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Montepietra, Daniele, (2023)  - Combinazione di simulazioni Enhanced Sampling, reti neurali e tecniche FRET per lo studio della struttura e della dinamica di small Heat Shock Proteins  - , Tesi di dottorato - (, , Universitą degli studi di Modena e Reggio Emilia ) - pagg. -

Abstract: Intrinsically disordered proteins (IDPs) are abundant in cells and have central roles in protein-protein interaction networks. Many are involved in cancer, aging, and neurodegenerative diseases. IDPs do not possess a single native structure but an ensemble of possible conformations related to interactions with binding partners. Due to this inherent flexibility, conventional methods for determining the structure of globular proteins may not be directly applicable to IDPs. A primary aim of this work was to use Enhanced Sampling Molecular Dynamics simulations in conjunction with Neural Network algorithms and FRET biophysical techniques to achieve a deeper understanding of the structure and dynamics of a specific IDP, namely Heat Shock Protein B8 (HSPB8), a human chaperone involved in preventing the aggregation of misfolded proteins, whose mutation leads to neurodegenerative diseases. HSPB8 consists of a conserved structure called the α-crystallin domain and two intrinsically disordered regions (IDRs). At present, no experimental 3D structures are available for wt HSPB8 and its K141E variant. To establish suitable force field parameters and a computational workflow for simulating IDPs, extensive Temperature Replica Exchange (TREMD) simulations of HSPB8 variants were analyzed with a Neural Network algorithm called EncoderMap, and the results were compared to available experimental data. The findings allowed us to determine key factors affecting the structure of the HSPB8 K141E variant. Indeed, its structures tend to be more compact, and the hydrophobic area exposed to the solvent is reduced. These features likely play a role in the K141E reduced chaperone activity. Because IDPs are highly sensitive to environmental conditions, the effects of high ionic strength on the dynamics of HSPB8 IDRs were also investigated. The results show that ionic strength might have differential effects on the conformational propensities of distinct regions of HSPB8. This information will help to understand the mutant's behavior and determine suitable conditions for accurately studying it. The effect of small-molecule binding to IDPs was investigated by simulating HSPB8 variants in the presence of paroxetine, a small molecule commonly found in antidepressant drugs that was shown to have a high affinity for HSPB8 and is able to partially restore the chaperone activity in the mutated K141E variant. Our results show that the paroxetine effect is stronger on the K141E variant and affects the compactness of its conformations. To directly compare computational results with smFRET experiments, we developed FRETpredict, a Python program to calculate FRET efficiency from protein structures and trajectories based on the Rotamer Library Approach. This software is freely available on GitHub (KULL-Centre/FRETpredict/) and as a Python PyPI package. Moreover, Molecular Dynamics simulations were employed to design a novel FRET sensor for the detection of Sars-Cov-2 spike protein. The results obtained in this Ph.D. thesis provide the first 3D structural characterization of HSPB8 and reveal the effects of the pathogenic K141E mutation on its conformational ensembles. These results offer the possibility of rationalizing the pathogenic effects of the K141E mutation in terms of conformational changes. This work has helped to improve the understanding of how HSPB8 structure and dynamics are related to environmental changes such as ionic strength and the presence of small molecules. The FRETpredict software, efficiently operating on large protein conformational ensembles, facilitates the validation or refinement of molecular models and the interpretation of experimental data.