Computational Methods for Nucleic Acid Structure Prediction and G Protein-Coupled Receptor Mechanism Investigation

Citation

Gonzalvo i Ulla, Marta (2025) Computational Methods for Nucleic Acid Structure Prediction and G Protein-Coupled Receptor Mechanism Investigation. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/bxdy-5x58. https://resolver.caltech.edu/CaltechTHESIS:05152025-170540802

Abstract

Molecular dynamics (MD) simulation is a powerful tool to characterize molecular structure. In this thesis, we use MD to solve three problems in biological chemistry: the prediction of secondary nucleic acid structure, the prediction of the structure of a siRNA-based tool, and the understanding of the activation mechanism of the sweet taste receptor.

First, we use MD to computationally parameterize nucleic acid secondary structure models. Current models are parameterized using experimental data that was limited and time consuming to generate. In this work, we present a workflow to select an ensemble of base pairing reactions using machine learning, perform MD simulations to obtain their free energy and enthalpy profiles, and perform nonlinear regression on the energies and enthalpies to yield thermodynamic nearest neighbor parameters. This computational framework parameterizes secondary structure models with comparable accuracy to experimental data, and can be used to expand the current models to a range of materials and experimental conditions beyond the specific experimental conditions the parameters were originally generated in.

Next, we predict the structure of a RNA therapeutic tool, conditionally activated small interfering RNAs (Cond-siRNAs). We evaluate how two structural modifications to the two double helix topology affect the ability of the construct to perform its function in the RNAi pathway, finding that a short sensor overhang and a carbon chain linker between the two duplexes reduce undesired interactions in the structure. We also characterize the structure for a new topology with a single linker between the duplexes, and show how the position of terminal modifiers causes structural distortions and can disrupt its function. These insights will guide the design of Cond-siRNAs and other RNA tools with similar non-canonical modifications.

Lastly, we investigate the mechanism of activation of the TAS1R2/TAS1R3 sweet taste receptor, coupled to the G protein gustducin. We use metadynamics simulations to estimate the reduction of the free energy of opening the G alpha subunit in the presence of a positive allosteric modulator and steviol glycosides of varying sweetness. We also uncover insights into how the modulator induces the activation of the G alpha, leading to the partial release of GDP; and how the steviol glycosides RebM, RebD and IsoRebM of high sweetness induce an interdomain twist in the Venus Fly Trap domains. These results further our understanding of the activation mechanism of the class C sweet taste receptor and can be used for the development of new sweeteners.