Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/521715
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dc.date.accessioned2023-10-30T11:12:05Z-
dc.date.available2023-10-30T11:12:05Z-
dc.identifier.urihttp://hdl.handle.net/10603/521715-
dc.description.abstractnewline Nowadays, cancer has become an important cause of mortality worldwide. Cancer is known as an irregular and abnormal uncontrolled growth of cells in the human body (any part of the body). As per observations, more than 200 different cancer types have been reported. However, various causative or cancer-linked agents such as ionizing radiation, any toxic or chemical agents exposure, daily lifestyle, or human inheritances may be responsible to develop abnormal cancer cells from normal cells. So, the present research is work focused to identify a natural phytochemical against the particular cancer drug targets of the signaling pathway. The NF-and#954;B signaling pathway was targeted in the current work to identify potent and natural leads against various intracellular anticancer targets. However, the fresh and novel chemical natural entity for anticancer properties is growing progressively. So far, the number of various databases has been precisely designed to retrieve the chemical entities/compounds with cytotoxic or anticancer properties. Although, the level for the required chemical structure selectivity with realistic justification in the drug development has not been attained yet. Hence, recognition of a significant pattern is a complex, time-consuming process in a biological system. The numerous techniques of cheminformatics have developed, fruitfully applied and practiced in various extents of cancer drug development procedure. Likewise, the cheminformatics applications namely in silico QSAR, computational pharmacokinetic evaluation (ADME/T), molecular docking simulations provides a framework in the direction of novel and safe lead identification. Though, the number of chemical databases or web resources is available to collect raw data of experimental bioactivities to establish a real QSAR model. To achieve a successful QSAR model development, a raw data collection (experimental bioactivity) is a crucial phase of the entire process. Model authenticity and quality are entirely based on the experiment.
dc.format.extent220
dc.languageEnglish
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dc.rightsself
dc.titleQsar docking and in vitro evaluation of plant terpenoids and their derivatives for anticancer activity targeting nfand#954;b signaling pathway
dc.title.alternativeNA
dc.creator.researcherDeepika Yadav
dc.subject.keywordLife Sciences
dc.description.noteQSAR Docking Cancer ADMET MTT assay
dc.contributor.guideProf. Bhartendu Nath Mishra and Dr. Feroz Khan
dc.publisher.placeLucknow
dc.publisher.universityDr. A.P.J. Abdul Kalam Technical University
dc.publisher.institutionBiotechnology
dc.date.registered2015
dc.date.completed2023
dc.date.awarded2023
dc.format.dimensionsPD
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Biotechnology

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01_title.pdfAttached File31.46 kBAdobe PDFView/Open
02_prelimpages.pdf245.07 kBAdobe PDFView/Open
03_contents.pdf191.91 kBAdobe PDFView/Open
04_abstract.pdf12.15 kBAdobe PDFView/Open
05_chapter 1.pdf165.13 kBAdobe PDFView/Open
06_chapter 2.pdf1.36 MBAdobe PDFView/Open
07_chapter 3.pdf1.03 MBAdobe PDFView/Open
09_chapter 5.pdf1.15 MBAdobe PDFView/Open
10_chapter 6.pdf840.93 kBAdobe PDFView/Open
11_chapter 7.pdf823.38 kBAdobe PDFView/Open
80_recommendation.pdf66.39 kBAdobe PDFView/Open
annexures.pdf3.8 MBAdobe PDFView/Open


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