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http://hdl.handle.net/10603/521715
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DC Field | Value | Language |
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dc.coverage.spatial | ||
dc.date.accessioned | 2023-10-30T11:12:05Z | - |
dc.date.available | 2023-10-30T11:12:05Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/521715 | - |
dc.description.abstract | newline 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.extent | 220 | |
dc.language | English | |
dc.relation | ||
dc.rights | self | |
dc.title | Qsar docking and in vitro evaluation of plant terpenoids and their derivatives for anticancer activity targeting nfand#954;b signaling pathway | |
dc.title.alternative | NA | |
dc.creator.researcher | Deepika Yadav | |
dc.subject.keyword | Life Sciences | |
dc.description.note | QSAR Docking Cancer ADMET MTT assay | |
dc.contributor.guide | Prof. Bhartendu Nath Mishra and Dr. Feroz Khan | |
dc.publisher.place | Lucknow | |
dc.publisher.university | Dr. A.P.J. Abdul Kalam Technical University | |
dc.publisher.institution | Biotechnology | |
dc.date.registered | 2015 | |
dc.date.completed | 2023 | |
dc.date.awarded | 2023 | |
dc.format.dimensions | PD | |
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Biotechnology |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 31.46 kB | Adobe PDF | View/Open |
02_prelimpages.pdf | 245.07 kB | Adobe PDF | View/Open | |
03_contents.pdf | 191.91 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 12.15 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 165.13 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 1.36 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 1.03 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 1.15 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 840.93 kB | Adobe PDF | View/Open | |
11_chapter 7.pdf | 823.38 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 66.39 kB | Adobe PDF | View/Open | |
annexures.pdf | 3.8 MB | Adobe PDF | View/Open |
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