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Structural systems pharmacology: A framework for integrating metabolic network and structure-based virtual screening for drug discovery against bacteria.

ABSTRACT: Advances in genome-scale metabolic models (GEMs) and computational drug discovery have caused the identification of drug targets at the system-level and inhibitors to combat bacterial infection and drug resistance. Here we report a structural systems pharmacology framework that integrates the GEM and structure-based virtual screening (SBVS) method to identify drugs effective for Escherichia coli infection. The most complete genome-scale metabolic reconstruction integrated with protein structures (GEM-PRO) of E. coli, iML1515_GP, and FDA-approved drugs have been used. FBA was performed to predict drug targets in silico. The 195 essential genes were predicted in the rich medium. The subsystems in which a significant number of these genes are involved are cofactor, lipopolysaccharide (LPS) biosynthesis that are necessary for cell growth. Therefore, some proteins encoded by these genes are responsible for the biosynthesis and transport of LPS which is the first line of defense against threats. So, these proteins can be potential drug targets. The enzymes with experimental structure and cognate ligands were selected as final drug targets for performing the SBVS method. Finally, we have suggested those drugs that have good interaction with the selected proteins as drug repositioning cases. Also, the suggested molecules could be promising lead compounds. This framework may be helpful to fill the gap between genomics and drug discovery. Results show this framework suggests novel antibacterials that can be subjected to experimental testing soon and it can be suitable for other pathogens.

SUBMITTER: Nazarshodeh E

PROVIDER: S-EPMC8670682 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background The limited therapeutic outcomes of atherosclerosis (AS) have allowed, traditional Chinese medicine has been well established as an alternative approach in ameliorating AS and associated clinical syndromes. Clinically, Tongsaimai tablet (TSMT), a commercial Chinese patent medicine approved by CFDA, shows an obvious therapeutic effect on AS treatment. However, its effective mechanism and quality control still need thorough and urgent exploration. Methods The mice were orally administered with TSMT and their serum was investigated for the absorbed compounds using serum pharmacochemistry via the UPLC-Q-Exactive Orbitrap/MS analysis was employed to investigate these absorbed compounds in serum of mice orally administrated with TSMT. Based on these absorbed prototype compounds in serum derived from TSMT, a component-target-disease network was constructed using network pharmacology strategy, which elucidated the potential bioactive components, effective targets, and molecular mechanisms of TSMT against AS. Further, the screened compounds from the component-target network were utilized as the quality control (QC) markers, determining multi-component content determination and HPLC fingerprint to assess quality of nine batches of TSMT samples. Results A total of 164 individual components were identified in TSMT. Among them, 29 prototype compounds were found in serum of mice administrated with TSMT. Based on these candidate prototype components, 34 protein targets and 151 pathways related to AS were predicted, and they might significantly exhibit potential anti-AS mechanisms via synergistic regulations of lipid regulation, shear stress, and anti-inflammation, etc. Five potentially bioactive ingredients in TSMT, including Ferulic acid, Liquiritin, Senkyunolide I, Luteolin and Glycyrrhizic acid in quantity not less than 1.2798, 0.4716, 0.5419, 0.1349, 4.0386 mg/g, respectively, screened from the component-target-pathway network. Thereby, these indicated that these five compounds of TMST which played vital roles in the attenuation of AS could serve as crucial marker compounds for quality control. Conclusions Overall, based on the combination of serum pharmacochemistry and network pharmacology, the present study firstly provided a useful strategy to establish a quality assessment approach for TSMT by screening out the potential anti-AS mechanisms and chemical quality markers. Graphical Abstract Supplementary Information The online version contains supplementary material available at 10.1186/s13020-022-00658-9.

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Structural systems pharmacology: A framework for integrating metabolic network and structure-based virtual screening for drug discovery against bacteria.

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