, Volume 6, Issue 3, pp 289–296 | Cite as

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

  • Zhan Wang
  • Tingting Wang
  • Guoyan Yang
  • Xinlei GaoEmail author
  • Kang Dai
Open Access
Research Article


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 q2 > 0.5 and conventional coefficients r2 > 0.9, indicating that the models are sufficiently reliable for activity prediction, and may be useful in the design of novel ester-based oils.


quantitative structure tribo-ability relationship antiwear properties lubricant-based oils 



This work was supported by the National Nature Science Foundation of China (NSFC, No. 51675395).

Supplementary material

40544_2017_175_MOESM1_ESM.pdf (485 kb)
Estimating antiwear properties of esters as potential lubricant-based oils using QSTR models with CoMFA and CoMSIA


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Copyright information

© The author(s) 2018

Authors and Affiliations

  • Zhan Wang
    • 1
  • Tingting Wang
    • 2
  • Guoyan Yang
    • 1
  • Xinlei Gao
    • 2
    Email author
  • Kang Dai
    • 3
  1. 1.College of Food Science and EngineeringWuhan Polytechnic UniversityWuhanChina
  2. 2.School of Chemical and Environmental EngineeringWuhan Polytechnic UniversityWuhanChina
  3. 3.College of PharmacySouth-Central University for NationalitiesWuhanChina

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