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A Systematic In Silico Analysis of the Legionellaceae Family for Identification of Novel Drug Target Candidates.

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The family Legionellaceae consists of Gram-negative bacteria that are widely distributed in aquatic environments around the world. This family consists of a single genus, Legionella, that is recognized as an… Click to show full abstract

The family Legionellaceae consists of Gram-negative bacteria that are widely distributed in aquatic environments around the world. This family consists of a single genus, Legionella, that is recognized as an important cause of community-acquired pneumonia and hospital-acquired pneumonia. Legionella consists of intracellular pathogens, thus cellular pharmacokinetic and pharmacodynamic properties of an antibiotic against these bacteria as well as uptake and subcellular distribution into macrophages should be considered for a successful outcome of disease. Treatment strategies for Legionella infection require a combination of multiple antibiotics. Hence, because of the possible development of resistance to the drugs during therapy, a new alternative targeted therapy is yielding promising results. In this study, a comprehensive in silico target identification pipeline was performed on members of the family Legionellaceae to identify the best targets. Using a homology-based computational pipeline method, new drug targets were identified. Of 4,358 analyzed proteins, 18 proteins, including proteins involved in metabolism (amino acid, energy, and lipid metabolisms), cellular transport, cell division, and cell motility, were selected as the final putative drug targets. These proteins play an important role in the survival and propagation of Legionella infection. In conclusion, homology-based methods could improve the identification of novel drug targets and the drug discovery process, which can potentially be effective for the prevention and treatment of Legionella infections.

Keywords: novel drug; family; drug; identification novel; legionella

Journal Title: Microbial drug resistance
Year Published: 2019

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