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Computational approach for autophagy and apoptosis specific knowledgebases-guided system pharmacology drug research

Wang, Nanyi (2017) Computational approach for autophagy and apoptosis specific knowledgebases-guided system pharmacology drug research. Master's Thesis, University of Pittsburgh. (Unpublished)

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Autophagy and Apoptosis are the basic physiological processes in cells to clean up aged and mutant cellular components or even the entire cells. However, both autophagy and apoptosis are disrupted in most of the major diseases like cancer and neurological disorder. Increasing attention is also paid recently in academia to understand the crosstalk between autophagy and apoptosis due to their tight synergetic or opposite functions in several pathological processes. To assist autophagy and apoptosis related drug research, we established two chemical-genomic databases which are specifically designed for autophagy and apoptosis, by collecting protein targets, chemicals, and pathways closely related to autophagy and apoptosis. This information, supported by our established system pharmacological analysis tools, such as HTDocking and TargetHunter, provided two comprehensive knowledgebases for the pharmacological study of autophagy and apoptosis. Additionally, to enhance the accuracy of the prediction by HTDocking in these two knowledgebases, we developed ProSeletion, a computational protein selection algorithm bases on the research purpose, is designed to generate the proper structure subset for molecular docking study. A suggested docking score threshold for active ligands (SDA) was then generated according to the receiver operating characteristic (ROC) curve and was used as an individual docking score criterion for the active ligands prediction. The performance of prediction was further evaluated by FDA recently approved small molecule antineoplastic drugs. Overall, the Autophagy Knowledgebase and the Apoptosis Knowledgebase will accelerate our work in autophagy-apoptosis related research and can be a useful tool for information searching, target prediction, and new chemical discovery.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Wang, Nanyinaw63@pitt.eduNAW63
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairSun,
Committee MemberXie,
Committee MemberWang,
Date: 25 April 2017
Date Type: Publication
Defense Date: 28 March 2017
Approval Date: 25 April 2017
Submission Date: 5 April 2017
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Number of Pages: 111
Institution: University of Pittsburgh
Schools and Programs: School of Pharmacy > Pharmaceutical Sciences
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Autophagy; Apoptosis; Cancer; Neurological disease
Date Deposited: 25 Apr 2017 20:19
Last Modified: 25 Apr 2022 05:15


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