UC Berkeley

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Export and quality control of messenger ribonucleic acids (mRNAs) feature a prominent example of such an intricate molecular system. Export of mRNAs into the cytoplasm is a fundamental step in gene regulation processes, which is meticulously quality controlled by highly efficient mechanisms in eukaryotic cells. Despite extensive research on how mRNAs are quality controlled prior to export into the cytoplasm, the exact underlying mechanisms are still under debate. Specifically, it is unclear how aberrant mRNAs are recognized and retained inside the nucleus. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. In this dissertation, I present my research on mRNA quality control using different computational techniques.

Using the agent-based modeling (ABM) approach, which is an emerging molecular systems biology technique for exploring the dynamics of molecular systems/pathways in health and disease, we first developed a minimal model of the mRNA quality control (QC) mechanism. Our results suggested that regulation of the affinity of RNA-binding proteins (RBPs) to export receptors along with the weak interaction between the RBPs and nuclear basket proteins, namely myosin-like protein-1 (Mlp1) or translocated promoter region (Tpr) protein, are the minimum requirements to distinguish and retain aberrant mRNAs. In addition, we demonstrated how the length of mRNA may affect the QC process.

The interaction between Mlp1 with one of the Saccharomyces cerevisiae RBPs, namely the nuclear polyadenylated RNA-binding protein (Nab2), was then investigated. Mlp1 plays a substantial role in mRNA quality control by interacting with other proteins involved in this process, specifically the RBPs. Yet, the mechanism of the interaction between Mlp1 and RBPs is still elusive. Using an array of integrated computational approaches including protein structure prediction, protein-protein docking, and molecular dynamics simulations, we dissected Mlp1-Nab2 interaction. Our results were consistent with experimental observations, which suggested that Nab2 residue F73 is essential for Mlp1 binding and further uncovered an indirect role of Nab2-F73 in this interaction.