Studies in Computational Biophysics: SARS-CoV-2 and Plant Cell Plate Maturation
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Studies in Computational Biophysics: SARS-CoV-2 and Plant Cell Plate Maturation

Abstract

This dissertation is split into two parts. In part 1, we discuss plant cytokinesis, a fundamental process of plant life which involves de novo formation of a “cell plate” partitioningthe cytoplasm of dividing cells. Cell plate formation is directed by orchestrated delivery, fusion of cytokinetic vesicles, and membrane maturation to form a nascent cell wall by timely deposition of polysaccharides. During cell plate maturation, the fragile membrane network transitions to a fenestrated sheet and finally a young cell wall. Here, we approximated cell plate sub-structures with testable shapes and adopted the Helfrich-free energy model for membranes, including a stabilizing and spreading force, to understand the transition from a vesicular network to a fenestrated sheet and mature cell plate. Regular cell plate development in the model was possible, with suitable bending modulus, for a two-dimensional late stage spreading force of 2–6pN/nm, an osmotic pressure difference of 2–10kP a, and spontaneous curvature between 0 and 0.04nm−1 . With these conditions, stable membrane conformation sizes and morphologies emerged in concordance with stages of cell plate development. To reach a mature cell plate, our model required the late-stage onset of a spreading/stabilizing force coupled with a concurrent loss of spontaneous curvature. Absence of a spreading/stabilizing force predicts failure of maturation. The proposed model provides a framework to interrogate different players in late cytokinesis and potentially other membrane networks that undergo such transitions. Callose, is a polysaccharide that accumulates transiently during cell plate maturation. Callose-related observations were consistent with the proposed model’s concept, suggesting that it is one of the factors involved in establishing the spreading force. In part 2, we discuss three different in-silico studies of SARS-CoV-2. These studies involve the use of molecular dynamics simulations, endpoint free-energy estimates, as well as predictive neural networks (AlphaFold). In Chapter 4, we present binding strength estimates of three critical fitness parameters (RBD/ACE2 binding, furin enzyme binding, antibody escape) of the SARS-CoV-2 omicron variant. We show that our results align with the preliminary observations noted with the variant, i.e. weakened RBD/ACE2 binding, but increased antibody escape. In Chapter 5, we present an in-depth analysis of the most commonly observed sequences in the Furin Cleavage Domain (FCD) and their interaction with the furin enzyme. We show that the Delta variant exhibits the strongest possible binding with the furin enzyme, and we identify key observed and unobserved sequences that could exhibit the same binding strength. In Chapter 6, we present a computational design of a humanized ACE2 decoy to be used as a possible therapeutic or diagnostic agent based on the principles of competitive binding. We show that our design binds favorably well to multiple SARS-CoV-2 target RBDs, including the delta and omicron variants.

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