Predictive power of<em> in silico</em> approach to evaluate chemicals against <em>M. tuberculosis</em>: A systematic review
Maurício Homem-de-Mello, Giulia Oliveira Timo, Rodrigo dos Reis, Adriana de Melo, Thales Viana Labourdette Costa, Pérola Oliveira Magalhães
Proceedings of 5th International Electronic Conference on Medicinal Chemistry · 2019-10
Abstract
Tuberculosis is still one of the most prevalent diseases worldwide caused by Mycobacteriumtuberculosis (Mtb), bearing a long-term treatment that is not always effective. Admitting thiscontext, multiple studies have been trying to develop novel substances against Mtb, specially using in silico techniques to predict its effects on a known target. Using a systematic approach, we were able to retrieve and evaluate 46 manuscripts from three different databases that firstly applied an in silico technique to explore new antimycobacterial molecules and secondly attempted to prove its predictive potential by an in vitro or in vivo assay. We found that although all manuscripts followed a similar screening procedure (ligand and/or structure-based screening), they explored a large number of ligands on 29 distinct bacterial enzymes. The following in vitro/vivo analysis showed that the virtual screening was able to decrease the number of tested molecules, saving time and funding, but could only provide a modest correlation to the effectiveness of those molecules in vitro. In short, we found that the preliminary in silico approach is recommended specially on the early steps in developinga new drug, but call for more studies to evaluate its clinical predictive possibilities.
MeSH terms
- In silico
- Antimycobacterial
- Virtual screening
- In vivo
- In vitro
- Computational biology
- Tuberculosis
- Mycobacterium tuberculosis
- Biology