UC Riverside

Single-stranded RNA viruses efficiently encapsulate their genome into a protein shell called the capsid. Understanding the physical principles underlying the formation of virus capsid assembly and genome packaging is of great interest because of their potential applications in blocking viral infections and various areas of bio-nanotechnology, such as drug delivery and gene therapy. The first part of the thesis investigates the encapsidation of single-stranded RNAs into virus capsid. Electrostatic interactions between the positive charges in the capsid protein’s N-terminal tail and the negatively charged genome have been postulated as the main driving force for virus assembly. Recent experimental results indicate that the N-terminal tails with the same number of charges and same lengths package different amounts of RNA, which reveals that electrostatics alone cannot explain all the observed outcomes of the RNA self-assembly experiments. Using a mean-field theory, we show that the combined effect of genome configurational entropy and electrostatics can explain to some extent the amount of packaged RNA with mutant proteins where the location and number of charges on the tails are altered.

The second part focuses on understanding the physical principles of virus capsid assembly, specifically for the difficult cases of the assembly of nonspherical structures such as Human Immunodeficiency Viruses (HIV). For HIV shells, while there are often 5 defects at the smaller and 7 at the larger caps, defect positions vary from one HIV structure to another. Currently, there is no clear understanding of what determines the position of the defects as the surfaces with non-zero Gaussian curvature such as the conical shell of HIV grow. To tackle this issue, in this thesis, we take the first step and solve an intermediate problem of characterizing the structure of an elastic network constrained to lie on a frozen curved surface by continuum elasticity theory. We provide an exact solution to this problem without resorting to any approximation in terms of geometric quantities.