Subtractive genomics profiling for potential drug targets identification against Moraxella catarrhalis

Abstract

Moraxella catarrhalis (M. catarrhalis) is a gram-negative bacterium, responsible for major respiratory tract and middle ear infection in infants and adults. The recent emergence of the antibiotic resistance M. catarrhalis demands the prioritization of an effective drug target as a top priority. Fortunately, the failure of new drugs and host toxicity associated with traditional drug development approaches can be avoided by using an in silico subtractive genomics approach. In the current study, the advanced in silico genome subtraction approach was applied to identify potential and pathogen-specific drug targets against M. catarrhalis. We applied a series of subtraction methods from the whole genome of pathogen based on certain steps i.e. paralogous protein that have extensive homology with humans, essential, drug like, non-virulent, and resistant proteins. Only 38 potent drug targets were identified in this study. Eventually, one protein was identified as a potential new drug target and forwarded to the structure-based studies i.e. histidine kinase (UniProt ID: D5VAF6). Furthermore, virtual screening of 2000 compounds from the ZINC database was performed against the histidine kinase that resulted in the shortlisting of three compounds as the potential therapeutic candidates based on their binding energies and the properties exhibited using ADMET analysis. The identified protein gives a platform for the discovery of a lead drug candidate that may inhibit it and may help to eradicate the otitis media caused by drug-resistant M. catarrhalis. Nevertheless, the current study helped in creating a pipeline for drug target identification that may assist wet-lab research in the future.

Fig 1. Flow chart: A general sketch of the current study integrated with the use of various computational approaches and tools to identify potential drug targets against M. catarrhalis BBH18.

Fig 2

Subcellular localization: (A) Psortb results showing the subcellular distribution of 38 essential proteins identified in M. catarrhalis (B) CELLO2GO results showing the subcellular distribution of 38 essential proteins identified in M. catarrhalis.

Fig 3. Current study summary for target protein identification: Stepwise analysis of subtractive genomic approach for drug targets identification in M. catarrhalis.

Fig 4

(A) Modeled Structure of Proteins (drug targets): Structure modeled through Homology SWISS modeler for sensor histidine kinases using 4biz as respective template. (B) Template Protein and Modelled Protein: Superimpose protein of histidine kinase with template protein in slenna color and modelled protein in medium purple. (C) Protein sequence alignment of modelled protein i.e. histidine kinase and template protein i.e. 4biz generated through clustal omega showing sequence similarity.

Fig 5

A. Predicted Active Site for histidine kinase: i.e. depicted by R423 (1.330 Å), L461 (1.550 Å), E407 (1.546 Å), R428 (1.339 Å) and I417 (1.548 Å) residues. B. Pre-Docked and Post Docked Protein: the superimposed docked complex of pre docked ADP (in dark khaki) over post docked (in aqua) highlighting the accuracy of docking study in terms of RMSD indicated as 1.660 Å.

Fig 6

(A) Virtual screening of 2000 compounds, (B) identified leads like compounds, (C) and proposed leads compounds in current study.

Fig 7

Redocked compound incorporating the modelled protein: (A) For ZINC09185674, (B) ZINC03839141, (C) ZINC00631248 and (D) Reference Protein.

Fig 8. Protein-protein interactions: Schematic PPI network generated through the STRING database for histidine kinase.