Shape measurement for cylindirical structures formed by tyrosine molecules

Habiboglu, M. Gokhan; Uyaver, Şahin

doi:10.1063/1.5136196

Cited by 1 publication

(2 citation statements)

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“…To have a better analytical understanding about the formation of these structures, two measures are used in this study. We apply one cylindricity measure for cylindrical aggregations and use the well-known sphericity measure for spherical formations [12]. We have also taken the ratio of the largest cluster to the total number of molecules into account to reflect the contribution of the degree of clustering.…”

Section: Methodsmentioning

confidence: 99%

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Shape investigations of structures formed by the self-assembly of aromatic amino acids using the density-based spatial clustering of applications with noise algorithm

HABİBOĞLU,

HERNANDEZ,

UYAVER

2022

Turkish Journal of Electrical Engineering and Computer Sciences

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Tyrosine, tryptophan, and phenylalanine are important aromatic amino acids for human health. If they are not properly metabolized, severe rare mental or metabolic diseases can emerge, many of which are not researched enough due to economic priorities. In our previous simulations, all three of these amino acids are discovered to be self-organizing and to have complex aggregations at different temperatures. Two of these essential stable formations are observed during our simulations: tubular-like and spherical-like structures. In this study, we develop and implement a clustering analyzing algorithm using DBSCAN (Density-Based Spatial Clustering of Applications with Noise) to measure the shapes of the formed structures by the self-assembly processes of these amino acids. We present the results in quantitative and qualitative ways. To the best of our knowledge, the geometric shapes of the formed structures by the self-assembly processes of these amino acids are not measured quantitatively in the literature. Analytical measurements and comparisons of these aggregations might help us to identify the self-aggregations quickly at early stages in our simulations and hence provide us with more opportunity to experiment with different parameters of the molecular simulations (like temperature, mixture rates, density etc.). We first implement DBSCAN method to identify the main self-aggregation cluster and then we develop and implement two algorithms to measure the shapes of the formed structures by the self-assembly processes of these amino acids. The measurements, which are completely in line with our simulation results, are presented in quantitative and qualitative ways.

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Section: Methodsmentioning

confidence: 99%

“…The study of the self-assembly of single amino acids is still less worked out compared to the cases of many peptides. Recently in our molecular dynamics simulations, we have investigated the self-assembly processes of the amino acids with aromatic rings, namely, phenylalanine (Phe), tyrosine (Tyr) and tryptophan (Trp) [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%