uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction

Saurav Bhaskar Saha, Vijai Kumar Gupta, Pramod Wasudeo Ramteke*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


In the era of antibiotic resistance, in silico prediction of bacterial resistome profiles, likely to be associated with inactivation of new potential antibiotics is of utmost importance. Despite this, to the best of our knowledge, no tool exists for such prediction. Therefore, under the rationale that drugs with similar structures have similar resistome profiles, we developed two models, a deterministic model and a stochastic model, to predict the bacterial resistome likely to neutralize uncharacterized but potential chemical structures. The current version of the tool involves the prediction of a resistome for Escherichia coli and Pseudomonas aeruginosa. The deterministic model on omitting two diverse but relatively less characterized drug classes, polyketides and polypeptides showed an accuracy of 87%, a sensitivity of 85%, and a precision of 89%, whereas the stochastic model predicted antibiotic classes of the test set compounds with an accuracy of 72%, a sensitivity of 75%, and a precision of 83%. The models have been implemented in both a standalone package and an online server, uCAREChemSuiteCLI and uCARE Chem Suite, respectively. In addition to resistome prediction, the online version of the suite enables the user to visualize the chemical structure, classify compounds in 19 predefined drug classes, perform pairwise alignment, and cluster with database compounds using a graphical user interface. Availability: uCARE Chem Suite can be browsed at: https://sauravsaha.shinyapps.io/ucarechemsuite2/, and uCAREChemSuiteCLI can be installed from: 1. CRAN (https://cran.r-project.org/package=uCAREChemSuiteCLI) and 2. GitHub (https://github.com/sauravbsaha/uCAREChemSuiteCLI).

Original languageEnglish
Pages (from-to)721-729
Number of pages9
JournalGenes and Diseases
Issue number5
Early online date30 Jun 2020
Publication statusPrint publication - Sept 2021
Externally publishedYes

Bibliographical note

© 2020 Chongqing Medical University. Production and hosting by Elsevier B.V.


  • Drug resistance
  • Escherichia coli
  • Prediction
  • Pseudomonas aeruginosa
  • Resistome
  • uCARE chem suite
  • uCAREChemSuiteCLI


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