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Comprehensive in silico analyses of flavonoids elucidating the drug properties against kidney disease by targeting AIM2.

ABSTRACT: Kidney disorders are among the most common diseases and there is a scarcity of effective treatments for chronic kidney disease. There has been a progressive improvement in specific flavonoids for protective effects against kidney diseases. Flavonoids inhibit the regulatory enzymes to control inflammation-related diseases. In the present study, a hybrid approach of molecular docking analyses and molecular dynamic simulation was followed by principal component analyses and a dynamics cross-correlation matrix. In the present study, the top-ranked five flavonoids were reported, and the maximum binding affinity was observed against AIM2. Molecular docking analyses revealed that Glu_186, Phe_187, Lys_245, Glu_248, Ile_263, and Asn_265 are potent residues against AIM2 for ligand-receptor interactions. Extensive in silico analyses suggested that procyanidin is a potential molecule against AIM2. Moreover, the site-directed mutagenesis for the reported interacting residues of AIM2 could be important for further in vitro analyses. The observed novel results based on extensive computational analyses may be significant for potential drug design against renal disorders by targeting AIM2.

SUBMITTER: Kandeel M

PROVIDER: S-EPMC10194910 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Comprehensive in silico analyses of flavonoids elucidating the drug properties against kidney disease by targeting AIM2.

Kandeel Mahmoud M Iqbal Muhammad Nasir MN Ali Iqra I Malik Saima S Malik Abbeha A Sehgal Sheikh Arslan SA

PloS one 20230518 5

Kidney disorders are among the most common diseases and there is a scarcity of effective treatments for chronic kidney disease. There has been a progressive improvement in specific flavonoids for protective effects against kidney diseases. Flavonoids inhibit the regulatory enzymes to control inflammation-related diseases. In the present study, a hybrid approach of molecular docking analyses and molecular dynamic simulation was followed by principal component analyses and a dynamics cross-correla ...[more]

PMID: 37200367

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Project description:Background: Yuquan Pill (YQW) is a modern concentrated pill preparation of six herbs, namely, Ge Gen (Pueraria lobata Ohwi), Di huang (Rehmannia glutinosa Libosch.), Tian Huafen (Trichosanthes kirilowii Maxim.), Mai Dong (Ophiopogon japonicus (L. f.) Ker Gawl.), Wu Weizi (Schisandra chinensis (Turcz.) Baill.) and Gan Cao (Glycyrrhiza uralensis Fisch.). It is extensively used to treat type 2 diabetes-related glucose and lipid metabolism disorders. But what's the pharmacodynamic substance and how it works in the treatment of Type 2 diabetes mellitus (T2DM) are still unclear. Purpose: The purpose of this study is to determine the likely pharmacological components and molecular mechanism of YQW's intervention on T2DM by combining serum pharmacochemistry, network analysis and transcriptomics. Methods: The efficacy and prototypical components of blood entry were determined after oral administration of YQW aqueous solution to T2DM rats induced by high-fat feed and low-dose streptozotocin (STZ), and the key targets and pathways for these compounds to intervene in T2DM rats were predicted and integrated using network analysis and transcriptomics techniques. Results: In diabetic rats, YQW can lower TG, CHO, NO, and MDA levels (p < 0.05) while increasing HDL-C levels (p < 0.01), and protecting the liver and kidney. 22 prototype components (including puerarin, daidzein, 3'-methoxypuerarin, and liquiritigenin, among others) were found in the serum of rats after oral administration of YQW for 90 min, which might be used as a possible important ingredient for YQW to intervene in T2DM rats. 538 YQW pharmacodynamic components-related targets and 1,667 disease-related targets were projected through the PharmMapper database, with 217 common targets between the two, all of which were engaged in regulating PI3K-Akt, MAPK, Ras and FoxO signal pathway. Finally, the mRNA expression profiles of liver tissues from rats in the control, model, and YQW groups were investigated using high-throughput mRNA sequencing technology. YQW can regulate the abnormal expression of 89 differential genes in a disease state, including 28 genes with abnormally high expression and 61 genes with abnormally low expression. Five common genes (Kit, Ppard, Ppara, Fabp4, and Tymp) and two extensively used regulatory pathways (PI3K-Akt and MAPK signaling pathways) were revealed by the integrated transcriptomics and network analysis study. Conclusion: The mechanism of YQW's intervention in T2DM rats could be linked to 22 important components like puerarin, daidzein, and glycyrrhetinic acid further activating PI3K-Akt and MAPK signaling pathways by regulating key targets Kit, Ppard, Ppara, Fabp4, and Tymp, and thus improving lipid metabolism disorder, oxidative stress, and inflammation levels in T2DM rats. On the topic, more research into the pharmacological ingredient foundation and mechanism of YQW intervention in T2DM rats can be done.

Project description:BackgroundComputational approaches in the identification of drug targets are expected to reduce time and effort in drug development. Advances in genomics and proteomics provide the opportunity to uncover properties of druggable genomes. Although several studies have been conducted for distinguishing drug targets from non-drug targets, they mainly focus on the sequences and functional roles of proteins. Many other properties of proteins have not been fully investigated.MethodsUsing the DrugBank (version 3.0) database containing nearly 6,816 drug entries including 760 FDA-approved drugs and 1822 of their targets and human UniProt/Swiss-Prot databases, we defined 1578 non-redundant drug target and 17,575 non-drug target proteins. To select these non-redundant protein datasets, we built four datasets (A, B, C, and D) by considering clustering of paralogous proteins.ResultsWe first reassessed the widely used properties of drug target proteins. We confirmed and extended that drug target proteins (1) are likely to have more hydrophobic, less polar, less PEST sequences, and more signal peptide sequences higher and (2) are more involved in enzyme catalysis, oxidation and reduction in cellular respiration, and operational genes. In this study, we proposed new properties (essentiality, expression pattern, PTMs, and solvent accessibility) for effectively identifying drug target proteins. We found that (1) drug targetability and protein essentiality are decoupled, (2) druggability of proteins has high expression level and tissue specificity, and (3) functional post-translational modification residues are enriched in drug target proteins. In addition, to predict the drug targetability of proteins, we exploited two machine learning methods (Support Vector Machine and Random Forest). When we predicted drug targets by combining previously known protein properties and proposed new properties, an F-score of 0.8307 was obtained.ConclusionsWhen the newly proposed properties are integrated, the prediction performance is improved and these properties are related to drug targets. We believe that our study will provide a new aspect in inferring drug-target interactions.

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Comprehensive in silico analyses of flavonoids elucidating the drug properties against kidney disease by targeting AIM2.

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Comprehensive in silico analyses of flavonoids elucidating the drug properties against kidney disease by targeting AIM2.

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