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dc.contributor.authorSharp, Amanda Kristineen
dc.date.accessioned2020-05-19T08:01:35Z
dc.date.available2020-05-19T08:01:35Z
dc.date.issued2020-05-18
dc.identifier.othervt_gsexam:25969en
dc.identifier.urihttp://hdl.handle.net/10919/98471
dc.description.abstractKinases are involved in a multitude of signaling pathways, such as cellular growth, proliferation, and apoptosis, and have been discovered to be important in numerous diseases including cancer, Alzheimer's disease, cardiovascular health, rheumatoid arthritis, and fibrosis. Due to the involvement in a wide variety of disease types, kinases have been studied for exploitation and use as targets for therapeutics. There are many limitations with developing kinase target therapeutics due to the high similarity of kinase active site composition, making the utilization of new techniques to determine kinase exploitability for therapeutic design with high specificity essential for the advancement of novel drug strategies. In silico approaches have become increasingly prevalent for providing useful insight into protein structure-function relationships, offering new information to researchers about drug discovery strategies. This work utilizes streamlined computational techniques on an atomistic level to aid in the identification of orthologue and isoform exploitability, identifying new features to be utilized for future inhibitor design. By exploring two separate kinases and kinase targeting domains, we found that orthologues and isoforms contain distinct features, likely responsible for their biological roles, which can be utilized and exploited for selective drug development. In this work, we identified new exploitable features between kinase orthologues for treatment in Human African Trypanosomiasis and structural morphology differences between two kinase isoforms that can potentially be exploited for cancer therapeutic design.en
dc.format.mediumETDen
dc.publisherVirginia Techen
dc.rightsThis item is protected by copyright and/or related rights. Some uses of this item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en
dc.subjectproteins kinasesen
dc.subjectmolecular dynamics simulationsen
dc.subjectmolecular dockingen
dc.subjectprotein structure-functionen
dc.subjectdrug discoveryen
dc.titleProbing Orthologue and Isoform Specific Inhibition of Kinases using In Silico Strategies: Perspectives for Improved Drug Designen
dc.typeThesisen
dc.contributor.departmentBiochemistryen
dc.description.degreeMaster of Science in Life Sciencesen
thesis.degree.nameMaster of Science in Life Sciencesen
thesis.degree.levelmastersen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.disciplineBiochemistryen
dc.contributor.committeechairBrown, Anne M.en
dc.contributor.committeememberAllen, Kylie Dawnen
dc.contributor.committeememberLemkul, Justin Alanen
dc.description.abstractgeneralNumerous diseases such as cancer, Alzheimer's disease, cardiovascular disease, rheumatoid arthritis, and fibrosis have been attributed to different cell growth and survival pathways. Many of these pathways are controlled by a class of enzymes called kinases. Kinases are involved in almost every metabolic pathway in human cells and can act as molecular switches to turn on and off disease progression. Due to the involvement of these kinases' in a wide variety of disease types, kinases have been continually studied for the development of new drugs. Developing effective drugs for kinases requires an extensive understanding of the structural characteristics due to the high structural similarity across all kinases. In silico, or computational, techniques are useful strategies for drug development practices, offering new information into protein structure-function relationships, which in turn can be utilized in drug discovery advancements. Utilizing computational methods to explore structural features can help identify specific protein structural features, thus providing new strategies for protein specific inhibitor design. In this work, we identified new exploitable features between kinase orthologues for treatment in Human African Trypanosomiasis and structural morphology differences between two kinase isoforms that can potentially be exploited for cancer therapeutic design.en


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