uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction

Saurav Bhaskar Saha; Vijai Kumar Gupta; Pramod Wasudeo Ramteke

doi:10.1016/j.gendis.2020.06.008

uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction

Genes Dis. 2020 Jun 30;8(5):721-729. doi: 10.1016/j.gendis.2020.06.008. eCollection 2021 Sep.

Authors

Saurav Bhaskar Saha¹, Vijai Kumar Gupta², Pramod Wasudeo Ramteke³

Affiliations

¹ Department of Computational Biology and Bioinformatics, JIBB, SHUATS, Prayagraj, Uttar Pradesh, 211007, India.
² Department of Chemistry and Biotechnology, School of Science, Tallinn University of Technology, Akadeemia Tee 15, Tallinn, 12618, Estonia.
³ Department of Biological Sciences, SHUATS, Prayagraj, Uttar Pradesh, 211007, India.

Abstract

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) and2. GitHub (https://github.com/sauravbsaha/uCAREChemSuiteCLI).

Keywords: Drug resistance; Escherichia coli; Prediction; Pseudomonas aeruginosa; Resistome; uCARE chem suite; uCAREChemSuiteCLI.