Computational molecular modelling as a platform for a deeper understanding of protein dynamics and rational drug design

Authors

  • Gianvito Grasso Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Scuola Universitaria Professionale della Svizzera Italiana (SUPSI), Università della Svizzera Italiana (USI), Centro Galleria 2, Manno
  • Lorenzo Pallante Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin
  • Jack A. Tuszynski Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin
  • Umberto Morbiducci Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin
  • Marco A. Deriu Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin

DOI:

https://doi.org/10.4081/bse.87

Keywords:

Molecular modelling, drug design neurodegenerative, protein folding

Abstract

Elucidating structural features of protein aggregation at molecular level may provide novel opportunities for overarching therapeutic approaches such as blocking common aggregation-induced cellular toxicity pathways. In this context molecular modelling stimulates further research on amyloid aggregation modulators and modelling platforms can be used to test the efficiency of potential aggregation inhibitors aimed at destabilizing/reducing the stability of the amyloidogenic proteins

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Author Biography

  • Lorenzo Pallante, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin

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References

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Published

11-02-2020

Issue

Vol. 1 No. 1 (2020)

Section

Original Articles

License

Copyright (c) 2019 The Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.

How to Cite

Computational molecular modelling as a platform for a deeper understanding of protein dynamics and rational drug design. (2020). Biomedical Science and Engineering, 1(1). https://doi.org/10.4081/bse.87