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Lead discovery and in silico 3D structure modeling of tumorigenic FAM72A (p17)

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dc.contributor.authorPramanik, Subrata-
dc.contributor.authorKutzner, Arne-
dc.contributor.authorHeese, Klaus-
dc.date.accessioned2022-07-16T00:54:49Z-
dc.date.available2022-07-16T00:54:49Z-
dc.date.issued2015-01-
dc.identifier.issn1010-4283-
dc.identifier.issn1423-0380-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/158098-
dc.description.abstractFAM72A (p17) is a novel neuronal protein that has been linked to tumorigenic effects in non-neuronal tissue. Using state of the art in silico physicochemical analyses (e.g., I-TASSER, RaptorX, and Modeller), we determined the three-dimensional (3D) protein structure of FAM72A and further identified potential ligand-protein interactions. Our data indicate a Zn2+/Fe3+-containing 3D protein structure, based on a 3GA3_A model template, which potentially interacts with the organic molecule RSM ((2s)-2-(acetylamino)-N-methyl-4-[(R)-methylsulfinyl] butanamide). The discovery of RSM may serve as potential lead for further anti-FAM72A drug screening tests in the pharmaceutical industry because interference with FAM72A's activities via RSM-related molecules might be a novel option to influence the tumor suppressor protein p53 signaling pathways for the treatment of various types of cancers.-
dc.format.extent11-
dc.language영어-
dc.language.isoENG-
dc.publisherSpringer Verlag-
dc.titleLead discovery and in silico 3D structure modeling of tumorigenic FAM72A (p17)-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1007/s13277-014-2620-7-
dc.identifier.scopusid2-s2.0-84925492190-
dc.identifier.wosid000350477300026-
dc.identifier.bibliographicCitationTumor Biology, v.36, no.1, pp 239 - 249-
dc.citation.titleTumor Biology-
dc.citation.volume36-
dc.citation.number1-
dc.citation.startPage239-
dc.citation.endPage249-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaOncology-
dc.relation.journalWebOfScienceCategoryOncology-
dc.subject.keywordPlusMOLECULAR-DYNAMICS SIMULATIONS-
dc.subject.keywordPlusPROTEIN-STRUCTURE-
dc.subject.keywordPlusSTRUCTURE PREDICTION-
dc.subject.keywordPlusSECONDARY STRUCTURE-
dc.subject.keywordPlusBINDING-SITE-
dc.subject.keywordPlusCANCER-
dc.subject.keywordPlusRECEPTOR-
dc.subject.keywordPlusDOCKING-
dc.subject.keywordPlusGENERATION-
dc.subject.keywordPlusHALLMARKS-
dc.subject.keywordAuthorUgene-
dc.subject.keywordAuthorFAM72A-
dc.subject.keywordAuthorIn silico-
dc.subject.keywordAuthor3D structure-
dc.subject.keywordAuthorCancer-
dc.subject.keywordAuthorRSM-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s13277-014-2620-7-
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서울 의생명공학전문대학원 > 서울 의생명과학과 > 1. Journal Articles
서울 공과대학 > 서울 정보시스템학과 > 1. Journal Articles

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