Rv0807, a putative phospholipase A2 of Mycobacterium tuberculosis; Elucidation through sequence analysis, homology modeling, molecular docking and molecular dynamics studies of potential substrates and inhibitors

Abstract

Mycobacterium tuberculosis (Mtb) has the ability to scrounge off the host macrophages and create a cordial environment for its survival. Identification of mechanisms favoring this purpose leads to novel treatment strategies for tuberculosis. In this study through in silico approaches, we intend to identify the putative role for Rv0807 from Mtb and its essentiality for mycobacterium survival within the macrophages. Through sequence analysis, we hypothesize that Rv0807 could be a Phospholipase A2 of Mtb. Moreover, through in silico mutation studies we have predicted certain residues to be a part of the catalytic process of the Rv0807 homodimer. Rv0807 could be a potential drug target as it binds phosphatidylinositol-3-phosphate (PI3P) and could be involved in processing the host cell PI3Ps, thereby blocking the phagosomal maturation. A pharmacophore hypothesis was generated for the Rv0807 homodimer based on the ligand binding site and a set of Pretomanid related compounds were screened against the Rv0807 homodimer. The top five compounds which had better docking scores and good ADME properties were selected as best inhibitory compounds and analyzed further. Molecular dynamics (MD) studies of Rv0807 homodimer with PI3P and with the top scored compound in docking studies, demonstrated a lot of conformational changes in the protein structure as it gets occluded through the course of simulation. The movement of a loop atop the ligand binding site, suggests of a lid-like region as seen in many other phospholipases. MD simulation of the mutant structures was also performed and its effect on the protein conformational changes was discussed.

Communicated by Ramaswamy H. Sarma

Keywords:

• Rv0807
• Mycobacterium tuberculosis
• homology modeling
• molecular docking
• in silico mutation
• molecular dynamics

Acknowledgements

We thank the DBT-Centre for Bioinformatics, Bharathiar University, Coimbatore, Tamil Nadu, India for providing the computational facilities to carrying out this work.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Shobana Sundar acknowledges the financial support through the award of Research Associateship from ICMR, Award Letter No: ISRM/11(13)/2019.