基于泛基因组学和消减蛋白质组学技术筛选金黄色葡萄球菌新型抗菌靶点及其药物的分子对接分析

doi:10.13481/j.1671-587X.20240411

Abstract

Abstract:

Objective To use pan-genomics and subtractive proteomics techniques to screen the new antibacterial targets from the Staphylococcus aureus genome， and to lay the foundation for the development of anti-Staphylococcus aureus drugs. Methods The genome sequencing data of 50 strains with sequencing level Complete were collected by searching the whole genome sequencing data in the National Center for Biotechnology Information （NCBI） Database with Staphylococcus aureus as the keyword；BPGA tool was used to conduct the pan-genomics analysis on the genomic data to obtain the core genes of Staphylococcus aureus； subtractive proteomics technique was used to screen the potential antibacterial targets from the core genes. These potential antibacterial targets were used as the receptors； LibDock software was used to screen the potential anti-Staphylococcus aureus drugs from the US Food and Drug Administration （FDA）-approved drug library； molecular docking technology was used to analyze the binding abilities of the drugs and targets. Results There were 14 379 gene families in the 50 Staphylococcus aureus genomes， of which 1 620 were the core genes. The subtractive proteomics analysis results showed that tyrosine autokinase 1335 was the potential anti-Staphylococcus aureus target. LibDock software screened out nine compounds， including balofloxacin， tenofovir disoproxil fumarate， and adefovir， that may exert anti-Staphylococcus aureus effects on this target protein. The molecular docking results showed there was good binding abilities between the targets and the compounds. Conclusion Tyrosine autokinase may be the potential target for anti-Staphylococcus aureus.

Key words: Staphylococcus aureus, Pan-genome, Molecular docking, Subtractive proteome

CLC Number:

R378.1

Jinli TAN,Dan HUANG,Jingyang LIAO,Liuchong ZHU,Wenbin LIU. Molecular docking analysis on screening of novel antibacterial targets and their drugs of Staphylococcus aureus based on pan-genomics and subtractive proteomics techniques[J].Journal of Jilin University(Medicine Edition), 2024, 50(4): 970-977.

Figures/Tables 7

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References 32

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Gene ID	Protein	Amino acid number	Molecular weight（×10³）	pI	Aliphatic index	GRAVY	Cell localization
Gene576	Thermonuclease family protein	228	25.15	9.2	81.32	-0.350	Extracellular
Gene474	Bifunctional autolysin	1 260	137.88	9.6	67.98	-0.621	Extracellular
Gene1335	Tyrosine autokinase	230	25.25	5.45	88.61	-0.247	Cytoplasmic membrane
Gene1015	Type 8 capsular polysaccharide synthesis protein	185	21.06	9.28	103.73	-0.104	Cytoplasmic membrane
Gene2511	Delta-haemolysin precurser	45	5.14	9.03	142.89	0.827	Unknown
Gene2085	Manganese-dependent protein-tyrosine phosphatase	255	28.92	7.83	101.33	-0.252	Cytoplasmic
Gene2294	Capsular polysaccharide type 5/8 biosynthesis protein CapA	222	24.85	9.2	118.02	0.087	Cytoplasmic membrane
Gene66	Thermonuclease family protein	177	20.33	9.68	77.01	-0.691	Extracellular

Compound ID	Compound name	LibDock score	Biological activity
ZINC000060183170	Paromomycin	168.972	Antibacterial^[15]
ZINC000003929022	Tenofovir Disoproxil	164.924	-
ZINC000003930376	Adefovir dipivoxil	157.219	-
ZINC000003830635	Deferoxamine	153.865	Antibacterial^[16]
ZINC000001540998	Pemetrexed	152.596	-
ZINC000008214483	Ciprofloxacin	151.885	Antibacterial^[17]
ZINC000001529323	Methotrexate	151.268	Antibacterial^[18]
ZINC000018324776	Vardenafil	147.649	Decrease antibacterial activity
ZINC000003794794	Mitoxantrone	144.891	-

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Molecular docking analysis on screening of novel antibacterial targets and their drugs of Staphylococcus aureus based on pan-genomics and subtractive proteomics techniques

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