Malaria is caused by a protozoan parasite, Plasmodium falciparum, which is responsible for over 500,000 deaths per year worldwide. Although malaria medicines are working well in many parts of the world, antimalarial drug resistance has emerged as one of the greatest challenges facing malaria control today. Since the malaria parasites are once again developing widespread resistance to antimalarial drugs, this can cause the spread of malaria to new areas and the re-emergence of malaria in areas where it had already been eradicated. Therefore, the discovery and characterization of novel antimalarials is extremely urgent. A previous drug screen in Dr. Chakrabarti's lab identified several natural products (NPs) with antiplasmodial activities. The focus of this study is to characterize the hit compounds using Principal Component Analysis (PCA) to determine structural uniqueness compared to known antimalarial drugs. This study will compare multiple libraries of different compounds, such as known drugs, kinase inhibitors, macrocycles, and top antimalarial hits discovered in our lab. Prioritizing the hit compounds by their chemical uniqueness will lessen the probability of future drug resistance. This is an important step in drug discovery as this will allow us to increase the interpretability of the datasets by creating new uncorrelated variables that will successively maximize variance. Characterization of the Natural Product inspired compounds will enable us to discover potent, selective, and novel antiplasmodial scaffolds that are unique in the 3-dimensional chemical space and will provide critical information that will serve as advanced starting points for the antimalarial drug discovery pipeline.
Bachelor of Science (B.S.)
College of Medicine
Burnett School of Biomedical Sciences
Orlando (Main) Campus
Length of Campus-only Access
Balde, Zarina Marie G., "Characterization of Novel Antimalarials From Compounds Inspired By Natural Products Using Principal Component Analysis (PCA)" (2018). Honors Undergraduate Theses. 405.
Restricted to the UCF community until 11-1-2023; it will then be open access.