Graduation Year

2016

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Biology (Cell Biology, Microbiology, Molecular Biology)

Major Professor

Sameer Varma, Ph.D.

Committee Member

Gary Daughdrill, Ph.D.

Committee Member

James Riordan, Ph.D.

Committee Member

Yu Chen, Ph.D.

Keywords

Inverse machine learning, Molecular dynamics, Paramyxovirus, Protein–protein interaction, Structure prediction, Water dynamics

Abstract

Nipah belongs to the family of paramyxoviruses that cause numerous fatal diseases in humans and farm animals. There are no FDA approved drugs for Nipah or any of the paramyxoviruses. Designing antiviral therapies that are more resistant to viral mutations require understanding of molecular details underlying infection. This dissertation focuses on obtaining molecular insights into the very first step of infection by Nipah. Such details, in fact, remain unknown for all paramyxoviruses. Infection begins with the allosteric stimulation of Nipah virus host binding protein by host cell receptors. Understanding molecular details of this stimulation process have been challenging mainly because, just as in many eukaryotic proteins, including GPCRs, PDZ domains and T-cell receptors, host receptors induce only minor structural changes (< 2 Å) and, consequently, thermal fluctuations or dynamics play a key role. This work utilizes a powerful molecular dynamics based approach, which yields information on both structure and dynamics, laying the foundation for its future applications to other paramyxoviruses. It proposes a new model for the initial phase of stimulation of Nipah’s host binding protein, and in general, highlights that (a) interfacial waters can play a crucial role in the inception and propagation of allosteric signals; (b) extensive inter-domain rearrangements can be triggered by minor changes in the structures of individual domains; and (c) mutations in dynamically stimulated proteins can induce non-local changes that spread across entire domains.

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