We propose a simple general framework to predict folding, native states, energy barriers, protein unfolding, as well as mutation induced diseases and other protein structural analyses. The model should not be considered as an alternative to classical approaches (Molecular Dynamics or Monte Carlo) because it neglects low scale details and rather focuses on global features of proteins and structural information. We aim at the description of phenomena that are out of the range of classical molecular modeling approaches due to the large computational cost: multimolecular interactions, cyclic behavior under variable external interactions, and similar. To demonstrate the effectiveness of the approach in a real case, we focus on the folding and unfolding behavior of tropoelastin and its mutations. Specifically, we derive a discrete mechanical model whose structure is deduced based on a coarse graining approach that allows us to group the amino acids sequence in a smaller number of ‘equivalent’ masses. Nearest neighbor energy terms are then introduced to reproduce the interaction of such amino acid groups. Nearest and non-nearest neighbor energy terms, inter and intra functional blocks are phenomenologically added in the form of Morse potentials. As we show, the resulting system reproduces important properties of the folding-unfolding mechanical response, including the monotonic and cyclic force-elongation behavior, representing a physiologically important information for elastin. The comparison with the experimental behavior of mutated tropoelastin confirms the predictivity of the model.

A coarse-grained mechanical model for folding and unfolding of tropoelastin with possible mutations / Florio, Giuseppe; Pugno, Nicola M.; Buehler, Markus J.; Puglisi, Giuseppe. - In: ACTA BIOMATERIALIA. - ISSN 1742-7061. - 134:(2021), pp. 477-489. [10.1016/j.actbio.2021.07.032]

A coarse-grained mechanical model for folding and unfolding of tropoelastin with possible mutations

Pugno, Nicola M.;
2021

Abstract

We propose a simple general framework to predict folding, native states, energy barriers, protein unfolding, as well as mutation induced diseases and other protein structural analyses. The model should not be considered as an alternative to classical approaches (Molecular Dynamics or Monte Carlo) because it neglects low scale details and rather focuses on global features of proteins and structural information. We aim at the description of phenomena that are out of the range of classical molecular modeling approaches due to the large computational cost: multimolecular interactions, cyclic behavior under variable external interactions, and similar. To demonstrate the effectiveness of the approach in a real case, we focus on the folding and unfolding behavior of tropoelastin and its mutations. Specifically, we derive a discrete mechanical model whose structure is deduced based on a coarse graining approach that allows us to group the amino acids sequence in a smaller number of ‘equivalent’ masses. Nearest neighbor energy terms are then introduced to reproduce the interaction of such amino acid groups. Nearest and non-nearest neighbor energy terms, inter and intra functional blocks are phenomenologically added in the form of Morse potentials. As we show, the resulting system reproduces important properties of the folding-unfolding mechanical response, including the monotonic and cyclic force-elongation behavior, representing a physiologically important information for elastin. The comparison with the experimental behavior of mutated tropoelastin confirms the predictivity of the model.
Florio, Giuseppe; Pugno, Nicola M.; Buehler, Markus J.; Puglisi, Giuseppe
A coarse-grained mechanical model for folding and unfolding of tropoelastin with possible mutations / Florio, Giuseppe; Pugno, Nicola M.; Buehler, Markus J.; Puglisi, Giuseppe. - In: ACTA BIOMATERIALIA. - ISSN 1742-7061. - 134:(2021), pp. 477-489. [10.1016/j.actbio.2021.07.032]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11572/332202
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