Predictive power of in silico approach to evaluate chemicals against M. tuberculosis: A systematic review

Tuberculosis is still one of the most prevalent diseases worldwide caused by Mycobacterium
tuberculosis (Mtb), bearing a long-term treatment that is not always effective. Admitting this
context, 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 developing
a new drug, but call for more studies to evaluate its clinical predictive possibilities.