Date of Award
2017
Document Type
Thesis
Degree Name
Bachelor of Science
Department
Chemistry
First Advisor
Dr. Carol Parish
Abstract
Molecular dynamics (MD) simulations and computational chemistry allow for an atomistic understanding of protein-protein and protein-ligand binding motifs. Through the use of MD, medicinally relevant complexes can be examined in detail unattainable by experimental methods. Within this work, systems pertinent to both Alzheimer’s Disease and HIV-1 are probed and thoroughly sampled to help elucidate potential therapeutic pathways. We used molecular dynamics and free energy estimations to gauge the affinity for the binary and ternary complexes of KLC1, APP and JIP1, three proteins all believed to be involved in the propagation of Alzheimer’s Disease. Two areas of thought exist suggesting that APP is either transported in a binary KLC1:APP complex, or is assisted by a third protein, JIP1, in a ternary KLC1:JIP1:APP complex. We find that all binary and ternary complexes (KLC1:APP, KLC1:JIP1, APP:JIP1, and KLC1:JIP1:APP) contain conformations with favorable binding free energies, and that the ternary KLC1:JIP1:APP complex shows signs of being thermodynamically more favorable than the binary KLC1:APP complex. With regards to the HIV-1 studies, a pyrazolo-piperdine ligand was recently synthesized and the corresponding biological data showed good binding to both CCR5 and CXCR4, receptors involved in the HIV-1 lifecycle, thus effectively preventing HIV-1 entry. After extensive sampling, we find that π-stacking interactions between the ligand and receptor residues, as well as electrostatic interactions involving the protonated piperidine nitrogen are the driving forces behind the ligand-protein binding. We also propose and computationally verify a new, synthetically- accessible derivative designed to increase the electrostatic interactions without compromising the π-stacking features.
Recommended Citation
Taylor, Cooper Ashley, "Investigating medicinally important portein-protein and protein-ligand interactions : a computational approach" (2017). Honors Theses. 1005.
https://scholarship.richmond.edu/honors-theses/1005