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

  • Zhan Wang
  • Tingting Wang
  • Guoyan Yang
  • Xinlei Gao
  • 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 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.


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 (488 kb)
Supplementary material, approximately 489 KB.


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© The author(s) 2017

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Zhan Wang
    • 1
  • Tingting Wang
    • 2
  • Guoyan Yang
    • 1
  • Xinlei Gao
    • 2
  • 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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