Data-mining of potential antitubercular activities from molecular ingredients of Traditional Chinese Medicines

Abstract

View the peer-reviewed version (peerj.com/articles/476), which is the preferred citable publication unless you specifically need to cite this preprint. Jamal S, Scaria V, Open Source Drug Discovery Consortium. 2014. Datamining of potential antitubercular activities from molecular ingredients of traditional Chinese medicines. PeerJ 2:e476 https://doi.org/10.7717/peerj.476 Data-mining of potential antitubercular activities from molecular ingredients of Traditional Chinese MedicinesBackground 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. ResultsWe 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 TraditionalChinese 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 hepatoprotection offered by the source of these ingredients. PrePrints 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...

Machine-readable Yin–Yang imbalance: traditional Chinese medicine syndrome computer modeling based on three-dimensional noninvasive cardiac electrophysiology imaging

“…The fields of traditional and complementary medicine are important but often underestimated parts of health care. While traditional medicine has a long history of use in health maintenance and disease prevention and treatment, particularly for chronic disease 1–6 such as cardiovascular disease and cancer, rigorous scientific data are needed to demonstrate its efficacy and evidence-based standards for quality and safety evaluation. 7 The principal techniques of traditional Chinese medicine (TCM) are the four diagnostic methods of inspection, auscultation and olfaction, inquiry, and pulse-taking.…”