ArticleJournal of clinical tuberculosis and other mycobacterial diseases2021
In silico identification of novel chemical compounds with antituberculosis activity for the inhibition of InhA and EthR proteins from Mycobacterium tuberculosis.
Article in Journal of clinical tuberculosis and other mycobacterial diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 27 citations in OpenAlex.
- Design, Synthesis, Antimycobacterial Evaluation, and In Silico Investigation of Benzisothiazole-Based Hydrazide Derivatives as Potential Anti-Tuberculosis Agents.Chemical biology & drug design · 2026Article
- Identification of potential inhibitors of dihydrofolate reductase (DHFR) through blocking the folate biosynthetic pathway ofRSC advances · 2025Article
- Integration of AI and ML in Tuberculosis (TB) Management: From Diagnosis to Drug Discovery.Diseases (Basel, Switzerland) · 2025Review
- Exploration of pyrazole-based pyridine-4-carbohydrazide derivatives as drug-resistantFuture medicinal chemistry · 2025Article
- Article
- Rapid discovery of Transglutaminase 2 inhibitors for celiac disease with boosting ensemble machine learning.Computational and structural biotechnology journal · 2024Article
- Developing phytocompound-based new drugs against multi-drug-resistantRoyal Society open science · 2024Article
- Design and Synthesis of the Linezolid Bioisosteres to Resolve the Serotonergic Toxicity Associated with Linezolid.ACS medicinal chemistry letters · 2024Article
- A Comprehensive Study to Unleash the Putative Inhibitors of Serotype2 of Dengue Virus: Insights from an In Silico Structure-Based Drug Discovery.Molecular biotechnology · 2024Article
- Elucidation and active ingredient identification of aqueous extract ofIn silico pharmacology · 2024Article
- Immunoinformatics-aided rational design of multiepitope-based peptide vaccine (MEBV) targeting human parainfluenza virus 3 (HPIV-3) stable proteins.Journal, genetic engineering & biotechnology · 2023Article
- In Silico Identification and Analysis of Potentially Bioactive Antiviral Phytochemicals against SARS-CoV-2: A Molecular Docking and Dynamics Simulation Approach.BioMed research international · 2023Article
- Synthesis, Biological Evaluation and Computational Studies of New Hydrazide Derivatives Containing 1,3,4-Oxadiazole as Antitubercular Agents.International journal of molecular sciences · 2022Article
- Oxa-376 and Oxa-530 variants of β-lactamase: computational study uncovers potential therapeutic targets ofRSC advances · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tuberculosis (TB) continuously poses a major public health concern around the globe, with a mounting death toll of approximately 1.4 million in 2019. Reduced bioavailability, elevated toxicity, increased side effects, and resistance of multiple first-line and second-line TB medications, including isoniazid, ethionamide necessitate studies of new drugs. The method of computational biology and bioinformatics approach allows virtual screening of a large number of drugs, reduces growing side effects of medications, and predicts potential drug resistance over time. In this study, we have analyzed fifty small molecules with antituberculosis properties using in silico approach including molecular docking, drug-likeness assessment, ADMET (absorption, distribution, metabolism, excretion, toxicity) profile evaluation, P450 site of metabolism prediction, and molecular dynamics simulation. Among those fifty compounds, 3-[3-(4-Fluorophenyl)-1,2,4-oxadiazol-5-yl]-N-(2-methylphenyl) piperidine-1-carboxamide (C22) and 5-(4-Ethyl-phenyl)-2-(1H-tetrazol-5-ylmethyl)-2H-tetrazole (C29) were found to pass the two-step molecular docking, P450 site of metabolism prediction and pharmacokinetics analysis successfully. Their binding stability for target proteins has been evaluated through root mean square deviation and root mean square fluctuation, Radius of gyration analysis from 10 ns Molecular Dynamics Simulation (MDS). Our identified drugs (C22 and C29) performed better than the control drugs (Isoniazid, Ethionamide) regarding binding affinity and molecular stability with the regulatory proteins (InhA, EthR) of Mycobacterium tuberculosis. The study proposed these compounds as effective therapeutic agents for Tuberculosis drug discovery, but further in vitro and in vivo testing are needed to substantiate their potential as novel drugs and modes of action.
Indexed as
Identifiers
What OpenQuestion holds
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.