Biophysical Society Thematic Meeting | Trieste 2024

Emerging Theoretical Approaches to Complement Single-Particle Cryo-EM

Friday Speaker Abstracts

COMPUTATIONAL MODELING OF RNA 3D STRUCTURES AND INTERACTIONS - WITH AND WITHOUT THE USE OF EXPERIMENTAL DATA Janusz M Bujnicki 1 ; 1 International Institute of Molecular and Cell Biology in Warsaw, Laboratory of Bioinformatics and Protein Engineering, Warsaw, Poland Ribonucleic acid (RNA) molecules are master regulators of cells. They play key roles in many molecular processes: transmitting genetic information, sensing cellular signals, relaying responses, and even catalyzing chemical reactions. The function of RNA, especially its ability to interact with other molecules, is encoded in its sequence. To understand how these molecules carry out their biological tasks, we need detailed knowledge of RNA structure, dynamics, and thermodynamics. The latter largely determines how RNA folds and interacts within the cellular environment. Experimentally determining these properties is challenging. Several computational methods have been developed to model the folding of RNA 3D structures and their interactions, mainly with proteins. However, these computational methods are nearing their limits, especially when the biological implications demand calculations of dynamics beyond a few hundred nanoseconds. For researchers facing such challenges, a more effective approach is to use coarse grained modeling. This reduces both the data points and computational effort to a feasible level, while retaining as much essential information as possible. I will present strategies for computational modeling of RNA 3D structures and their interactions with other molecules. These strategies use a suite of methods from my laboratory, based on the SimRNA program. Our methods employ coarse-grained representations of molecules, utilize the Monte Carlo method for sampling conformational space, and use statistical potentials to approximate energy. They also help identify conformations that match biologically relevant structures. Specifically, I will discuss computational methods to determine RNA structure using low-resolution experimental data, such as chemical probing and electron microscopy. References 1. Ponce-Salvatierra, A. et al. Biosci. Rep. 39, BSR20180430 (2019)2. Boniecki, M. J. et al. Nucleic Acids Res. 44, e63 (2016)3. Rocha de Moura, T., et al. Nucleic Acids Res. 52(6): 3419–3432 (2024)

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