Literature DB >> 26931727

A coarse grained protein model with internal degrees of freedom. Application to α-synuclein aggregation.

Ioana M Ilie1, Wouter K den Otter1, Wim J Briels1.   

Abstract

Particles in simulations are traditionally endowed with fixed interactions. While this is appropriate for particles representing atoms or molecules, objects with significant internal dynamics--like sequences of amino acids or even an entire protein--are poorly modelled by invariable particles. We develop a highly coarse grained polymorph patchy particle with the ultimate aim of simulating proteins as chains of particles at the secondary structure level. Conformational changes, e.g., a transition between disordered and β-sheet states, are accommodated by internal coordinates that determine the shape and interaction characteristics of the particles. The internal coordinates, as well as the particle positions and orientations, are propagated by Brownian Dynamics in response to their local environment. As an example of the potential offered by polymorph particles, we model the amyloidogenic intrinsically disordered protein α-synuclein, involved in Parkinson's disease, as a single particle with two internal states. The simulations yield oligomers of particles in the disordered state and fibrils of particles in the "misfolded" cross-β-sheet state. The aggregation dynamics is complex, as aggregates can form by a direct nucleation-and-growth mechanism and by two-step-nucleation through conversions between the two cluster types. The aggregation dynamics is complex, with fibrils formed by direct nucleation-and-growth, by two-step-nucleation through the conversion of an oligomer and by auto-catalysis of this conversion.

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Year:  2016        PMID: 26931727     DOI: 10.1063/1.4942115

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


  6 in total

1.  Amyloid-β (Aβ42) Peptide Aggregation Rate and Mechanism on Surfaces with Widely Varied Properties: Insights from Brownian Dynamics Simulations.

Authors:  Timothy Cholko; Joseph Barnum; Chia-En A Chang
Journal:  J Phys Chem B       Date:  2020-06-26       Impact factor: 2.991

Review 2.  Bottom-up Coarse-Graining: Principles and Perspectives.

Authors:  Jaehyeok Jin; Alexander J Pak; Aleksander E P Durumeric; Timothy D Loose; Gregory A Voth
Journal:  J Chem Theory Comput       Date:  2022-09-07       Impact factor: 6.578

Review 3.  Biomolecular Assemblies: Moving from Observation to Predictive Design.

Authors:  Corey J Wilson; Andreas S Bommarius; Julie A Champion; Yury O Chernoff; David G Lynn; Anant K Paravastu; Chen Liang; Ming-Chien Hsieh; Jennifer M Heemstra
Journal:  Chem Rev       Date:  2018-10-03       Impact factor: 60.622

Review 4.  Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis.

Authors:  Phuong H Nguyen; Ayyalusamy Ramamoorthy; Bikash R Sahoo; Jie Zheng; Peter Faller; John E Straub; Laura Dominguez; Joan-Emma Shea; Nikolay V Dokholyan; Alfonso De Simone; Buyong Ma; Ruth Nussinov; Saeed Najafi; Son Tung Ngo; Antoine Loquet; Mara Chiricotto; Pritam Ganguly; James McCarty; Mai Suan Li; Carol Hall; Yiming Wang; Yifat Miller; Simone Melchionna; Birgit Habenstein; Stepan Timr; Jiaxing Chen; Brianna Hnath; Birgit Strodel; Rakez Kayed; Sylvain Lesné; Guanghong Wei; Fabio Sterpone; Andrew J Doig; Philippe Derreumaux
Journal:  Chem Rev       Date:  2021-02-05       Impact factor: 60.622

5.  Physical determinants of the self-replication of protein fibrils.

Authors:  Alexander K Buell; Georg Meisl; Anđela Šarić; Thomas C T Michaels; Christopher M Dobson; Sara Linse; Tuomas P J Knowles; Daan Frenkel
Journal:  Nat Phys       Date:  2016-07-18       Impact factor: 20.034

Review 6.  Computational models for studying physical instabilities in high concentration biotherapeutic formulations.

Authors:  Marco A Blanco
Journal:  MAbs       Date:  2022 Jan-Dec       Impact factor: 5.857

  6 in total

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