ReviewMolecules (Basel, Switzerland)2020
Review in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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
28 citing papers in PubMed.
- Redefining Therapies for Drug-Resistant Tuberculosis: Synergistic Effects of Antimicrobial Peptides, Nanotechnology, and Computational Design.Advanced healthcare materials · 2026Review
- Tuberculosis: An Ongoing Global Threat.Advances in experimental medicine and biology · 2026Review
- Mechanisms of Antibiotic Resistance and Novel Therapeutic Approaches forHealth science reports · 2025Article
- Integrating Multi-Domain Approach for Identification of Neo Anti-DHPS Inhibitors Against PathogenicBiology · 2025Article
- [Research and International Cooperation for Shortening the Treatment Duration of Tuberculosis].Jugan geon-gang gwa jilbyeong · 2025Review
- Computational Exploration of Isatin Derivatives for InhA Inhibition in Tuberculosis: Molecular Docking, MD Simulations and ADMET Insights.Current computer-aided drug design · 2025Article
- Article
- Molecular docking, free energy calculations, ADMETox studies, DFT analysis, and dynamic simulations highlighting a chromene glycoside as a potential inhibitor of PknG inFrontiers in chemistry · 2025Article
- Multi-scale computational modeling to identify novel chemical scaffolds as trehalose-6-phosphate phosphatase inhibitors to combatIn silico pharmacology · 2025Article
- Identification of natural potent inhibitors against Mycobacterium tuberculosis isocitrate lyase: an in silico study.Molecular diversity · 2024Article
- Article
- The Structural and Molecular Mechanisms ofMolecules (Basel, Switzerland) · 2024Review
- An Update on Toll-like Receptor 2, Its Function and Dimerization in Pro- and Anti-Inflammatory Processes.International journal of molecular sciences · 2023Review
- Target Identification in Anti-Tuberculosis Drug Discovery.International journal of molecular sciences · 2023Review
- Study of the Rv1417 and Rv2617c Membrane Proteins and Their Interactions with Nicotine Derivatives as Potential Inhibitors of Erp Virulence-Associated Factor inBiomolecules · 2023Article
- Machine Learning Prediction of Mycobacterial Cell Wall Permeability of Drugs and Drug-like Compounds.Molecules (Basel, Switzerland) · 2023Article
- Assay development and inhibition of theMicrobiology (Reading, England) · 2023Article
- Advances in computational frameworks in the fight against TB: The way forward.Frontiers in pharmacology · 2023Review
- Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study.Frontiers in pharmacology · 2023Review
- Advances in the design of combination therapies for the treatment of tuberculosis.Expert opinion on drug discovery · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic.
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.