Accelerated simulations and computer-aided drug design of membrane proteins

Membrane proteins represent ~30% of the proteome and more than 60% of drug targets. They play key roles in physiological functions, such as signal transduction, transport, ion regulation and enzymatic activities. Malfunction of these proteins result in deadly human diseases, such as paralysis, cancer, heart failure and Alzheimer’s diseases (AD). Despite the importance, the structural dynamics and functional mechanisms of many membrane proteins remain poorly understood, which has greatly hindered effective drug design. Gaussian accelerated Molecular Dynamics (GaMD) is a novel technique that provides simultaneous unconstrained enhanced sampling and free energy calculations. GaMD has been successfully applied to study physical pathways and mechanisms of protein folding and ligand binding of important membrane proteins. Based on the principles of GaMD, Ligand GaMD (LiGaMD) and Peptide GaMD (Pep-GaMD) methods were developed to efficiently simulate ligand and peptide binding/unbinding, respectively. Here, I have integrated GaMD, LiGaMD and Pep-GaMD with advanced complementary computational techniques including molecular docking, homology modeling and free energy calculations for accelerated simulations and computer-aided drug design of different membrane proteins. In Chapters 1 and 2, I focus on applying GaMD and Pep-GaMD to determine the mechanisms of γ-secretase activation and substrate processive proteolysis. In Chapters 3 and 4, I focus on investigating the dependence of GPCR-membrane interactions on the receptor activation state and retrospective docking of known positive allosteric modulators (PAMs) to GaMD simulation-derived structural ensembles of the adenosine A1 receptor (A1AR), respectively. Finally, in Chapter 5, I apply LiGaMD to understand the mechanism of ligand recognition by human Angiotensin Converting Enzyme-2 (ACE2) receptor.

Grantor dc:publisher

University of Kansas

Year dc:date.issued

2022

Author dc:creator

• Bhattarai, Apurba

Advisor dc:contributor.advisor

• Miao, Yinglong

• Biology
• Computational chemistry
• Bioinformatics
• Alzheimer’s disease (AD)
• Angiotensin converting enzyme 2 (ACE2)
• Covid-19
• Ensemble Docking
• G-protein-coupled receptors (GPCRs)
• Molecular Dynamics (MD)

Statement dc:rights

• Copyright held by the author.

Language dc:language.iso

en

Dc Identifier Other

http://dissertations.umi.com/ku:18216

OAI identifier oai:identifier

oai:kuscholarworks.ku.edu:1808/35363