Investigation, design and synthesis of new anticancer agents with anticancer effect potential on MCF-7 breast cancer cells by machine learning method

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dc.contributor.authorKeskin, Suat Utku
dc.contributor.authorBülbül, Volkan
dc.contributor.authorKalender, Mervenur
dc.contributor.authorÖzyaman, Sümeyye
dc.contributor.authorMermer, Arif
dc.date.accessioned2022-12-02T11:47:57Z
dc.date.available2022-12-02T11:47:57Z
dc.date.issued2022
dc.departmentİstanbul Medipol Üniversitesi, Tıp Fakültesi, Temel Tıp Bilimleri Bölümü, Histoloji ve Embriyoloji Ana Bilim Dalı
dc.description.abstractCancer is one of the diseases with a high mortality rate, which occurs when cells multiply uncontrollably, acquire an invasive character and metastasize. Breast cancer is one of the cancer types with an increasing incidence worldwide. Chemotherapy is a method used in the treatment of cancer diseases, and the chemotherapeutic drugs used inhibit the growth and proliferation of cancer cells due to their cytotoxic properties. Today, machine learning techniques offer significant advantages by helping several steps of the drug discovery process, reducing the time spent in the laboratory, the use of consumables and chemical materials, and the maximum time predicted for the discovery of a drug with traditional methods. In our study, it was aimed to determine the 3 Schiff base derivatives with the most active cytotoxic effect on breast cancer cells from the large data set using machine learning. In our study, 7 Schiff base derivatives were determined from a large data set containing 98 compounds, and the 3 most active compounds with cytotoxic properties on breast cancer cells and their IC50 values were determined by machine learning method. In the future, it is thought that compound 1 can be used as an alternative to pharmacological applications to be used in preclinical studies as a therapeutic agent, supported by in vitro and in vivo applications, in order to be used in cancer treatments.
dc.identifier.citationKeskin, S. U., Bülbül, V., Kalender, M., Özyaman, S. ve Mermer, A. (2022). Investigation, design and synthesis of new anticancer agents with anticancer effect potential on MCF-7 breast cancer cells by machine learning method. Journal of Experimental and Clinical Medicine (Turkey), 39(4), 1043-1050. https://doi.org/10.52142/omujecm.39.4.23
dc.identifier.doi10.52142/omujecm.39.4.23
dc.identifier.endpage1050
dc.identifier.issn1309-4483
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85142057551
dc.identifier.scopusqualityQ4
dc.identifier.startpage1043
dc.identifier.urihttps://doi.org/10.52142/omujecm.39.4.23
dc.identifier.urihttps://hdl.handle.net/20.500.12511/10068
dc.identifier.volume39
dc.indekslendigikaynakScopus
dc.institutionauthorKalender, Mervenur
dc.institutionauthorÖzyaman, Sümeyye
dc.language.isoen
dc.publisherOndokuz Mayıs University
dc.relation.ispartofJournal of Experimental and Clinical Medicine (Turkey)en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBreast Cancer
dc.subjectDrug Discovery
dc.subjectMachine Learning
dc.subjectMCF-7
dc.titleInvestigation, design and synthesis of new anticancer agents with anticancer effect potential on MCF-7 breast cancer cells by machine learning method
dc.typeArticle

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