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PDFOpen Access (License Unspecified), Open Access
Thesis
Utilization of computer artificial intelligence in the design of small molecule-based immunoinhibitors of PD-L1
Master of Science (M.S.), Drexel University
Jun 2021
DOI:
https://doi.org/10.17918/00000819
Abstract
Cancer is one of the leading causes of death worldwide with around 9.5 million recorded deaths in 2018 alone. Prevention and treatment processes are the key for a therapeutic intervention. Despite all the advances in cancer treatment, shortcomings in immunotherapy exist, specifically towards small molecule based immunoinhibitors for the PD-1/PDL-1 pathway. To date, an anti-cancer medication has not been created. Previously, monoclonal antibodies and macromolecules have demonstrated better efficacy towards PD-1/PD-L1 inhibition, thus treating infection through immune response. Additionally, both monoclonal antibodies and macromolecules have shown to be non-cytotoxic26. While these previous innovations have improved patient outcomes, small molecule inhibitors have not been able to replicate the same results. In this study, the utilization of computer artificial intelligence (A. I.) in the design of small molecule based immunoinhibitors was investigated. Creation of a python script-based pipeline was used with molecular docking data performed with Autodock Vina to convert docked ligands into fragmented variations based upon protein-ligand interactions. Additional docking calculations were performed utilizing Schrodinger™ Masetro in search of a small molecule inhibitor by way of a structure-based drug design approach. These investigations demonstrated the possibility of a new approach towards the drug design process. The potential for complete A. I. recognition and development of lead ligands would eliminate a large majority of current issues within the drug design process. Ultimately, A. I. is the future of drug design and ligand optimization.
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Details
- Title
- Utilization of computer artificial intelligence in the design of small molecule-based immunoinhibitors of PD-L1
- Creators
- John P. Averona
- Contributors
- Haifeng Ji (Advisor) - Drexel University, Chemistry
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- 41 pages
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- College of Arts and Sciences; Chemistry; Drexel University
- Other Identifier
- 991015241980304721