ABCRpred: Prediction of antibiotic resistant strains of bacteria from their beta-lactamases protein

Welcome to the official repository for ABCRpred, a machine learning-based computational tool developed for predicting ceftazidime-resistant and ceftazidime-sensitive bacterial strains using beta-lactamase protein sequences. Web Server: https://webs.iiitd.edu.in/raghava/abcrpred/ Citation Maryam, L., Dhall, A., Patiyal, S., Usmani, S. S., Sharma, N., & Raghava, G. P. S. (2021). Prediction of antibiotic-resistant strains of bacteria from their beta-lactamases protein bioRxiv. https://doi.org/10.1101/2021.06.26.450028 About the Study Antimicrobial resistance (AMR) is one of the major global public health threats. Beta-lactamases are enzymes produced by bacteria that deactivate beta-lactam antibiotics such as ceftazidime. This study presents a computational framework to predict whether a bacterial strain is: Resistant to ceftazidime Sensitive to ceftazidime using only the beta-lactamase protein sequence. The developed system uses machine learning techniques and sequence-derived protein descriptors for classification. Dataset Information The dataset was collected from the β-lactamase database (BLDB). Dataset Statistics 199 beta-lactamase protein sequences 87 ceftazidime-sensitive proteins 112 ceftazidime-resistant proteins External Validation 22 resistant beta-lactamase sequences from the RGI database