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DOI 10.1063/1.4942115

Медицинская библиотека · The Journal of chemical physics · 2016

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

Ilie Ioana M, den Otter Wouter K, Briels Wim J

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

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.

Для цитирования: Ilie Ioana M, den Otter Wouter K, Briels Wim J. A coarse grained protein model with internal degrees of freedom. Application to α-synuclein aggregation.. The Journal of chemical physics. 2016. DOI: 10.1063/1.4942115.

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