Literature DB >> 21231356

Factors governing fibrillogenesis of polypeptide chains revealed by lattice models.

Mai Suan Li1, Nguyen Truong Co, Govardhan Reddy, Chin-Kun Hu, J E Straub, D Thirumalai.   

Abstract

Using lattice models we explore the factors that determine the tendencies of polypeptide chains to aggregate by exhaustively sampling the sequence and conformational space. The morphologies of the fibril-like structures and the time scales (τ(fib)) for their formation depend on a balance between hydrophobic and Coulomb interactions. The extent of population of an ensemble of N* structures, which are fibril-prone structures in the spectrum of conformations of an isolated protein, is the major determinant of τ(fib). This observation is used to determine the aggregating sequences by exhaustively exploring the sequence space, thus providing a basis for genome wide search of fragments that are aggregation prone.

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Year:  2010        PMID: 21231356     DOI: 10.1103/PhysRevLett.105.218101

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  28 in total

1.  Spontaneous formation of twisted Aβ(16-22) fibrils in large-scale molecular-dynamics simulations.

Authors:  Mookyung Cheon; Iksoo Chang; Carol K Hall
Journal:  Biophys J       Date:  2011-11-15       Impact factor: 4.033

2.  Intrinsic disorder modulates protein self-assembly and aggregation.

Authors:  Alfonso De Simone; Craig Kitchen; Ann H Kwan; Margaret Sunde; Christopher M Dobson; Daan Frenkel
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-16       Impact factor: 11.205

3.  Side-chain hydrophobicity and the stability of Aβ₁₆₋₂₂ aggregates.

Authors:  Workalemahu M Berhanu; Ulrich H E Hansmann
Journal:  Protein Sci       Date:  2012-12       Impact factor: 6.725

4.  Crucial role of nonspecific interactions in amyloid nucleation.

Authors:  Anđela Šarić; Yassmine C Chebaro; Tuomas P J Knowles; Daan Frenkel
Journal:  Proc Natl Acad Sci U S A       Date:  2014-12-01       Impact factor: 11.205

Review 5.  Amyloid β Protein and Alzheimer's Disease: When Computer Simulations Complement Experimental Studies.

Authors:  Jessica Nasica-Labouze; Phuong H Nguyen; Fabio Sterpone; Olivia Berthoumieu; Nicolae-Viorel Buchete; Sébastien Coté; Alfonso De Simone; Andrew J Doig; Peter Faller; Angel Garcia; Alessandro Laio; Mai Suan Li; Simone Melchionna; Normand Mousseau; Yuguang Mu; Anant Paravastu; Samuela Pasquali; David J Rosenman; Birgit Strodel; Bogdan Tarus; John H Viles; Tong Zhang; Chunyu Wang; Philippe Derreumaux
Journal:  Chem Rev       Date:  2015-03-19       Impact factor: 60.622

6.  Kinetics and mechanical stability of the fibril state control fibril formation time of polypeptide chains: A computational study.

Authors:  Maksim Kouza; Nguyen Truong Co; Mai Suan Li; Sebastian Kmiecik; Andrzej Kolinski; Andrzej Kloczkowski; Irina Alexandra Buhimschi
Journal:  J Chem Phys       Date:  2018-06-07       Impact factor: 3.488

7.  Influence of temperature on formation of perfect tau fragment fibrils using PRIME20/DMD simulations.

Authors:  Mookyung Cheon; Iksoo Chang; Carol K Hall
Journal:  Protein Sci       Date:  2012-09-17       Impact factor: 6.725

8.  Oligomerization of FVFLM peptides and their ability to inhibit beta amyloid peptides aggregation: consideration as a possible model.

Authors:  M Kouza; A Banerji; A Kolinski; I A Buhimschi; A Kloczkowski
Journal:  Phys Chem Chem Phys       Date:  2017-01-25       Impact factor: 3.676

9.  Propensity to form amyloid fibrils is encoded as excitations in the free energy landscape of monomeric proteins.

Authors:  Pavel I Zhuravlev; Govardhan Reddy; John E Straub; D Thirumalai
Journal:  J Mol Biol       Date:  2014-05-17       Impact factor: 5.469

10.  Impact of sequence on the molecular assembly of short amyloid peptides.

Authors:  Victoria A Wagoner; Mookyung Cheon; Iksoo Chang; Carol K Hall
Journal:  Proteins       Date:  2014-02-18
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