Self-assembly of aromatic amino acids: a molecular dynamics study

Literature Information

Publication Date 2018-11-27
DOI 10.1039/C8CP06239K
Impact Factor 3.676
Authors

Sahin Uyaver, Helen W. Hernandez, M. Gokhan Habiboglu


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Abstract

The self assembly processes of aromatic amino acids, phenylalanine, tyrosine, and tryptophan have been simulated and were observed to form fibril-like aggregates linked to certain rare diseases and instances of biological membrane disruption. Pure systems and their mixtures were studied systematically at constant temperatures and free energy landscapes were produced describing the height and the number of assembled monomers associated with lower energy structures. Consistent with some previous work, aromatic amino acid monomers display a tendency to arrange with a four-fold symmetry. The occurrence of this and other ordered structures increases at higher temperatures. At lower temperatures our binary mixture simulations indicate that increasing tryptophan content drives the assembly process away from the formation of distinct nanostructures and toward disordered aggregates which is in line with experimental observations of pure tryptophan solutions. This work provides molecular level insight to a variety of different physical phenomena relevant to fields including human disease.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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