Computational screening, docking and simulation analysis of phytochemicals from Senna auriculata against multiple targets of Mycobacterium tuberculosis

Abstract

Tuberculosis is an infectious disease caused by potential pathogenic bacteria Mycobacterium tuberculosis (Mtb) that causes more than ~1.5 million deaths every year. The reason for its successful infection rate is owed to its resilient, tough mycolic acid-rich cell wall that makes the antibiotics hard to penetrate into the cell and its ability to manipulate the immune system. In addition, drug resistance has become a major concern. For the above-mentioned reasons, incessant attempts are being made to identify novel drug targets and newer natural anti-tubercular drugs to control the spread of TB. In the previous study, ethnobotanically important medicinal plants Trachyspermum copticum and Senna auriculata were evaluated for anti-mycobacterial potential against M. smegmatis. The crude extracts were analyzed in Gas Chromatography-Mass Spectrometry (GC-MS) to identify potential anti-TB compounds. In the current study, a total of 53 phytochemicals identified and mentioned in literature from medicinal plants Trachyspermum copticum and Senna auriculata in addition to the phytochemicals obtained from the GC-MS analysis were subjected to in silico docking evaluation against important drug targets of Mycobacterium tuberculosis. Most targets chosen in the study contribute to cell wall metabolism of Mtb. From the exhaustive docking analysis, lupeol and stigmasterol are identified as potential multitargeted anti-TB compounds and proposed as drug candidates. Molecular dynamic simulation studies revealed stable interaction of stigmasterol with FbiB, MmpL3 and EmbC making it a potential multi-target compound.