Identification of Putative Drug Targets and Vaccine Candidates for Pathogens Causing Atherosclerosis

Hema, Kanipakam; Priyadarshini, Vani

doi:10.4172/2161-1009.1000175

Cited by 13 publications

(5 citation statements)

References 51 publications

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“…It consists of modules for paralog analysis, non-homolog analysis and essentiality analysis that exclude duplicates proteins, homolog of human and its gut flora proteins from the essential protein dataset [24–26]. Target prioritization module annotates the screened essential protein dataset on druggability and virulence which is essential for pathogen survival as well as pathogenicity [27].…”

Section: Methodsmentioning

confidence: 99%

An in silico approach towards identification of novel drug targets in pathogenic species of Leptospira

et al. 2019

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Leptospirosis is one of the leading zoonotic infections worldwide. As with other infectious diseases, report of antimicrobial resistance to existing therapeutic arsenal poses challenges in the management of disease. Hence, identification of novel drug targets for the pathogen deems essential. Present study used combined approach of comparative and subtractive genomics to identify putative drug targets. Crucial genes of 16 pathogenic Leptospira strains were filtered and subjected to homology search via target identification tool “TiD”. Thereafter, comparative analysis was performed for non-homologous, essential genes to accomplish the broad-spectrum drug target. Consequently, 37 essential genes were found to be conserved in at least 10 strains of Leptospira . Further, prioritization of resultant set of genes revealed 18 were hubs in protein–protein interaction network. Sixteen putative targets among the hub genes were conserved in all strains of Leptospira . Out of sixteen, fourteen were enzymes while 8 were novel and 4 were involved in virulence mechanism. In addition, genome scale metabolic network reconstruction and choke point analysis revealed cobA (porphyrin and chlorophyll metabolism) and thiL (thiamine metabolism) as chokepoints in their respective metabolic pathways. The proposed hub genes could act as putative broad-spectrum drug targets for Leptospira species, however, these putative targets should be validated to ensure them as real one prior to utilizing them for target based lead discovery.

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Section: Methodsmentioning

confidence: 99%

An in silico approach towards identification of novel drug targets in pathogenic species of Leptospira

et al. 2019

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“…In the study of infectious pathogens such as Chlamydophila pneumoniae, Porphyromonas gingivalis and Helicobacter pylori causing Atherosclerosis, a total of 14 interacting drug targets were predicted [58].…”

Section: Fig 1: Interacting and Non-interacting Proteins Of Malassezmentioning

confidence: 99%

Computational Identification of Putative Drug Targets in Malassezia Globosa by Subtractive Genomics and Protein Cluster Network Approach

Subhashini

Jeyam

2017

Int J Pharm Pharm Sci

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Objective: Yeast commonly causes superficial mycoses similar to the dermatophytes. Superficial mycoses were reported with an estimated incidence of ∼140,000,000 cases/year worldwide and most frequently caused by Malassezia globosa and Malassezia furfur. Treatment available for these conditions is limited and with side effects. Moreover, termination of the treatment may result in the reoccurrence of the disease. The objective of this research was to identify the putative drug targets using computational approaches. Methods:The analysis of genome sequence improves the understanding of diseases which leads to better treatment. Comparison of the genome of the pathogen with the host at the molecular level is suitable for performing the sequence based prediction of protein-protein interaction network, which also forms the basis of drug target identification leading to the discovery of new drugs for the improved treatment. Results:Out of 100 pathways of M. globosa, 95 were common to the host and 5 were unique to the pathogen. Total common and unique targets from common pathways are 1704 and 300, respectively. A unique target from unique pathways and 147 from common pathways were nonhomologous targets. From this, 46 targets were screened out as essential and processed in the next phase to identify the clustered targets which resulted with three clusters based on their biological role and subcellular location. Conclusion:In this study, putative drug targets were identified in M. globosa using in silico approaches of subtractive genomics and cluster network which will help in the next level of drug discovery such as lead identification for the novel targets.

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“…In 2019, an estimated 78% of MDR tuberculosis was reported among nearly half a million rifampicin-resistant tuberculosis patients [ 1 ]. In most cases, effective injectable agents could be administered [ 7 ]. Mtb can exhibit either primary (transmitted) resistance or secondary (acquired) resistance [ 6 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

Multi-epitope vaccine against drug-resistant strains of Mycobacterium tuberculosis: a proteome-wide subtraction and immunoinformatics approach

Khan,

Mahmud,

Islam

et al. 2023

Genomics Inform

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Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, one of the most deadly infections in humans. The emergence of multidrug-resistant and extensively drug-resistant Mtb strains presents a global challenge. Mtb has shown resistance to many frontline antibiotics, including rifampicin, kanamycin, isoniazid, and capreomycin. The only licensed vaccine, Bacille Calmette-Guerin, does not efficiently protect against adult pulmonary tuberculosis. Therefore, it is urgently necessary to develop new vaccines to prevent infections caused by these strains. We used a subtractive proteomics approach on 23 virulent Mtb strains and identified a conserved membrane protein (MmpL4, NP_214964.1) as both a potential drug target and vaccine candidate. MmpL4 is a non-homologous essential protein in the host and is involved in the pathogen-specific pathway. Furthermore, MmpL4 shows no homology with anti-targets and has limited homology to human gut microflora, potentially reducing the likelihood of adverse effects and cross-reactivity if therapeutics specific to this protein are developed. Subsequently, we constructed a highly soluble, safe, antigenic, and stable multi-subunit vaccine from the MmpL4 protein using immunoinformatics. Molecular dynamics simulations revealed the stability of the vaccine-bound Toll-like receptor-4 complex on a nanosecond scale, and immune simulations indicated strong primary and secondary immune responses in the host. Therefore, our study identifies a new target that could expedite the design of effective therapeutics, and the designed vaccine should be validated. Future directions include an extensive molecular interaction analysis, in silico cloning, wet-lab experiments, and evaluation and comparison of the designed candidate as both a DNA vaccine and protein vaccine.

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Identification of Putative Drug Targets and Vaccine Candidates for Pathogens Causing Atherosclerosis

Cited by 13 publications

References 51 publications

An in silico approach towards identification of novel drug targets in pathogenic species of Leptospira

An in silico approach towards identification of novel drug targets in pathogenic species of Leptospira

Computational Identification of Putative Drug Targets in Malassezia Globosa by Subtractive Genomics and Protein Cluster Network Approach

Multi-epitope vaccine against drug-resistant strains of Mycobacterium tuberculosis: a proteome-wide subtraction and immunoinformatics approach

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