Data-mining of potential antitubercular activities from molecular ingredients of Traditional Chinese Medicines
- Published
- Accepted
- Subject Areas
- Bioinformatics, Drugs and Devices, Pharmacology, Computational Science
- Keywords
- Tuberculosis, Traditional Chinese Medicine, Cheminformatics, Virtual Screening, Data-mining
- Copyright
- © 2014 Jamal et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2014. Data-mining of potential antitubercular activities from molecular ingredients of Traditional Chinese Medicines. PeerJ PrePrints 2:e276v1 https://doi.org/10.7287/peerj.preprints.276v1
Abstract
Background Traditional Chinese medicine encompasses a well established alternate system of medicine based on a broad range of herbal formulations and is practiced extensively in the region for the treatment of a wide variety of diseases. In recent years, several reports describe in depth studies of the molecular ingredients of Traditional Chinese Medicines on the biological activities including anti-bacterial activities. The availability of a well-curated dataset of molecular ingredients of Traditional Chinese Medicines and accurate in-silico cheminformatics models for data mining for antitubercular agents and computational filters to prioritize molecules has prompted us to search for potential hits from these datasets.
Results We used a consensus approach to predict molecules with potential antitubercular activities from a large dataset of molecular ingredients of Traditional Chinese Medicines available in the public domain. We further prioritized 160 molecules based on five computational filters (SMARTSfilter) so as to avoid potentially undesirable molecules. We further examined the molecules for permeability across Mycobacterial cell wall and for potential activities against non-replicating and drug tolerant Mycobacteria. Additional in-depth literature surveys for the reported antitubercular activities of the molecular ingredients and their sources were considered for drawing support to prioritization.
Conclusions Our analysis suggests that datasets of molecular ingredients of Traditional Chinese Medicines offer a new opportunity to mine for potential biological activities. In this report, we suggest a proof-of-concept methodology to prioritize molecules for further experimental assays using a variety of computational tools. We also additionally suggest that a subset of prioritized molecules could be used for evaluation for tuberculosis due to their additional effect against non-replicating tuberculosis as well as the additional hepato-protection offered by the source of these ingredients.
Supplemental Information
Supplementary Table 1
Chinese medicine molecules used in the present study with their smiles.
Supplementary Table 2
Molecules predicted to have anti tubercular activity by our models.
Supplementary Table 3
9 molecules which could penetrate the Mycobacterium tuberculosis cell wall.