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Exploring the chemical space of protein-protein interaction inhibitors through machine learning

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dc.contributor.author김남희-
dc.contributor.author김현실-
dc.contributor.author육종인-
dc.contributor.author김현실-
dc.contributor.author육종인-
dc.contributor.author최지원-
dc.date.accessioned2021-09-29T01:17:45Z-
dc.date.available2021-09-29T01:17:45Z-
dc.date.issued2021-06-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/184295-
dc.description.abstractAlthough protein-protein interactions (PPIs) have emerged as the basis of potential new therapeutic approaches, targeting intracellular PPIs with small molecule inhibitors is conventionally considered highly challenging. Driven by increasing research efforts, success rates have increased significantly in recent years. In this study, we analyze the physicochemical properties of 9351 non-redundant inhibitors present in the iPPI-DB and TIMBAL databases to define a computational model for active compounds acting against PPI targets. Principle component analysis (PCA) and k-means clustering were used to identify plausible PPI targets in regions of interest in the active group in the chemical space between active and inactive iPPI compounds. Notably, the uniquely defined active group exhibited distinct differences in activity compared with other active compounds. These results demonstrate that active compounds with regions of interest in the chemical space may be expected to provide insights into potential PPI inhibitors for particular protein targets.-
dc.description.statementOfResponsibilityopen-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherNature Publishing Group-
dc.relation.isPartOfSCIENTIFIC REPORTS-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleExploring the chemical space of protein-protein interaction inhibitors through machine learning-
dc.typeArticle-
dc.contributor.collegeCollege of Dentistry (치과대학)-
dc.contributor.departmentResearch Institute (부설연구소)-
dc.contributor.googleauthorJiwon Choi-
dc.contributor.googleauthorJun Seop Yun-
dc.contributor.googleauthorHyeeun Song-
dc.contributor.googleauthorNam Hee Kim-
dc.contributor.googleauthorHyun Sil Kim-
dc.contributor.googleauthorJong In Yook-
dc.identifier.doi10.1038/s41598-021-92825-5-
dc.contributor.localIdA00360-
dc.contributor.localIdA01121-
dc.contributor.localIdA02536-
dc.contributor.localIdA01121-
dc.contributor.localIdA02536-
dc.relation.journalcodeJ02646-
dc.identifier.eissn2045-2322-
dc.identifier.pmid34183730-
dc.contributor.alternativeNameKim, Nam Hee-
dc.contributor.affiliatedAuthor김남희-
dc.contributor.affiliatedAuthor김현실-
dc.contributor.affiliatedAuthor육종인-
dc.contributor.affiliatedAuthor김현실-
dc.contributor.affiliatedAuthor육종인-
dc.citation.volume11-
dc.citation.number1-
dc.citation.startPage13369-
dc.identifier.bibliographicCitationSCIENTIFIC REPORTS, Vol.11(1) : 13369, 2021-06-
Appears in Collections:
2. College of Dentistry (치과대학) > Research Institute (부설연구소) > 1. Journal Papers
2. College of Dentistry (치과대학) > Dept. of Oral Pathology (구강병리학교실) > 1. Journal Papers

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