Homology modeling, structural insights and in-silico screening for selective inhibitors of mycobacterial CysE

Abstract

Tuberculosis posses a major threat for health practitioners due to lengthy treatment regimen, increase in the drug-resistant strains of Mycobacterium tuberculosis (M. tb) and unavailability of drugs for its persistent form. Therefore, there is an urgent need for discovery of new and improved anti-tubercular drugs. In M. tb, the two step de novo biosynthesis of L-cysteine, an essential metabolic pathway is reported to be up-regulated in the persistent phase of the organism, involves two enzymes CysE and CysK. Although, structural insights for rational drug discovery are available for the later, not much information is known for the former. This study proposes a 3-dimensional model of M. tb CysE followed by in-silico screening of 67,030 anti-tuberculosis bioactive compounds. Subsequently, post-processing of 1000 best hits was carried out and top 200 compounds thus obtained were docked into the active site cleft of E. coli homologue as a control, but revealed unexpected results. Differences in the active site architectures and comparative analysis of molecular electrostatic potentials between the two CysEs provide molecular basis for the compounds C1, C3, C4 and C7 exhibiting preferential binding for M. tb CysE. In addition, shorter N-terminus along with positive and irregular trimeric base of M. tb CysE indicates its biological assembly as trimer. Based on mapping of residues involved in cysteine sensitivity on to the model structure of M. tb CysE, it is hypothesized that feedback inhibition of this homologue by cysteine may be affected.

Communicated by Ramaswamy H. Sarma

Keywords:

• Serine acetyltransferase
• Mycobacterium tuberculosis
• Escherichia coli
• virtual screening
• BEAR-algorithm
• Active-site architecture

Acknowledgements

This work would not have been possible without the exceptional support of Prof. Andrew M Lynn (School of Computational and Integrative Sciences, Jawaharlal Nehru University). His remarkable generosity provided us unconditional access to computational resources, his expert advice and encouragement made it possible to complete this study successfully. SG wishes to acknowledge the research grant from the Department of Science and Technology (DST), Govt. of India for support through WOS-A program (SR/WOS-A/LS-1442/2015). Special thanks to Deepali Verma and Gunjan Dixit for their critical acumen of the manuscript.

Author’s contribution

SG carried out all the experiments, analyzed the data and wrote the manuscript; VG conceived and supervised the study, helped in data interpretation and critical evaluation of the manuscript.

Conflict of interest

Authors declare there is no conflict of interest.

Additional information

Funding

The research work was financially supported by the WOS-A program (SR/WOS-A/LS-1442/2015), Department of Science and Technology (DST), Govt. of India.