative Molecular Field Analysis (CoMFA) is a popular Three‐Dimensional Quantitative Structure–Activity Relationship (3D‐QSAR) method. The effect of varying molecular fields [CoMFA vs. Comparative Molecular Similarity Indices Analysis (CoMSIA)], lattice spacing and analysis options on predictive performance was assessed based on cross validated R2 values of 30 datasets taken from the literature. The CoMFA method results in statistically significantly higher cross validated R2 values compared to CoMSIA when only steric and electrostatic fields are used. When the hydrophobic molecular field is included in the CoMSIA analysis (as is most commonly the case) the difference between CoMFA and CoMSIA is no longer statistically significant. Addition of hydrogen bond field does not improve CoMFA predictivity. Although there was a trend towards increased predictivity with decreased lattice spacing, this was not statistically significant. Altering the default filtering criteria and cut‐off values for Lennard Jones and Coulomb fields also did not generally result in a statistically significant effect on predictive performance.