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Suppressing Mycobacterium tuberculosis virulence and drug resistance by targeting Eis protein through computational drug discovery.
Kumar, Geethu S; Sahoo, Amaresh Kumar; Ranjan, Nishant; Dwivedi, Vivek Dhar; Agrawal, Sharad.
Afiliação
  • Kumar GS; Centre for Development of Biomaterials and Department of Life Sciences, Sharda School of Basic Sciences and Research, Sharda University, Greater Noida, Uttar Pradesh, 201310, India.
  • Sahoo AK; Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Allahabad, India.
  • Ranjan N; University Centre for Research and Development, Department of Mechanical Engineering, Chandigarh University Gharuan, Mohali, Punjab, India.
  • Dwivedi VD; Center for Global Health Research, Saveetha Institute of Medical and Technical Sciences, Saveetha Medical College and Hospitals, Saveetha University, Chennai, India. vivek_bioinformatics@yahoo.com.
  • Agrawal S; Bioinformatics Research Division, Quanta Calculus, Greater Noida, India. vivek_bioinformatics@yahoo.com.
Mol Divers ; 2024 Aug 03.
Article em En | MEDLINE | ID: mdl-39096353
ABSTRACT
Tuberculosis (TB) remains a critical health threat, particularly with the emergence of multidrug-resistant strains. This demands attention from scientific communities and healthcare professionals worldwide to develop effective treatments. The enhanced intracellular survival (Eis) protein is an acetyltransferase enzyme of Mycobacterium tuberculosis that functions by adding acetyl groups to aminoglycoside antibiotics, which interferes with their ability to bind to the bacterial ribosome, thereby preventing them from inhibiting protein synthesis and killing the bacterium. Therefore, targeting this protein accelerates the chance of restoring the aminoglycoside drug activity, thereby reducing the emergence of drug-resistant TB. For this, we have screened 406,747 natural compounds from the Coconut database against Eis protein. Based on MM/GBSA rescoring binding energy, the top 5 most prominent natural compounds, viz. CNP0187003 (- 96.14 kcal/mol), CNP0176690 (- 93.79 kcal/mol), CNP0136537 (- 92.31 kcal/mol), CNP0398701 (- 91.96 kcal/mol), and CNP0043390 (- 91.60 kcal/mol) were selected. These compounds exhibited the presence of a substantial number of hydrogen bonds and other significant interactions confirming their strong binding affinity with the Eis protein during the docking process. Subsequently, the MD simulation of these compounds exhibited that the Eis-CNP0043390 complex was the most stable, followed by Eis-CNP0187003 and Eis-CNP0176690 complex, further verified by binding free energy calculation, principal component analysis (PCA), and Free energy landscape analysis. These compounds demonstrated the most favourable results in all parameters utilised for this investigation and may have the potential to inhibit the Eis protein. There these findings will leverage computational techniques to identify and develop a natural compound inhibitor as an alternative for drug-resistant TB.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Mol Divers Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Índia País de publicação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Mol Divers Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Índia País de publicação: Holanda