scholarly journals Molecular dynamics of DNA-binding protein and its 2D-crystals

2021 ◽  
Vol 2056 (1) ◽  
pp. 012016
Author(s):  
E V Tereshkin ◽  
K B Tereshkina ◽  
Y F Krupyanskii
Keyword(s):  
Molecular Dynamics ◽  
Dna Binding ◽  
Binding Protein ◽  
Dna Binding Protein ◽  
Dynamics Simulation ◽  
Amino Acid Residues ◽  
Wide Range ◽  
Living Nature ◽  
Dps Protein ◽  
2D Crystals

Abstract In this work the dodecamers and the two-dimensional crystals of DNA-binding protein from starved cells (DPS) of Escherichia coli bacteria were investigated. The DPS monomer contains 167 amino acids residues. It can form dimers, trimers, and dodecamers. The versatility of the DPS protein structure can be used to design nanomaterials with structures and functions not found in living nature. The ability of this protein to self-assemble into complex shapes and structures defined on the nanometer scale can make them highly demanded for various technological applications. It was used all-atom classical molecular dynamics simulation on 0.1 microsecond scale to obtain the spatial and energy characteristics of the proteins and the components of the simulation box. The fluctuation mobility of DPS protein at various temperatures was discussed. The diffusion of ions in the presence of dodecamers and 2D crystals was compared. It has been shown that this protein retains its ability to accumulate ions in a wide range of biological temperatures from 277 to 369K. It also retains the mobility of key amino acid residues involved in the formation of nanocrystals and the transport of ions into the cavity, even at low physiological temperatures.

Damage-specific DNA binding protein 1 (DDB1): a protein with a wide range of functions

2011 ◽  
Vol 43 (12) ◽  
pp. 1664-1667 ◽  
Author(s):  
Barbara Iovine ◽  
Maria Luigia Iannella ◽  
Maria Assunta Bevilacqua
Keyword(s):  
Dna Binding ◽  
Binding Protein ◽  
Dna Binding Protein ◽  
Wide Range ◽  
Range Of Functions

scholarly journals HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Rianon Zaman ◽  
Shahana Yasmin Chowdhury ◽  
Mahmood A. Rashid ◽  
Alok Sharma ◽  
Abdollah Dehzangi ◽  
...  
Keyword(s):  
Dna Binding ◽  
Binding Protein ◽  
Prediction Method ◽  
Dna Binding Protein ◽  
Support Vector ◽  
Classification Technique ◽  
Protein Prediction ◽  
Wide Range ◽  
Vector Machines ◽  
Benchmark Datasets

DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

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