Literature DB >> 28915764

Sequence dependent aggregation of peptides and fibril formation.

Nguyen Ba Hung1, Duy-Manh Le2, Trinh X Hoang1.   

Abstract

Deciphering the links between amino acid sequence and amyloid fibril formation is key for understanding protein misfolding diseases. Here we use Monte Carlo simulations to study the aggregation of short peptides in a coarse-grained model with hydrophobic-polar (HP) amino acid sequences and correlated side chain orientations for hydrophobic contacts. A significant heterogeneity is observed in the aggregate structures and in the thermodynamics of aggregation for systems of different HP sequences and different numbers of peptides. Fibril-like ordered aggregates are found for several sequences that contain the common HPH pattern, while other sequences may form helix bundles or disordered aggregates. A wide variation of the aggregation transition temperatures among sequences, even among those of the same hydrophobic fraction, indicates that not all sequences undergo aggregation at a presumable physiological temperature. The transition is found to be the most cooperative for sequences forming fibril-like structures. For a fibril-prone sequence, it is shown that fibril formation follows the nucleation and growth mechanism. Interestingly, a binary mixture of peptides of an aggregation-prone and a non-aggregation-prone sequence shows the association and conversion of the latter to the fibrillar structure. Our study highlights the role of a sequence in selecting fibril-like aggregates and also the impact of a structural template on fibril formation by peptides of unrelated sequences.

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Year:  2017        PMID: 28915764     DOI: 10.1063/1.5001517

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  3 in total

Review 1.  Contact-Based Analysis of Aggregation of Intrinsically Disordered Proteins.

Authors:  Marek Cieplak; Łukasz Mioduszewski; Mateusz Chwastyk
Journal:  Methods Mol Biol       Date:  2022

2.  Computational Models for the Study of Protein Aggregation.

Authors:  Nguyen Truong Co; Mai Suan Li; Pawel Krupa
Journal:  Methods Mol Biol       Date:  2022

3.  Pseudo-Improper-Dihedral Model for Intrinsically Disordered Proteins.

Authors:  Łukasz Mioduszewski; Bartosz Różycki; Marek Cieplak
Journal:  J Chem Theory Comput       Date:  2020-06-12       Impact factor: 6.006

  3 in total

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