A Comparative Genomics Approach for Shortlisting Broad-Spectrum Drug Targets in Nontuberculous Mycobacteria

Swain, Aishwarya; Gnanasekar, Pranavathiyani; Prava, Jyoti; Rajeev, Athira C.; Kesarwani, Pragya; Lahiri, Chandrajit; Pan, Archana

doi:10.1089/mdr.2020.0161

Cited by 6 publications

(2 citation statements)

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“…Alternatively, MmpL3 ( Sethiya et al, 2020 ), a transporter crucial for exporting trehalose monomycolates to the periplasmic space and outer membrane, could also be a novel target in treating NTM. A study ( Swain et al, 2021 ) found 15 new targets through screening 537 core proteins that researchers could further utilize to design inhibitors for discovering antimicrobial agents. In addition, some new drug research approaches are equally exciting.…”

Section: Discussionmentioning

confidence: 99%

Treatment of non-tuberculosis mycobacteria skin infections

Wang,

Jia,

2023

Front. Pharmacol.

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Non-tuberculosis mycobacteria (NTM) skin infections have become increasingly prevalent in recent years, presenting a unique challenge in clinical management. This review explored the complexities of NTM infections localized to the superficial tissues and provided valuable insights into the optimal therapeutic strategies. The antibiotic selection should base on NTM species and their susceptibility profiles. It is recommended to adopt a comprehensive approach that considers the unique characteristics of superficial tissues to improve treatment effectiveness and reduce the incidence of adverse reactions, infection recurrence, and treatment failure. Infection control measures, patient education, and close monitoring should complement the treatment strategies to achieve favorable outcomes in managing NTM skin infections. Further efforts are warranted to elucidate factors and mechanisms contributing to treatment resistance and relapse. Future research should focus on exploring novel treatment options, innovative drug development/delivery platforms, and precise methodologies for determining therapeutic duration. Longitudinal studies are also needed to assess the long-term safety profiles of the integrated approaches.

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Section: Discussionmentioning

confidence: 99%

Treatment of non-tuberculosis mycobacteria skin infections

Wang,

Jia,

2023

Front. Pharmacol.

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“…In the light of the rapid development in multi-omic methods, as well as databases curated thereof, the contribution of bioinformatics based studies has been ubiquitous in research efforts on combating multidrug-resistant bacteria (18)(19)(20)(21). For instance, by analysing the bacterial genome or proteome via in silico approaches such as protein interactome analysis, one can unveil novel crucial proteins in the bacteria of interest, which can potentially be vaccine candidates (22)(23)(24). With the increasing entries in experimentally validated 3D structure database, scilicet Protein Data Bank (PDB), the strength of interactions between small molecules and proteins, as well as protein-protein interactions, can now be predicted via in silico approaches (25)(26)(27).…”

Section: Introductionmentioning

confidence: 99%

Promising Acinetobacter baumannii Vaccine Candidates and Drug Targets in Recent Years

Tan

Lahiri

2022

Front. Immunol.

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In parallel to the uncontrolled use of antibiotics, the emergence of multidrug-resistant bacteria, like Acinetobacter baumannii, has posed a severe threat. A. baumannii predominates in the nosocomial setting due to its ability to persist in hospitals and survive antibiotic treatment, thereby eventually leading to an increasing prevalence and mortality due to its infection. With the increasing spectra of drug resistance and the incessant collapse of newly discovered antibiotics, new therapeutic countermeasures have been in high demand. Hence, recent research has shown favouritism towards the long-term solution of designing vaccines. Therefore, being a realistic alternative strategy to combat this pathogen, anti-A. Baumannii vaccines research has continued unearthing various antigens with variable results over the last decade. Again, other approaches, including pan-genomics, subtractive proteomics, and reverse vaccination strategies, have shown promise for identifying promiscuous core vaccine candidates that resulted in chimeric vaccine constructs. In addition, the integration of basic knowledge of the pathobiology of this drug-resistant bacteria has also facilitated the development of effective multiantigen vaccines. As opposed to the conventional trial-and-error approach, incorporating the in silico methods in recent studies, particularly network analysis, has manifested a great promise in unearthing novel vaccine candidates from the A. baumannii proteome. Some studies have used multiple A. baumannii data sources to build the co-functional networks and analyze them by k-shell decomposition. Additionally, Whole Genomic Protein Interactome (GPIN) analysis has utilized a rational approach for identifying essential proteins and presenting them as vaccines effective enough to combat the deadly pathogenic threats posed by A. baumannii. Others have identified multiple immune nodes using network-based centrality measurements for synergistic antigen combinations for different vaccination strategies. Protein-protein interactions have also been inferenced utilizing structural approaches, such as molecular docking and molecular dynamics simulation. Similar workflows and technologies were employed to unveil novel A. baumannii drug targets, with a similar trend in the increasing influx of in silico techniques. This review integrates the latest knowledge on the development of A. baumannii vaccines while highlighting the in silico methods as the future of such exploratory research. In parallel, we also briefly summarize recent advancements in A. baumannii drug target research.

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In silico Methods for Identification of Potential Therapeutic Targets

Zhang

Yang

et al. 2021

Interdiscip Sci Comput Life Sci

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At the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods—comparative genomics and network-based methods—for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery. Graphical abstract

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A Comparative Genomics Approach for Shortlisting Broad-Spectrum Drug Targets in Nontuberculous Mycobacteria

Cited by 6 publications

References 94 publications

Treatment of non-tuberculosis mycobacteria skin infections

Treatment of non-tuberculosis mycobacteria skin infections

Promising Acinetobacter baumannii Vaccine Candidates and Drug Targets in Recent Years

In silico Methods for Identification of Potential Therapeutic Targets

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