Cited 9 time in
Computational Studies of Novel Chymase Inhibitors Against Cardiovascular and Allergic Diseases: Mechanism and Inhibition
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Arooj, Mahreen | - |
| dc.contributor.author | Thangapandian, Sundarapandian | - |
| dc.contributor.author | John, Shalini | - |
| dc.contributor.author | Hwang, Swan | - |
| dc.contributor.author | Park, Jong K. | - |
| dc.contributor.author | Lee, Keun W. | - |
| dc.date.accessioned | 2022-12-27T01:34:46Z | - |
| dc.date.available | 2022-12-27T01:34:46Z | - |
| dc.date.issued | 2012-12 | - |
| dc.identifier.issn | 1747-0277 | - |
| dc.identifier.issn | 1747-0285 | - |
| dc.identifier.uri | https://scholarworks.gnu.ac.kr/handle/sw.gnu/21895 | - |
| dc.description.abstract | To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4-diazepane-2,5-diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4-diazepane-2,5-diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structureactivity relationships models. Two models (genetic function approximation model 1 r2 = 0.812 and genetic function approximation model 2 r2 = 0.783) performed better in terms of correlation coefficients and cross-validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structureactivity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors. | - |
| dc.format.extent | 14 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | WILEY | - |
| dc.title | Computational Studies of Novel Chymase Inhibitors Against Cardiovascular and Allergic Diseases: Mechanism and Inhibition | - |
| dc.type | Article | - |
| dc.publisher.location | 미국 | - |
| dc.identifier.doi | 10.1111/cbdd.12006 | - |
| dc.identifier.scopusid | 2-s2.0-84868014176 | - |
| dc.identifier.wosid | 000310469500007 | - |
| dc.identifier.bibliographicCitation | CHEMICAL BIOLOGY & DRUG DESIGN, v.80, no.6, pp 862 - 875 | - |
| dc.citation.title | CHEMICAL BIOLOGY & DRUG DESIGN | - |
| dc.citation.volume | 80 | - |
| dc.citation.number | 6 | - |
| dc.citation.startPage | 862 | - |
| dc.citation.endPage | 875 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | sci | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
| dc.relation.journalResearchArea | Pharmacology & Pharmacy | - |
| dc.relation.journalWebOfScienceCategory | Biochemistry & Molecular Biology | - |
| dc.relation.journalWebOfScienceCategory | Chemistry, Medicinal | - |
| dc.subject.keywordPlus | NONPEPTIDE INHIBITORS | - |
| dc.subject.keywordPlus | CHLOROMETHYL KETONE | - |
| dc.subject.keywordPlus | SERINE PROTEASES | - |
| dc.subject.keywordPlus | ANGIOTENSIN-II | - |
| dc.subject.keywordPlus | 3D QSAR | - |
| dc.subject.keywordPlus | DERIVATIVES | - |
| dc.subject.keywordPlus | DOCKING | - |
| dc.subject.keywordPlus | BINDING | - |
| dc.subject.keywordPlus | IDENTIFICATION | - |
| dc.subject.keywordPlus | POTENT | - |
| dc.subject.keywordAuthor | Bayesian categorization | - |
| dc.subject.keywordAuthor | chymase | - |
| dc.subject.keywordAuthor | genetic function approximation | - |
| dc.subject.keywordAuthor | molecular docking | - |
| dc.subject.keywordAuthor | quantitative structure-activity relationship | - |
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