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      Potential molecular mechanism of the Xiexin capsule in the intervention of dyslipidemia based on bioinformatics and molecular docking Translated title: Posible mecanismo molecular de la cápsula Xiexin en la intervención de la dislipidemia basada en la bioinformática y el acoplamiento molecular

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          Abstract

          Abstract Objective: bioinformatic methods and molecular docking technology were used to predict the active components, targets, and related biological pathways of the Xiexin capsule in the intervention for dyslipidemia, exploring its mechanism. Methods: the active components and targets of the Xiexin capsule were screened by the TCMSP (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform )database. Genecards (The Human Gene Database), OMIM (Online Mendelian Inheritance in Man), PharmGkb (Pharmacogenomics Knowledge Base database), TTD (Therapeutic Target Database), and Drugbank platforms were used to search the disease targets of dyslipidemia. The Cytoscape 3.8.0 software was used to construct the 'component-target' network diagram, and the STRING (functional protein association networks) platform was used to analyze protein-protein interaction (PPI). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG) enrichment analyses were performed by R language data packets to predict the mechanism of action. The AutoDockVina and PyMol software were used to dock the key active components in the Xiexin capsule and the core proteins in PPI. Results: a total of 66 effective components were screened, involving 114 targets; 87 key active compounds were screened from the 'drug-component-target' diagram. The PPI network mainly involved core proteins such as PTGS2 (prostaglandin-endoperoxide synthase 2), PTGS1 (prostaglandin-endoperoxide synthase 1), and HSP90AA1 (heat shock protein 90 alpha family class A member 1). GO and KEGG enrichment analysis results of common targets mainly involved hormone-mediated signaling pathway, steroid hormone response, lipid transport and metabolism, regulation of cholesterol storage, cyclooxygenase pathway, and other biological pathways, as well asMM PPAR (peroxisome proliferators-activated receptor) signaling pathway, IL-17 (interleukin 17) signaling pathway, PI3K-Akt (protein kinase b) signaling pathway, FcεRI signaling pathway, and other related pathways. Molecular docking verification showed that quercetin had the best binding with the core target protein HSP90AA1, and HSP90AA1 was the target protein with the best binding activity for the key chemical components in Xiexin capsules. Conclusion: the main chemical components in the Xiexin capsules may participate in the regulation of PPAR and other signaling pathways by regulating key genes such as ESR1 (estrogen receptor 1), MAPK14 (mitogen-activated protein kinase 14), and HSP90AA1, to exert the pharmacological effect of the intervention on dyslipidemia.

          Translated abstract

          Resumen Objetivo: se utilizaron métodos bioinformáticos y técnicas de acoplamiento molecular para predecir los componentes efectivos, los objetivos y las vías biológicas relacionadas de la cápsula Xiexin en la intervención de la dislipidemia y explorar su mecanismo. Métodos: los componentes activos y los objetivos de la cápsula Xiexin fueron seleccionados por la base de datos TCMSP. Se utilizaron las plataformas Genecards, OMIM, PharmGkb, TTD (Therapeutic Target Database) y Drugbank para buscar las dianas de la enfermedad en la dislipidemia. El diagrama reticular “componente-diana” fue construido por el software Cytoscape 3.7.0, y la interacción proteína-proteína (PPI) fue analizada por la plataforma STRING. Los análisis de enriquecimiento de Gene Ontology (GO) y Kyoto Encyclopedia of Genes and Genomics (KEGG) se realizaron mediante paquetes de datos en lenguaje R para predecir el mecanismo de acción. El software AutoDockVina y PyMol se utilizó para unir los componentes activos clave de la cápsula Xiexin y las proteínas clave de la PPI. Resultados: se seleccionaron 65 componentes activos y 114 dianas. Veintitrés compuestos activos clave fueron seleccionados a partir de la tabla “componentes farmacéuticos-dianas”. Las redes PPI incluyen principalmente proteínas básicas como PTGS2, PTGS1 y HSP90AA1. Los resultados del análisis de enriquecimiento de GO y KEGG en los objetivos comunes se refieren principalmente a la vía de señalización mediada por esteroides, la respuesta hormonal esteroidea, el transporte y metabolismo lipídicos, la regulación del almacenamiento de colesterol, la vía de la ciclooxigenasa y otras vías biológicas, así como la vía de señalización de PPAR, la vía de señalización de IL-17, la vía de señalización de PI3K-Akt, la vía de señalización de FcnnnnnnnnRI y otras vías relacionadas. La prueba de acoplamiento molecular mostró que la quercetina se une mejor a la proteína diana central HSP90AA1, que es la proteína diana con la mejor actividad de unión de los componentes químicos clave de la cápsula Xiexin. Conclusión: los principales componentes químicos de la cápsula Xiexin pueden participar en la regulación de la PPAR y otras vías de señalización mediante la regulación de genes clave como ESR1, MAPK14 (mitogen-activated protein kinase 14), HSP90AA1, por lo que pueden desempeñar un papel farmacológico en la intervención de la dislipidemia.

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          Most cited references42

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          2016 ESC/EAS Guidelines for the Management of Dyslipidaemias.

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            A Novel Chemometric Method for the Prediction of Human Oral Bioavailability

            Orally administered drugs must overcome several barriers before reaching their target site. Such barriers depend largely upon specific membrane transport systems and intracellular drug-metabolizing enzymes. For the first time, the P-glycoprotein (P-gp) and cytochrome P450s, the main line of defense by limiting the oral bioavailability (OB) of drugs, were brought into construction of QSAR modeling for human OB based on 805 structurally diverse drug and drug-like molecules. The linear (multiple linear regression: MLR, and partial least squares regression: PLS) and nonlinear (support-vector machine regression: SVR) methods are used to construct the models with their predictivity verified with five-fold cross-validation and independent external tests. The performance of SVR is slightly better than that of MLR and PLS, as indicated by its determination coefficient (R 2) of 0.80 and standard error of estimate (SEE) of 0.31 for test sets. For the MLR and PLS, they are relatively weak, showing prediction abilities of 0.60 and 0.64 for the training set with SEE of 0.40 and 0.31, respectively. Our study indicates that the MLR, PLS and SVR-based in silico models have good potential in facilitating the prediction of oral bioavailability and can be applied in future drug design.
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              Statin Toxicity

              There is now overwhelming evidence to support lowering LDL-c (low-density lipoprotein cholesterol) to reduce cardiovascular morbidity and mortality. Statins are a class of drugs frequently prescribed to lower cholesterol. However, in spite of their wide-spread use, discontinuation and nonadherence remains a major gap in both the primary and secondary prevention of atherosclerotic cardiovascular disease. The major reason for statin discontinuation is because of the development of statin-associated muscle symptoms, but a range of other statin-induced side effects also exist. Although the mechanisms behind these side effects have not been fully elucidated, there is an urgent need to identify those at increased risk of developing side effects as well as provide alternative treatment strategies. In this article, we review the mechanisms and clinical importance of statin toxicity and focus on the evaluation and management of statin-associated muscle symptoms.
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                Author and article information

                Journal
                nh
                Nutrición Hospitalaria
                Nutr. Hosp.
                Grupo Arán (Madrid, Madrid, Spain )
                0212-1611
                1699-5198
                June 2022
                : 39
                : 3
                : 569-579
                Affiliations
                [3] Beijing Beijing orgnameBeijing University of Chinese Medicine orgdiv1School of Chinese Medicine China
                [1] Changsha Hunan orgnameHunan University of Chinese Medicine People's Republic of China
                [2] Changsha Hunan orgnameHunan University of Chinese Medicine orgdiv1The First Affiliated Hospital People's Republic of China
                Article
                S0212-16112022000400012 S0212-1611(22)03900300012
                10.20960/nh.03918
                7c1a5169-6423-4314-bcb2-291510673c60

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

                History
                : 24 December 2021
                : 25 October 2021
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 43, Pages: 11
                Product

                SciELO Spain

                Categories
                Original Papers

                Cápsula Xiexin,Dislipidemia,Bioinformática,Molecular mechanism,Mecanismo molecular,Xiexin capsule,Dyslipidemia,Bioinformatics

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