Core Proteomic Analysis of Unique Metabolic Pathways of Salmonella enterica for the Identification of Potential Drug Targets

Screening Marine Microbial Metabolites as Promising Inhibitors of Borrelia garinii: A Structural Docking Approach towards Developing Novel Lyme Disease Treatment

Lyme disease caused by the Borrelia species is a growing health concern in many parts of the world. Current treatments for the disease may have side effects, and there is also a need for new therapies that can selectively target the bacteria. Pathogens responsible for Lyme disease include B. burgdorferi, B. afzelii, and B. garinii. In this study, we employed structural docking-based screening to identify potential lead-like inhibitors against the bacterium. We first identified the core essential genome fraction of the bacterium, using 37 strains. Later, we screened a library of lead-like marine microbial metabolites (n = 4730) against the arginine deiminase (ADI) protein of Borrelia garinii. This protein plays a crucial role in the survival of the bacteria, and inhibiting it can kill the bacterium. The prioritized lead compounds demonstrating favorable binding energies and interactions with the active site of ADI were then evaluated for their drug-like and pharmacokinetic parameters to assess their suitability for development as drugs. Results from molecular dynamics simulation (100 ns) and other scoring parameters suggest that the compound CMNPD18759 (common name: aureobasidin; IUPAC name: 2-[(4R,6R)-4,6-dihydroxydecanoyl]oxypropan-2-yl (3S,5R)-3,5-dihydroxydecanoate) holds promise as a potential drug candidate for the treatment of Lyme disease, caused by B. garinii. However, further experimental studies are needed to validate the efficacy and safety of this compound in vivo.

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

Identification of Putative Vaccine and Drug Targets against the Methicillin-Resistant Staphylococcus aureus by Reverse Vaccinology and Subtractive Genomics Approaches

Methicillin-resistant Staphylococcus aureus (MRSA) is an opportunistic pathogen and responsible for causing life-threatening infections. The emergence of hypervirulent and multidrug-resistant (MDR) S. aureus strains led to challenging issues in antibiotic therapy. Consequently, the morbidity and mortality rates caused by S. aureus infections have a substantial impact on health concerns. The current worldwide prevalence of MRSA infections highlights the need for long-lasting preventive measures and strategies. Unfortunately, effective measures are limited. In this study, we focus on the identification of vaccine candidates and drug target proteins against the 16 strains of MRSA using reverse vaccinology and subtractive genomics approaches. Using the reverse vaccinology approach, 4 putative antigenic proteins were identified; among these, PrsA and EssA proteins were found to be more promising vaccine candidates. We applied a molecular docking approach of selected 8 drug target proteins with the drug-like molecules, revealing that the ZINC4235426 as potential drug molecule with favorable interactions with the target active site residues of 5 drug target proteins viz., biotin protein ligase, HPr kinase/phosphorylase, thymidylate kinase, UDP-N-acetylmuramoyl-L-alanyl-D-glutamate-L-lysine ligase, and pantothenate synthetase. Thus, the identified proteins can be used for further rational drug or vaccine design to identify novel therapeutic agents for the treatment of multidrug-resistant staphylococcal infection.

Computational Identification of Essential Enzymes as Potential Drug Targets in Shigella flexneri Pathogenesis Using Metabolic Pathway Analysis and Epitope Mapping

Shigella flexneri is a facultative intracellular pathogen that causes bacillary dysentery in humans. Infection with S. flexneri can result in more than a million deaths yearly and most of the victims are children in developing countries. Therefore, identifying novel and unique drug targets against this pathogen is instrumental to overcome the problem of drug resistance to the antibiotics given to patients as the current therapy. In this study, a comparative analysis of the metabolic pathways of the host and pathogen was performed to identify this pathogen's essential enzymes for the survival and propose potential drug targets. First, we extracted the metabolic pathways of the host, Homo sapiens, and pathogen, S. flexneri, from the KEGG database. Next, we manually compared the pathways to categorize those that were exclusive to the pathogen. Further, all enzymes for the 26 unique pathways were extracted and submitted to the Geptop tool to identify essential enzymes for further screening in determining the feasibility of the therapeutic targets that were predicted and analyzed using PPI network analysis, subcellular localization, druggability testing, gene ontology and epitope mapping. Using these various criteria, we narrowed it down to prioritize 5 novel drug targets against S. flexneri and one vaccine drug targets against all strains of Shigella. Hence, we suggest the identified enzymes as the best putative drug targets for the effective treatment of S. flexneri.

A comparative proteomic approach using metabolic pathways for the identification of potential drug targets against Helicobacter pylori

BACKGROUND

Helicobacter pylori is the most highlighted pathogen across the globe especially in developing countries. Severe gastric problems like ulcers, cancers are associated with H. pylori and its prevalence is widespread. Evolution in the genome and cross-resistance with different antibiotics are the major reason of its survival and pandemic resistance against current regimens.

OBJECTIVES

To prioritize potential drug target against H. pylori by comparing metabolic pathways of its available strains.

METHODS

We used various computational tools to extract metabolic sets of all available (61) strains of H. pylori and performed pan genomics and subtractive genomics analysis to prioritize potential drug target. Additionally, the protein interaction and detailed structure-based studies were performed for further characterization of protein.

RESULTS

We found 41 strains showing similar set of metabolic pathways. However, 19 strains were found with unique set of metabolic pathways. The metabolic set of these 19 strains revealed 83 unique proteins and BLAST against human proteome further funneled them to 38 non-homologous proteins. The druggability and essentiality testing further converged our findings to a single unique protein as a potential drug target against H. pylori.

CONCLUSION

We prioritized one protein-based drug target which upon subject to applied protocol was found as close homolog of the Saccharopine dehydrogenase. Our study has opened further avenues of research regarding the discovery of new drug targets against H. pylori.

Identification of glucosyl-3-phosphoglycerate phosphatase as a novel drug target against resistant strain of Mycobacterium tuberculosis (XDR1219) by using comparative metabolic pathway approach

Tuberculosis (TB) is a major global health challenge. It has been afflicting human for thousands of years and is still severely affecting a huge population. The etiological agent of the disease is Mycobacterium tuberculosis (MTB) that survives in the human host in latent, dormant, and non-replicative state by evading the immune system. It is one of the leading causes of infection related death worldwide. The situation is exacerbated by the massive increase in the resistant strains such as multi-drug resistant TB (MDR-TB) and extensive drug-resistant TB (XDR-TB). The resistance is as severe that it resulted in failure of the current chemotherapy regimens (i.e. anti-tubercular drugs). It is therefore imperative to discover the new anti-tuberculosis drug targets and their potential inhibitors. Current study has made the use of in silico approaches to perform the comparative metabolic pathway analysis of the MTBXDR1219 with the host i.e. H. sapiens. We identified several metabolic pathways which are unique to pathogen only. By performing subtractive genomic analysis 05 proteins as potential drug target are retrieved. This study suggested that the identified proteins are essential for the bacterial survival and non-homolog to the host proteins. Furthermore, we selected glucosyl-3-phosoglycerate phosphatase (GpgP, EC 5.4.2.1) out of the 05 proteins for molecular docking analysis and virtual screening. The protein is involved in the biosynthesis of methylglucose lipopolysaccharides (MGLPs) which regulate the biosynthesis of mycolic acid. Mycolic acid is the building block of the unique cell wall of the MTB which is responsible for the resistance and pathogenicity. A relatively larger library consisting of 10,431 compounds was screened using AutoDock Vina to predict the binding modes and to rank the potential inhibitors. No potent inhibitor against MTB GpgP has been reported yet, therefore ranking of compounds is performed by making a comparison with the substrate i.e. glucosyl-3-phosphoglycerate. The obtained results provide the understanding of underlying mechanism of interactions of ligands with protein. Follow up study will include the study of the Protein-Protein Interactions (PPIs), and to propose the potential inhibitors against them.