Date Approved


Embargo Period


Document Type


Degree Name

Master of Science (M.S.) in Pharmaceutical Science


Chemistry and Biochemistry


College of Science & Mathematics


Chun Wu, Ph.D.

Committee Member 1

Zhihong Wang, Ph.D.

Committee Member 2

Zhiwei Liu, Ph.D.


computer-aided drug design, viral evolution dynamics, molecular dynamics simulation, near-neutral balanced selectionist theory, anti-HER2 chimeric antigen receptor, HER-2 positive cancer treatment


Drugs-- Design; Cancer--Treatment


Medicine and Health Sciences | Pharmacy and Pharmaceutical Sciences


This study encompasses three significant chapters focusing on diverse yet interconnected aspects of pharmaceutical research. Chapter 1 delves into the complexities of drug development, emphasizing the challenges and the pressing need for advanced technologies to streamline the process. Computational methods like Computer-Aided Drug Design (CADD) extend their scope beyond small molecules, aiding in the design of intricate biomolecules vital for biomedical advancements, especially in immunotherapy. Chapter 2 introduces the Near-Neutral Balanced Selectionist Theory (NNBST) validated through analysis of Dengue virus evolution. The unique features observed align with NNBST, surpassing existing theories. This approach offers a deeper understanding of viral evolution dynamics, identifying conserved segments critical for vaccine development and shedding light on potential drug targets, amplifying the battle against Dengue. Finally, Chapter 3 focuses on molecular dynamics simulations of a novel anti-HER2 Chimeric Antigen Receptor (CAR) for HER2-positive cancer treatment. The proposed Binding Induced Domain Dynamics Switch (BIDDS) unveils a new signal transduction mechanism, revolutionizing the understanding of CAR activation. This breakthrough not only challenges existing models but also opens avenues for broader applications in receptor-based therapies. These chapters collectively represent a multidisciplinary approach merging computational techniques, evolutionary biology, and molecular dynamics simulations, promising significant contributions to drug development, viral evolution understanding, and therapeutic advancements in cancer treatment.