Subtractive proteomics revealed plausible drug candidates in the proteome of multi-drug resistant Corynebacterium diphtheriae

Identification of potential inhibitors against Corynebacterium diphtheriae MtrA response regulator protein; an in-silico drug discovery approach

Corynebacterium diphtheriae is a multi-drug resistant bacteria responsible for the life-threatening respiratory illness, diphtheria which can lead to severe Nervous system disorders, mainly infecting the lungs, heart, and kidneys if left untreated. In the current study, Corynebacterium diphtheriae MtrA response regulator protein was targeted, which regulates a two-component system of bacterial pathogenesis, and initiates DNA replication and cell division. In the current study a computational approach have been described for drug development against C. diphtheriae infections by inhibiting MtrA protein by small molecules acting as potential inhibitors against it. Molecular docking analysis of the equilibrated MtrA protein revealed compound-0.2970, compound-0.3029, and compound-0.3016 from Asinex Library as the promising inhibitors based on their lowest binding energies (-9.8 kJ/mol, -9.2 kJ/mol, and -8.9 kJ/mol), highest gold scores (40.53, 47.41, and 48.41), drug-likeness and pharmacokinetic properties. The MD simulation studies of the identified top-ranked inhibitors at 100 ns elucidated the system stability and fluctuations in the binding pocket of MtrA protein. Molecular Dynamics Simulations of the top three docked complexes further revealed that the standard binding pocket was retained ensuring the system stability. The rearrangements of H-bonds, van der Waals, pi-pi, and solid hydrophobic interactions were also observed. The binding free energy calculations (MM/PBSA and MM/GBSA) suggested a fundamental binding capability of the ligand to the target receptor MtrA. Therefore, the current study has provided excellent candidates acting as potent inhibitors for developing therapeutic drugs against C. diphtheriae infections. However, in vivo and in vitro animal experiments and accurate clinical trials are needed to validate the potential inhibitory effect of these compounds.

Identification of potential novel therapeutic drug target against Elizabethkingia anophelis by integrative pan and subtractive genomic analysis: An in silico approach

Elizabethkingia anophelis is a human pathogen responsible for severe nosocomial infections in neonates and immunocompromised patients. The significantly higher mortality rate from E. anophelis infections and the lack of available regimens highlight the critical need to explore novel drug targets. The current study investigated effective novel drug targets by employing a comprehensive in silico subtractive genomic approach integrated with pangenomic analysis of E. anophelis strains. A total of 2809 core genomic proteins were found by pangenomic analysis of non-paralogous proteins. Subsequently, 156 pathogen-specific, 442 choke point, 202 virulence factor, 53 antibiotic resistant and 119 host-pathogen interacting proteins were identified in E. anophelis. By subtractive genomic approach, at first 791 proteins were found to be indispensable for the survival of E. anophelis. 558 and 315 proteins were detected as non-homologous to human and gut microflora respectively. Following that 245 cytoplasmic, 245 novel, and 23 broad-spectrum targets were selected and finally four proteins were considered as potential therapeutic targets of E. anophelis based on highest degree score in PPI network. Among those, three proteins were subjected to molecular docking and subsequent MD simulation as one protein did not contain a plausible binding pocket with sufficient surface area and volume. All the complexes were found to be stable and compact in 100 ns molecular dynamics simulation studies as measured by RMSD, RMSF, and Rg. These three short-listed targets identified in this study may lead to the development of novel antimicrobials capable of curing infections and pave the way to prevent and control the disease progression caused by the deadly agent E. anophelis.

In silico analysis of Leishmania proteomes and protein-protein interaction network: Prioritizing therapeutic targets and drugs for repurposing to treat leishmaniasis

Leishmaniasis is a serious world health problem and its current therapies have several limitations demanding to develop novel therapeutics for this disease. The present study aims to prioritize novel broad-spectrum targets using proteomics and protein-protein interaction network (PPIN) data for 11 Leishmania species. Proteome comparison and host non-homology analysis resulted in 3605 pathogen-specific conserved core proteins. Gene ontology analysis indicated their involvement in major molecular functions like DNA binding, transportation, dioxygenase, and catalytic activity. PPIN analysis of these core proteins identified eight hub proteins (viz., vesicle-trafficking protein (LBRM2903_190011800), ribosomal proteins S17 (LBRM2903_34004790) and L2 (LBRM2903_080008100), eukaryotic translation initiation factor 3 (LBRM2903_350086700), replication factor A (LBRM2903_150008000), U3 small nucleolar RNA-associated protein (LBRM2903_340025600), exonuclease (LBRM2903_200021800), and mitochondrial RNA ligase (LBRM2903_200074100)). Among the hub proteins, six were classified as drug targets and two as vaccine candidates. Further, druggability analysis indicated three hub proteins, namely eukaryotic translation initiation factor 3, ribosomal proteins S17 and L2 as druggable. Their three-dimensional structures were modelled and docked with the identified ligands (2-methylthio-N6-isopentenyl-adenosine-5'-monophosphate, artenimol and omacetaxine mepesuccinate). These ligands could be experimentally validated (in vitro and in vivo) and repurposed for the development of novel antileishmanial agents.

Comparative Metabolic Pathways Analysis and Subtractive Genomics Profiling to Prioritize Potential Drug Targets Against Streptococcus pneumoniae

Streptococcus pneumoniae is a notorious pathogen that affects ∼450 million people worldwide and causes up to four million deaths per annum. Despite availability of antibiotics (i.e., penicillin, doxycycline, or clarithromycin) and conjugate vaccines (e.g., PCVs), it is still challenging to treat because of its drug resistance ability. The rise of antibiotic resistance in S. pneumoniae is a major source of concern across the world. Computational subtractive genomics is one of the most applied techniques in which the whole proteome of the bacterial pathogen is gradually reduced to a limited number of potential therapeutic targets. Whole-genome sequencing has greatly reduced the time required and provides more opportunities for drug target identification. The goal of this work is to evaluate and analyze metabolic pathways in serotype 14 of S. pneumonia to identify potential drug targets. In the present study, 47 potent drug targets were identified against S. pneumonia by employing the computational subtractive genomics approach. Among these, two proteins are prioritized (i.e., 4-oxalocrotonate tautomerase and Sensor histidine kinase uniquely present in S. pneumonia) as novel drug targets and selected for further structure-based studies. The identified proteins may provide a platform for the discovery of a lead drug candidate that may be capable of inhibiting these proteins and, therefore, could be helpful in minimizing the associated risk related to the drug-resistant S. pneumoniae. Finally, these enzymatic proteins could be of prime interest against S. pneumoniae to design rational targeted therapy.

Mining the Proteome of Streptococcus mutans for Putative Drug Targets

BACKGROUND

Dental caries is the most common and one of the prevalent diseases in the world. Streptococcus mutans is one of the major oral pathogens that cause dental caries by forming a biofilm on dental tissues, degrading dental enamel and consequent cavitation in the tissue. In vitro selection of drug targets is a laborious and expensive process and therefore, computational methods are preferable for target identification at the initial stage.

OBJECTIVE

The present research aims to find new drug targets in S. mutans by using subtractive proteomics analysis, which implements various bioinformatics tools and databases.

METHODS

The proteome of S. mutans UA159 was mined for novel drug targets using computational tools and databases such as: CD-HIT, BLASTP, DEG, KAAS and CELL2GO.

RESULTS

Out of 1953 proteins of S. mutans UA159, proteins that are redundant, homologous to human and non-essential to the pathogen were eliminated. Around 178 proteins already available in drug target repositories were also eliminated. Possible functions and subcellular localization of 32 uncharacterized proteins were predicted. Substantially, 13 proteins were identified as novel drug targets in S. mutans UA159 that can be targeted by various drugs against dental caries.

CONCLUSION

This study will effectuate the development of novel therapeutic agents against dental caries and other Streptococcal infections.

A systematic strategy for the investigation of vaccines and drugs targeting bacteria

Infectious and epidemic diseases induced by bacteria have historically caused great distress to people, and have even resulted in a large number of deaths worldwide. At present, many researchers are working on the discovery of viable drug and vaccine targets for bacteria through multiple methods, including the analyses of comparative subtractive genome, core genome, replication-related proteins, transcriptomics and riboswitches, which plays a significant part in the treatment of infectious and pandemic diseases. The 3D structures of the desired target proteins, drugs and epitopes can be predicted and modeled through target analysis. Meanwhile, molecular dynamics (MD) analysis of the constructed drug/epitope-protein complexes is an important standard for testing the suitability of these screened drugs and vaccines. Currently, target discovery, target analysis and MD analysis are integrated into a systematic set of drug and vaccine analysis strategy for bacteria. We hope that this comprehensive strategy will help in the design of high-performance vaccines and drugs.