Estimating antiwear properties of esters as potential lubricant-based oils using QSTR models with CoMFA and CoMSIA

Comparative molecular field analysis and comparative molecular similarity indices analysis were employed to analyze the antiwear properties of a series of 57 esters as potential lubricant-based oils. Predictive 3D-quantitative structure tribo-ability relationship models were established using the SYBYL multifit molecular alignment rule with a training set and a test set. The optimum models were all shown to be statistically significant with cross-validated coefficients q(2) > 0.5 and conventional coefficients r(2) > 0.9, indicating that the models are sufficiently reliable for activity prediction, and may be useful in the design of novel ester-based oils.