ArticlePloS one2019
Empirical ways to identify novel Bedaquiline resistance mutations in AtpE.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.
- Global mapping of bedaquiline-resistant Mycobacterium tuberculosis: a systematic review.BMC infectious diseases · 2026Pooled it
- The structural context of mutations in proteins predicts their effect on antibiotic resistance.eLife · 2026Article
- Machine learning method for the prediction of Bedaquiline-resistantLife science alliance · 2026Article
- Bedaquiline resistance-associated genetic mutations and minimum inhibitory concentrations in drug-resistant tuberculosis clinical isolates from Limpopo province, South Africa.Frontiers in microbiology · 2026Article
- Exploring the effects of missense mutations on protein thermodynamics through structure-based approaches: findings from the CAGI6 challenges.Human genetics · 2025Article
- Cross-District Transmission of Tuberculosis in a High-Mobility City in China: Implications for Regional Collaboration in Infectious Disease Control.Infection and drug resistance · 2025Article
- Engineering G protein-coupled receptors for stabilization.Protein science : a publication of the Protein Society · 2024Article
- Prediction of pyrazinamide resistance inJAC-antimicrobial resistance · 2024Article
- Identification of genetic determinants of bedaquiline resistance inMicrobiology spectrum · 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
- Identification ofInfection and drug resistance · 2024Review
- THPLM: a sequence-based deep learning framework for protein stability changes prediction upon point variations using pretrained protein language model.Bioinformatics (Oxford, England) · 2023Article
- Quantitative measurement of antibiotic resistance inResearch square · 2023Article
- Identifying Innate Resistance Hotspots for SARS-CoV-2 Antivirals Using In Silico Protein Techniques.Genes · 2023Article
- Site-directed mutagenesis of Mycobacterium tuberculosis and functional validation to investigate potential bedaquiline resistance-causing mutations.Scientific reports · 2023Article
- Prediction of protein stability changes upon single-point variant using 3D structure profile.Computational and structural biotechnology journal · 2023Article
- Using Graph-Based Signatures to Guide Rational Antibody Engineering.Methods in molecular biology (Clifton, N.J.) · 2023Article
- A CRISPR-guided mutagenic DNA polymerase strategy for the detection of antibiotic-resistant mutations inMolecular therapy. Nucleic acids · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
Clinical resistance against Bedaquiline, the first new anti-tuberculosis compound with a novel mechanism of action in over 40 years, has already been detected in Mycobacterium tuberculosis. As a new drug, however, there is currently insufficient clinical data to facilitate reliable and timely identification of genomic determinants of resistance. Here we investigate the structural basis for M. tuberculosis associated bedaquiline resistance in the drug target, AtpE. Together with the 9 previously identified resistance-associated variants in AtpE, 54 non-resistance-associated mutations were identified through comparisons of bedaquiline susceptibility across 23 different mycobacterial species. Computational analysis of the structural and functional consequences of these variants revealed that resistance associated variants were mainly localized at the drug binding site, disrupting key interactions with bedaquiline leading to reduced binding affinity. This was used to train a supervised predictive algorithm, which accurately identified likely resistance mutations (93.3% accuracy). Application of this model to circulating variants present in the Asia-Pacific region suggests that current circulating variants are likely to be susceptible to bedaquiline. We have made this model freely available through a user-friendly web interface called SUSPECT-BDQ, StrUctural Susceptibility PrEdiCTion for bedaquiline (http://biosig.unimelb.edu.au/suspect_bdq/). This tool could be useful for the rapid characterization of novel clinical variants, to help guide the effective use of bedaquiline, and to minimize the spread of clinical resistance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.