ArticleScientific reports2020
Structure guided prediction of Pyrazinamide resistance mutations in pncA.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed, 71 citations in OpenAlex.
- The structural context of mutations in proteins predicts their effect on antibiotic resistance.eLife · 2026Article
- MuFaDDG: a sequence-based multiscale feature fusion framework for protein stability changes prediction.Bioinformatics (Oxford, England) · 2026Article
- Predicting pyrazinamide resistance in Mycobacterium tuberculosis using a graph convolutional network.BMC microbiology · 2026Article
- Zoonotic Tuberculosis as a One Health Challenge: Global Evidence, Transmission Dynamics, and Policy Gaps in Indonesia.Veterinary sciences · 2026Review
- A Comprehensive Review of Molecular Mechanisms Leading to the Emergence of Multidrug Resistance in Bacteria.Indian journal of microbiology · 2025Review
- Predicting rifampicin resistance inERJ open research · 2025Article
- Exploring the effects of missense mutations on protein thermodynamics through structure-based approaches: findings from the CAGI6 challenges.Human genetics · 2025Article
- Enhancing diagnostic efficiency of pyrazinamide resistance inCurrent research in microbial sciences · 2025Article
- Article
- Feature selection and aggregation for antibiotic resistance GWAS inFrontiers in microbiology · 2025Article
- A simplified pyrazinamidase test forJournal of clinical microbiology · 2024Article
- Engineering G protein-coupled receptors for stabilization.Protein science : a publication of the Protein Society · 2024Article
- Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence.Microorganisms · 2024Review
- Prediction of pyrazinamide resistance inJAC-antimicrobial resistance · 2024Article
- Characterizing and predicting ccRCC-causing missense mutations in Von Hippel-Lindau disease.Human molecular genetics · 2024Article
- Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach.Nature communications · 2024Article
- AI-Driven Enhancements in Drug Screening and Optimization.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Studying the dynamics of the drug processing of pyrazinamide in Mycobacterium tuberculosis.PloS one · 2024Article
- Prevalence, Transmission and Genetic Diversity of Pyrazinamide Resistance Among Multidrug-ResistantInfection and drug resistance · 2024Article
- Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Pyrazinamide plays an important role in tuberculosis treatment; however, its use is complicated by side-effects and challenges with reliable drug susceptibility testing. Resistance to pyrazinamide is largely driven by mutations in pyrazinamidase (pncA), responsible for drug activation, but genetic heterogeneity has hindered development of a molecular diagnostic test. We proposed to use information on how variants were likely to affect the 3D structure of pncA to identify variants likely to lead to pyrazinamide resistance. We curated 610 pncA mutations with high confidence experimental and clinical information on pyrazinamide susceptibility. The molecular consequences of each mutation on protein stability, conformation, and interactions were computationally assessed using our comprehensive suite of graph-based signature methods, mCSM. The molecular consequences of the variants were used to train a classifier with an accuracy of 80%. Our model was tested against internationally curated clinical datasets, achieving up to 85% accuracy. Screening of 600 Victorian clinical isolates identified a set of previously unreported variants, which our model had a 71% agreement with drug susceptibility testing. Here, we have shown the 3D structure of pncA can be used to accurately identify pyrazinamide resistance mutations. SUSPECT-PZA is freely available at: http://biosig.unimelb.edu.au/suspect_pza/.
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