Gianluca Lombardi
Optimization of an RNA coarse-grained force field with Machine Learning.
Rel. Alessandro Pelizzola, Samuela Pasquali, Frédéric Lechenault. Politecnico di Torino, Corso di laurea magistrale in Physics Of Complex Systems (Fisica Dei Sistemi Complessi), 2022
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Abstract
Ribonucleic acid, or RNA, is a linear biological polymer involved in a wide variety of functions, both in human and in viral cells, as highlighted also by the recent pandemic. Functionality of RNA molecules is strongly linked to their three-dimensional structure, which is the reason why the RNA folding problem has become of great interest in recent years. Differently from proteins, RNA structures are less stable and heavily depend on the biochemical conditions of the surrounding environment. Among the proposed solutions to the problem, one possible approach relies on the design of coarse-grained physical models to speed up molecular dynamics simulations for RNA folding, that would be otherwise too expensive in term of computational cost .
Among these models, HiRE-RNA is a high resolution force field, where each nucleotide is represented as 6-7 beads and with specific functional forms for the interactions, designed to reproduce experimental results concerning simulations and extraction of thermodynamical quantities
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