ArticleMolecular diversity2009
Design of novel antituberculosis compounds using graph-theoretical and substructural approaches.
Article in Molecular diversity, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 44 citations in OpenAlex.
- An In Silico Study Based on QSAR and Molecular Docking and Molecular Dynamics Simulation for the Discovery of Novel Potent Inhibitor against AChE.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Computational Drug Repurposing for Antituberculosis Therapy: Discovery of Multi-Strain Inhibitors.Antibiotics (Basel, Switzerland) · 2021Article
- In vitro evaluation of arylsubstituted imidazoles derivatives as antiprotozoal agents and docking studies on sterol 14α-demethylase (CYP51) from Trypanosoma cruzi, Leishmania infantum, and Trypanosoma brucei.Parasitology research · 2019Article
- Bigger data, collaborative tools and the future of predictive drug discovery.Journal of computer-aided molecular design · 2014Article
- Fusing dual-event data sets for Mycobacterium tuberculosis machine learning models and their evaluation.Journal of chemical information and modeling · 2013Article
- Enhancing hit identification in Mycobacterium tuberculosis drug discovery using validated dual-event Bayesian models.PloS one · 2013Article
- In silico design of multi-target inhibitors for C-C chemokine receptors using substructural descriptors.Molecular diversity · 2012Article
- Fragment-based optimization of small molecule CXCL12 inhibitors for antagonizing the CXCL12/CXCR4 interaction.Current topics in medicinal chemistry · 2012Article
- QSAR model toward the rational design of new agrochemical fungicides with a defined resistance risk using substructural descriptors.Molecular diversity · 2011Article
- Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery.Trends in microbiology · 2011Review
Corrections and comments
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Authors and funding
6 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing resistance of Mycobacterium tuberculosis to the existing drugs has alarmed the worldwide scientific community. In an attempt to overcome this problem, two models for the design and prediction of new antituberculosis agents were obtained. The first used a mixed approach, containing descriptors based on fragments and the topological substructural molecular design approach (TOPS-MODE) descriptors. The other model used a combination of two-dimensional (2D) and three-dimensional (3D) descriptors. A data set of 167 compounds with great structural variability, 72 of them antituberculosis agents and 95 compounds belonging to other pharmaceutical categories, was analyzed. The first model showed sensitivity, specificity, and accuracy values above 80% and the second one showed values higher than 75% for these statistical indices. Subsequently, 12 structures of imidazoles not included in this study were designed, taking into account the two models. In both cases accuracy was 100%, showing that the methodology in silico developed by us is promising for the rational design of antituberculosis drugs.
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