Unleashing the potential of cheminformatic analysis for Mycobacterium tuberculosis inhibitors: Insights into chemical space and structural diversity

Abstract

Mycobacterium tuberculosis (Mtb) remains a major global health concern, causing millions of infections and deaths annually. Drug-resistant tuberculosis poses significant challenges, necessitating the search for new Mtb inhibitors. In this context, a cheminformatic analysis of the currently available antimycobacterial chemical space can be performed to discover structural diversity and new scaffolds. This study conducts a comprehensive cheminformatic analysis of two datasets containing Mtb inhibitors (Mtbs and Phytochemicals), comparing them with Approved drugs and Nutraceuticals datasets. The analysis includes physicochemical properties, molecular scaffolds, structural fingerprints, and structural similarities. The analysis of physicochemical property distributions revealed that Mtb inhibitors are generally less polar or equally polar compared to approved drugs and have similar flexibility. The visual representation of the property space illustrates that the Mtbs dataset is confined to a narrower area, whereas certain compounds within the Phytochemical dataset broaden the scope of the traditional medicinal space. Scaffold analysis identifies several promising candidates in both the Mtbs and Phytochemical datasets. Additionally, employing SkelSpheres descriptors and rubber band scaling for similarity analysis reveals a limited depiction of the chemical space. The analysis of structural diversity indicates that the compounds in the Mtbs dataset exhibit less structural diversity. These findings underscore the necessity to broaden the chemical space of Mtb-targeting molecules by incorporating representative molecules from diverse scaffolds to effectively tackle the issue of drug resistance.