Integrated computer-aided drug design and biophysical simulation approaches to determine natural anti-bacterial compounds for Acinetobacter baumannii

结合计算机辅助药物设计和生物物理模拟方法,筛选鲍曼不动杆菌的天然抗菌化合物

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Abstract

Acinetobacter baumannii is a nosocomial bacterial pathogen and is responsible for a wide range of diseases including pneumonia, necrotizing fasciitis, meningitis, and sepsis. The enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase (encoded by aroA gene) in ESKAPE pathogens catalyzes the sixth step of shikimate pathway. The shikimate pathway is an attractive drug targets pathway as it is present in bacteria but absent in humans. As EPSP is essential for the A. baumannii growth and needed during the infection process, therefore it was used as a drug target herein for high-throughput screening of a comprehensive marine natural products database (CMNPD). The objective was to identify natural molecules that fit best at the substrate binding pocket of the enzyme and interact with functionally critical residues. Comparative assessment of the docking scores allowed selection of three compounds namely CMNPD31561, CMNPD28986, and CMNPD28985 as best binding molecules. The molecules established a balanced network of hydrophobic and hydrophilic interactions, and the binding pose remained in equilibrium throughout the length of molecular simulation time. Radial distribution function (RDF) analysis projected key residues from enzyme active pocket which actively engaged the inhibitors. Further validation is performed through binding free energies estimation that affirms very low delta energy of <-22 kcal/mol in MM-GBSA method and <-12 kcal/mol in MM-PBSA method. Lastly, the most important active site residues were mutated and their ligand binding potential was re-investigated. The molecules also possess good druglike properties and better pharmacokinetics. Together, these findings suggest the potential biological potency of the leads and thus can be used by experimentalists in vivo and in vitro studies.

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