Development of an in silico prediction model for chemical-induced urinary tract toxicity by using naïve Bayes classifier

  • Hui ZhangEmail author
  • Ji-Xia Ren
  • Jin-Xiang Ma
  • Lan DingEmail author
Original Article


The urinary tract toxicity is one of the major reasons for investigational drugs not coming into the market and even marketed drugs being restricted or withdrawn. The objective of this investigation is to develop an easily interpretable and practically applicable in silico prediction model of chemical-induced urinary tract toxicity by using naïve Bayes classifier. The genetic algorithm was used to select important molecular descriptors related to urinary tract toxicity, and the ECFP-6 fingerprint descriptors were applied to the urinary tract toxic/non-toxic fragments production. The established naïve Bayes classifier (NB-2) produced 87.3% overall accuracy of fivefold cross-validation for the training set and 84.2% for the external test set, which can be employed for the chemical-induced urinary tract toxicity assessment. Furthermore, six important molecular descriptors (e.g., number of N atoms, AlogP, molecular weight, number of H acceptors, number of H donors and molecular fractional polar surface area) and toxic and non-toxic fragments were obtained, which would help medicinal chemists interpret the mechanisms of urinary tract toxicity, and even provide theoretical guidance for hit and lead optimization.

Graphical abstract


Urinary tract toxicity Naïve Bayes classifier Molecular descriptors Genetic algorithm Extended-connectivity fingerprints (ECFP-6) 



This work was supported by the National Natural Science Foundation of China (Grant Nos. 81660589 and 31660101).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

11030_2018_9882_MOESM1_ESM.xlsx (20 kb)
Supplementary material 1 (XLSX 19 kb)


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.College of Life ScienceNorthwest Normal UniversityLanzhouPeople’s Republic of China
  2. 2.State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, West China Medical SchoolSichuan UniversityChengduPeople’s Republic of China
  3. 3.College of Life ScienceLiaocheng UniversityLiaochengPeople’s Republic of China

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