Insilico Identification of Candidate Hits for MTRA Response Regulator
Aditya Simhadri, Krishna Chaitanya Amajala
SSRN Electronic Journal · 2020-02
Abstract
Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium tuberculosis which has been present in the human population for thousands of years and was recognized as the leading cause of mortality. The bacteria usually attack the lungs. Proteins named Two-component systems of bacteria play a major role in their adaptation to the environment. In its most basic form, the two-component system consists of a Histidine sensor Kinase (HK) and a Response Regulator (RR). The genome sequence of M. tuberculosis has shown the presence of at least 12 two-component system homologues with 8 unlinked sensor kinases or response regulators. However, the exact physiological role of most of these proteins is far from being understood. Hence, an attempt has been made in this study with the objective of identifying total number of HKs and RRs in entire proteome and their interaction partners to understand the functional specificity of various Response Regulators in M. tuberculosis. From the computational protein-protein interactomic network data analysis & literature, it was found thatone of the RR named DNA-binding MtrA response regulator protein is most potent drug target. Further, phylogenetic and domain analysis studies of various RRs, deciphers that they share common conserved structural domain regions including some of them having similar active site residues (Asp 56).Structure Based Virtual Screening (SBVS) was performed process using Mcule online drug discovery platform, resulting in identification of top 20 hits against MtrA protein, from which 6 were identified to be good hits basing on toxicity analysis.By ADME studies, among 6 good hits, 2 were found to be most potential candidate hits.
MeSH terms
- Response regulator
- Computational biology
- Mycobacterium tuberculosis
- Regulator
- Biology
- Proteome
- Genetics
- Virtual screening
- Two-component regulatory system
- ADME
- Population
- Drug discovery