Аннотация.

Предлагается классификация аминокислотных остатков по признакам контактов аминокислот белков с нуклеотидами ДНК, рассматриваются классификации с разными типами размытости. Для определения количества и площади контактов каждой аминокислоты с каждым нуклеотидом использовалось разбиение Вороного-Делоне. Показано существование инвариантов кластеризации аминокислот, а также то, что размытая классификация аминокислот на 6 классов является оптимальной для задачи белок-нуклеинового распознавания.

Ключевые слова:

кластерный анализ, размытая классификация, контакты аминокислота–нуклеотид, разбиение Вороного–Делоне, свойства аминокислотных остатков.

Стр. 85-96.

Полная версия статьи в формате pdf. 

E.N. Kuznetsov, A.A. Anashkina, A.A. Dorofeyuk, J.A. Dorofeyuk, A.G. Spiro

"Cluster analysis of DNA-protein spatial contacts using the Voronoi-Delaunay procedure"

Abstract. The paper deals with the amino acid residues classification on the basis of the amino acids proteins - DNA nucleotides contacts parameters. Amino acid residues have many different properties and functions, and can simultaneously belong to different classes. Therefore, it was interesting to use the classification of amino acids with different types of fuzzing. Voronoi-Delaunay tessellation was used to determine the contacts number and area for each amino acid with each nucleotide in 1937 complexes. General variation approach was used for the amino acids classification of with dif¬ferent types of fusion. Results: It was shown that about 30% of all contacts between amino acids and nucleotides in protein-DNA complexes are not random. Crisp classification methods showed the existence of clustering invariants of amino acids at the lowest level of association. It was shown by fuzzy classification methods that six classes are optimal for protein-DNA recog¬nition task. Conclusions: Fuzzy classification of amino acids data can be used to construct the substitution matrix for DNA-binding protein sequences and protein-DNA binding analysis.

Keywords: cluster analysis, crisp classification, fuzzy classification, protein-DNA interactions.

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