Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/341784
Title: Identification of flavonoids as inhibitors of matrix metalloproteinase9 for the management of rheumatoid arthritis in silico and invitro studies
Researcher: Pradiba D
Guide(s): Vasanthi M
Keywords: Engineering and Technology
Engineering
Nuclear Science and Technology
Rheumatoid Arthritis
Flavonoids
University: Anna University
Completed Date: 2020
Abstract: Rheumatoid Arthritis (RA) is a debilitating inflammatory disease of the articular joints of autoimmune origin, which leads to a significant impairment of the quality of life in the long term. Persistent inflammation of the synovial membrane that lines the joints produces a locally invasive pannus, that is capable of invading and ultimately destroying cartilage, bone and adjacent soft tissues. Conventional disease-modifying or biological anti-rheumatic drugs that are recommended along with short-term glucocorticoids show profound side-effects and adverse events. This has necessitated the development of novel agents for controlling rheumatoid arthritis. A more recent approach is the use of plant secondary metabolites as therapeutic agents. Flavonoids are pharmacologically active diverse group of phytochemicals to provide good lead-generation opportunities. In the present study, flavonoids were studied for their ability to inhibit matrix metalloproteinase-9 (MMP-9), a key zinc-containing metalloenzyme involved in the formation of new blood vessels in the invading pannus, which when inhibited prevents the angiogenesis ultimately resulting in inhibition of RA progression. This was done through computer based (in-silico) studies and their validation using (in-vitro) experimental methods. Flavonoids (136) were chosen from plants with anti-arthritic and anti-inflammatory properties through literature survey and were classified based on their structure. The chosen flavonoid dataset fell into nine different classes of flavonoids namely flavonols, flavones, flavyliums, flavan-ols, flavonones, flavonolols, biflavonoids, isoflavonoids and neoflavonoids. The drug-likeness of all these flavonoids was predicted using computational newline
Pagination: xxv,228p.
URI: http://hdl.handle.net/10603/341784
Appears in Departments:Faculty of Technology

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02_certificates.pdf123.67 kBAdobe PDFView/Open
03_vivaproceedings.pdf77.68 kBAdobe PDFView/Open
04_bonafidecertificate.pdf151.3 kBAdobe PDFView/Open
05_abstracts.pdf190.36 kBAdobe PDFView/Open
06_acknowledgements.pdf96.86 kBAdobe PDFView/Open
07_contents.pdf198.53 kBAdobe PDFView/Open
08_listoftables.pdf109.75 kBAdobe PDFView/Open
09_listoffigures.pdf198.29 kBAdobe PDFView/Open
10_listofabbreviations.pdf182.52 kBAdobe PDFView/Open
11_chapter1.pdf214.33 kBAdobe PDFView/Open
12_chapter2.pdf1.22 MBAdobe PDFView/Open
13_chapter3.pdf585.77 kBAdobe PDFView/Open
14_chapter4.pdf3.9 MBAdobe PDFView/Open
15_conclusion.pdf212.02 kBAdobe PDFView/Open
16_appendices.pdf805.37 kBAdobe PDFView/Open
17_references.pdf368.51 kBAdobe PDFView/Open
18_listofpublications.pdf185.19 kBAdobe PDFView/Open
80_recommendation.pdf249.91 kBAdobe PDFView/Open
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