Abstract

Currently, a substantial gap exists between the methods utilized for modeling biological pathways. While some methods rely heavily on assumptions that prevent them from capturing the spatial detail and stochastic behavior observed in nature, others are designed to account for deeper levels of spatial details and stochasticity but at the cost of increased computational time and resources. Agent-based modeling (ABM) is a highly promising approach that brings together the advantages of detailed spatiotemporal approaches and computationally inexpensive methods. ABMs consist of a collection of agents with governing rules that dictate local behavior and interactions with adjacent agents, eventually predicting the complex behavior that may not be obvious from the individual rules. Our recently developed ABM platform, called BioABM, is primarily designed to capture the dynamics of molecular-scale complex systems by associating diffusion and binding/unbinding constants of biological species to movement and interaction probabilities in ABM. In order to showcase its potential impact as a predictive tool, we apply BioABM to an important, yet not well understood, biological pathway, i.e. messenger ribonucleic acid (mRNA) export and quality control mechanism. mRNAs are transported to the cytoplasm to transfer genetic information and direct synthesis of functional proteins. Multiple proteins and complexes are involved and the process is meticulously quality controlled by various sophisticated, yet highly efficient, mechanisms in eukaryotic cells. Using BioABM, we explored the dynamics of mRNA export and the mechanism through which aberrant mRNAs are distinguished and retained inside the nucleus. Our results shed light on different aspects of this pathway; addressing factors such as the significance of the expression level of mRNA export factor and the length of mRNA as well as presence of a nuclear basket-associated quality control complex on mRNA export dynamics.

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