Academic Journal
IDENTIFICATION OF THERAPEUTIC TARGETS FOR POLYCYSTIC OVARY SYNDROME USING NETWORK PHARMACOLOGY AND COMPUTER SIMULATIONS.
| Τίτλος: | IDENTIFICATION OF THERAPEUTIC TARGETS FOR POLYCYSTIC OVARY SYNDROME USING NETWORK PHARMACOLOGY AND COMPUTER SIMULATIONS. |
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| Συγγραφείς: | ZAFAR, ISHA, MALIK, MUNAZZAH, MUBASHER, MIAN MUHAMMAD, TARIQ, MUHAMMAD, ALI, QURBAN, AHMAD, AJAZ, BILAL, MUHAMMAD, HAN, SHIMING |
| Πηγή: | Farmacia; Jul/Aug2024, Vol. 72 Issue 4, p893-905, 13p |
| Θεματικοί όροι: | Polyendocrine metabolic ovarian syndrome, Molecular dynamics, Molecular docking, Protein-protein interactions, Computer networks |
| Abstract (English): | This research aimed to identify therapeutic targets for polycystic ovary syndrome (PCOS) using network pharmacology. Phytochemicals were screened for ADMET properties and potential targets using Swiss Target Prediction, GeneCards and DisGNet. Enrichment analysis was performed with DAVID, and protein interactions visualized with Cytoscape. A Drug- Compounds-Genes-Disease network identified key therapeutic genes, which were further validated by molecular docking and 200 ns molecular dynamics simulations using GROMACS. The study identified three target genes (ESR1, PPARG and EGFR) and two phytochemicals (6 Prenylnaringenin and Schisandrol A) with potential therapeutic abilities for PCOS. Strong binding interactions between these targets and phytochemicals suggest their potential in PCOS treatment. MD simulations validated these findings. ESR1, EGFR and PPARG play significant roles in PCOS pathophysiology, highlighting their relevance as therapeutic targets. [ABSTRACT FROM AUTHOR] |
| Abstract (Romanian): | Acest studiu a urmărit identificarea ţintelor terapeutice pentru sindromul ovarului polichistic (SOPC) utilizând farmacologia de reţea. Compuşii fitochimici au fost examinaţi pentru proprietăţile ADMET şi potenţiale ţinte utilizând Swiss Target Prediction, GeneCards şi DisGNet. Studiul a utilizat baza de date DAVID, iar interacţiunile proteice au fost vizualizate cu Cytoscape. O reţea medicament-compuşi-gene-boli a identificat gene terapeutice cheie, care au fost validate în continuare prin docking molecular şi simulări de dinamică moleculară 200 ns utilizând GROMACS. Studiul a identificat trei gene ţintă (ESR1, PPARG şi EGFR) şi două fitocompuşi (6 Prenylnaringenin şi Schisandrol A) cu potenţial terapeutic pentru SOPC. Interacţiunile puternice de legare dintre aceste ţinte şi fitocompuşi sugerează potenţialul lor în tratamentul SOPC. Simulările MD au validat aceste constatări. ESR1, EGFR şi PPARG sunt implicate în fiziopatologia SOPC, subliniind relevanţa lor ca ţinte terapeutice. [ABSTRACT FROM AUTHOR] |
| Copyright of Farmacia is the property of Societatea de Stiinte Farmaceutice Romania and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: IDENTIFICATION OF THERAPEUTIC TARGETS FOR POLYCYSTIC OVARY SYNDROME USING NETWORK PHARMACOLOGY AND COMPUTER SIMULATIONS. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22ZAFAR%2C+ISHA%22">ZAFAR, ISHA</searchLink><br /><searchLink fieldCode="AR" term="%22MALIK%2C+MUNAZZAH%22">MALIK, MUNAZZAH</searchLink><br /><searchLink fieldCode="AR" term="%22MUBASHER%2C+MIAN+MUHAMMAD%22">MUBASHER, MIAN MUHAMMAD</searchLink><br /><searchLink fieldCode="AR" term="%22TARIQ%2C+MUHAMMAD%22">TARIQ, MUHAMMAD</searchLink><br /><searchLink fieldCode="AR" term="%22ALI%2C+QURBAN%22">ALI, QURBAN</searchLink><br /><searchLink fieldCode="AR" term="%22AHMAD%2C+AJAZ%22">AHMAD, AJAZ</searchLink><br /><searchLink fieldCode="AR" term="%22BILAL%2C+MUHAMMAD%22">BILAL, MUHAMMAD</searchLink><br /><searchLink fieldCode="AR" term="%22HAN%2C+SHIMING%22">HAN, SHIMING</searchLink> – Name: TitleSource Label: Source Group: Src Data: Farmacia; Jul/Aug2024, Vol. 72 Issue 4, p893-905, 13p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Polyendocrine+metabolic+ovarian+syndrome%22">Polyendocrine metabolic ovarian syndrome</searchLink><br /><searchLink fieldCode="DE" term="%22Molecular+dynamics%22">Molecular dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Molecular+docking%22">Molecular docking</searchLink><br /><searchLink fieldCode="DE" term="%22Protein-protein+interactions%22">Protein-protein interactions</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+networks%22">Computer networks</searchLink> – Name: AbstractNonEng Label: Abstract (English) Group: Ab Data: This research aimed to identify therapeutic targets for polycystic ovary syndrome (PCOS) using network pharmacology. Phytochemicals were screened for ADMET properties and potential targets using Swiss Target Prediction, GeneCards and DisGNet. Enrichment analysis was performed with DAVID, and protein interactions visualized with Cytoscape. A Drug- Compounds-Genes-Disease network identified key therapeutic genes, which were further validated by molecular docking and 200 ns molecular dynamics simulations using GROMACS. The study identified three target genes (ESR1, PPARG and EGFR) and two phytochemicals (6 Prenylnaringenin and Schisandrol A) with potential therapeutic abilities for PCOS. Strong binding interactions between these targets and phytochemicals suggest their potential in PCOS treatment. MD simulations validated these findings. ESR1, EGFR and PPARG play significant roles in PCOS pathophysiology, highlighting their relevance as therapeutic targets. [ABSTRACT FROM AUTHOR] – Name: AbstractNonEng Label: Abstract (Romanian) Group: Ab Data: Acest studiu a urmărit identificarea ţintelor terapeutice pentru sindromul ovarului polichistic (SOPC) utilizând farmacologia de reţea. Compuşii fitochimici au fost examinaţi pentru proprietăţile ADMET şi potenţiale ţinte utilizând Swiss Target Prediction, GeneCards şi DisGNet. Studiul a utilizat baza de date DAVID, iar interacţiunile proteice au fost vizualizate cu Cytoscape. O reţea medicament-compuşi-gene-boli a identificat gene terapeutice cheie, care au fost validate în continuare prin docking molecular şi simulări de dinamică moleculară 200 ns utilizând GROMACS. Studiul a identificat trei gene ţintă (ESR1, PPARG şi EGFR) şi două fitocompuşi (6 Prenylnaringenin şi Schisandrol A) cu potenţial terapeutic pentru SOPC. Interacţiunile puternice de legare dintre aceste ţinte şi fitocompuşi sugerează potenţialul lor în tratamentul SOPC. Simulările MD au validat aceste constatări. ESR1, EGFR şi PPARG sunt implicate în fiziopatologia SOPC, subliniind relevanţa lor ca ţinte terapeutice. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Farmacia is the property of Societatea de Stiinte Farmaceutice Romania and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.31925/farmacia.2024.4.18 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 893 Subjects: – SubjectFull: Polyendocrine metabolic ovarian syndrome Type: general – SubjectFull: Molecular dynamics Type: general – SubjectFull: Molecular docking Type: general – SubjectFull: Protein-protein interactions Type: general – SubjectFull: Computer networks Type: general Titles: – TitleFull: IDENTIFICATION OF THERAPEUTIC TARGETS FOR POLYCYSTIC OVARY SYNDROME USING NETWORK PHARMACOLOGY AND COMPUTER SIMULATIONS. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: ZAFAR, ISHA – PersonEntity: Name: NameFull: MALIK, MUNAZZAH – PersonEntity: Name: NameFull: MUBASHER, MIAN MUHAMMAD – PersonEntity: Name: NameFull: TARIQ, MUHAMMAD – PersonEntity: Name: NameFull: ALI, QURBAN – PersonEntity: Name: NameFull: AHMAD, AJAZ – PersonEntity: Name: NameFull: BILAL, MUHAMMAD – PersonEntity: Name: NameFull: HAN, SHIMING IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul/Aug2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 00148237 Numbering: – Type: volume Value: 72 – Type: issue Value: 4 Titles: – TitleFull: Farmacia Type: main |
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