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Antitubercular Agents

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First-line drug resistance profiling of : a machine learning approach.

AMIA ... Annual Symposium proceedings. AMIA Symposium 35309001
The persistence and emergence of new multi-drug resistant Mycobacterium tuberculosis (M. tb) strains continues to advance the devastating tuberculosis (TB) epidemic. Robust systems are needed to accurately and rapidly perform drug-resistance profilin...
Antitubercular Agents Drug Resistance, Multiple, Bacterial Humans Machine Learning Mycobacterium tuberculosis Tuberculosis
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Evaluation of magnesium oxide and zinc oxide nanoparticles against multi-drug-resistance Mycobacterium tuberculosis.

The Indian journal of tuberculosis 33845951
OBJECTIVE: The current study has evaluated the MICs and MBCs of ZnONPs, MgONPs, and MgONPs-ZnONPs against HRv Mtb and MDR-Mtb.
Antitubercular Agents Drug Synergism Humans Inhibitory Concentration 50 Magnesium Oxide Microbial Sensitivity Tests Mycobacterium tuberculosis Nanoparticles Tuberculosis, Multidrug-Resistant Zinc Oxide
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Antitubercular metabolites from the marine-derived fungus strain MF029.

Natural product research 34414849
During the systematic screening of bioactive compounds from our marine natural product library, crude extract of the marine-derived fungus strain MF029 exhibited moderate bioactivities against , S, methicillin-resistant , and bacillus Calmette-Guér...
Antitubercular Agents Aquatic Organisms Aspergillus fumigatus Biological Products Microbial Sensitivity Tests
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Development and validation of consensus machine learning-based models for the prediction of novel small molecules as potential anti-tubercular agents.

Molecular diversity 34110578
Tuberculosis (TB) is an infectious disease and the leading cause of death globally. The rapidly emerging cases of drug resistance among pathogenic mycobacteria have been a global threat urging the need of new drug discovery and development. However, ...
Algorithms Antitubercular Agents Bayes Theorem Consensus Machine Learning Support Vector Machine
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GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.

Genome medicine 34461978
BACKGROUND: Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly...
Antitubercular Agents Computational Biology Databases, Genetic Drug Resistance, Bacterial Genome, Bacterial Genomics Humans Machine Learning Microbial Sensitivity Tests Reproducibility of Results ROC Curve Software Tuberculosis, Multidrug-Resistant Web Browser Workflow
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Identification of active molecules against Mycobacterium tuberculosis through machine learning.

Briefings in bioinformatics 33822874
Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb) and it has been one of the top 10 causes of death globally. Drug-resistant tuberculosis (XDR-TB), extensively resistant to the commonly used first-line drugs, has e...
Antitubercular Agents Area Under Curve Data Accuracy Drug Discovery Humans Models, Biological Mycobacterium tuberculosis Neural Networks, Computer Reproducibility of Results ROC Curve Support Vector Machine Tuberculosis, Multidrug-Resistant
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Mycobacterium abscessus drug discovery using machine learning.

Tuberculosis (Edinburgh, Scotland) 35077930
The prevalence of infections by nontuberculous mycobacteria is increasing, having surpassed tuberculosis in the United States and much of the developed world. Nontuberculous mycobacteria occur naturally in the environment and are a significant proble...
Antitubercular Agents Bayes Theorem Drug Discovery Humans Machine Learning Mycobacterium abscessus
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Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.

Scientific reports 35165358
Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule-based Mycobacterium tuberculosis (MTB) drug resistance prediction methods using bacterial genomic s...
Antitubercular Agents Cohort Studies Data Accuracy Deep Learning Drug Resistance, Multiple, Bacterial Genome, Bacterial Humans Microbial Sensitivity Tests Mutation Mycobacterium tuberculosis Phenotype Phylogeny Prognosis Tuberculosis, Multidrug-Resistant Whole Genome Sequencing
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De novo design of anti-tuberculosis agents using a structure-based deep learning method.

Journal of molecular graphics & modelling 36257148
Mycobacterium tuberculosis (Mtb) is a pathogen of major concern due to its ability to withstand both first- and second-line antibiotics, leading to drug resistance. Thus, there is a critical need for identification of novel anti-tuberculosis agents t...
Antitubercular Agents Chorismate Mutase Deep Learning Drug Design Mycobacterium tuberculosis
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Machine learning-based drug design for identification of thymidylate kinase inhibitors as a potential anti-Mycobacterium tuberculosis.

Journal of biomolecular structure & dynamics 37232453
The rise of antibiotic-resistant Mycobacterium tuberculosis (Mtb) has reduced the availability of medications for tuberculosis therapy, resulting in increased morbidity and mortality globally. Tuberculosis spreads from the lungs to other parts of the...
Algorithms Antitubercular Agents Drug Design Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Mycobacterium tuberculosis Nucleoside-Phosphate Kinase Protein Binding Protein Kinase Inhibitors
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