scholarly journals An improved deep learning method for predicting DNA-binding proteins based on contextual features in amino acid sequences v1 (protocols.io.2rdgd26)

protocols.io ◽  
2019 ◽  
Author(s):  
Ruixiong Ma
Keyword(s):  
Deep Learning ◽  
Amino Acid ◽  
Dna Binding ◽  
Binding Proteins ◽  
Dna Binding Proteins ◽  
Amino Acid Sequences ◽  
Learning Method ◽  
Contextual Features

scholarly journals Complete Amino-Acid Sequences of DNA-Binding Proteins HU-1 and HU-2 from Escherichia coli

1980 ◽  
Vol 103 (3) ◽  
pp. 456-461
Author(s):  
B. Laine ◽  
D. Kmiecik ◽  
P. Sautiere ◽  
G. Biserte ◽  
M. Cohen-Solal
Keyword(s):  
Escherichia Coli ◽  
Amino Acid ◽  
Dna Binding ◽  
Binding Proteins ◽  
Dna Binding Proteins ◽  
Amino Acid Sequences

The leucine zipper: a hypothetical structure common to a new class of DNA binding proteins

Science ◽  
1988 ◽  
Vol 240 (4860) ◽  
pp. 1759-1764 ◽  
Author(s):  
WH Landschulz ◽  
PF Johnson ◽  
SL McKnight
Keyword(s):  
Amino Acid ◽  
Dna Binding ◽  
Binding Proteins ◽  
Leucine Zipper ◽  
Regulatory Protein ◽  
Alpha Helix ◽  
Dna Binding Proteins ◽  
Amino Acid Sequences ◽  
Helical Conformation ◽  
Hypothetical Structure

A 30-amino-acid segment of C/EBP, a newly discovered enhancer binding protein, shares notable sequence similarity with a segment of the cellular Myc transforming protein. Display of these respective amino acid sequences on an idealized alpha helix revealed a periodic repetition of leucine residues at every seventh position over a distance covering eight helical turns. The periodic array of at least four leucines was also noted in the sequences of the Fos and Jun transforming proteins, as well as that of the yeast gene regulatory protein, GCN4. The polypeptide segments containing these periodic arrays of leucine residues are proposed to exist in an alpha-helical conformation, and the leucine side chains extending from one alpha helix interdigitate with those displayed from a similar alpha helix of a second polypeptide, facilitating dimerization. This hypothetical structure is referred to as the "leucine zipper," and it may represent a characteristic property of a new category of DNA binding proteins.

Complete Amino-Acid Sequences of DNA-Binding Proteins HU-1 and HU-2 from Escherichia coli

1980 ◽  
Vol 103 (3) ◽  
pp. 447-461 ◽  
Author(s):  
Bernard LAINE ◽  
Daniel KMIECIK ◽  
Pierre SAUTIERE ◽  
Gerard BISERTE ◽  
Michel COHEN-SOLAL
Keyword(s):  
Escherichia Coli ◽  
Amino Acid ◽  
Dna Binding ◽  
Binding Proteins ◽  
Dna Binding Proteins ◽  
Amino Acid Sequences

scholarly journals Evidence for Nucleic Acid Binding Ability and Nucleosome Association of Bombyx mori Nucleopolyhedrovirus BRO Proteins

2000 ◽  
Vol 74 (15) ◽  
pp. 6784-6789 ◽  
Author(s):  
Evgueni A. Zemskov ◽  
WonKyung Kang ◽  
Susumu Maeda
Keyword(s):  
Amino Acid ◽  
Dna Binding ◽  
Bombyx Mori ◽  
Binding Proteins ◽  
Dna Binding Proteins ◽  
Amino Acid Sequences ◽  
Micrococcal Nuclease ◽  
Nucleic Acid Binding ◽  
Bombyx Mori Nucleopolyhedrovirus ◽  
Bmn Cells

ABSTRACT The Bombyx mori nucleopolyhedrovirus (BmNPV) genome contains five related members of the bro gene family, all of which are actively expressed in infected BmN cells. Although their functions are unknown, their amino acid sequences contain a motif found in all known viral and prokaryotic single-stranded DNA binding proteins. To determine if they bind to nucleic acids, we fractionated the nuclei of BmNPV-infected BmN cells using a histone extraction protocol. We detected BRO-A, BRO-C, and BRO-D in the histone H1 fraction using anti-BRO antibodies. Micrococcal nuclease treatment released these BRO proteins from the chromatin fraction, suggesting their involvement in nucleosome structures. Chromatographic fractionation showed that BRO-A and/or BRO-C interacted with core histones. Expression of partial sequences of BRO-A proved that the N-terminal 80 amino acid residues were required for DNA binding activity. We also demonstrated that BmNPV BRO proteins underwent phosphorylation and ubiquitination followed by proteasome degradation, which may explain their distribution in the cytoplasm as well as the nucleus. We propose that BRO-A and BRO-C may function as DNA binding proteins that influence host DNA replication and/or transcription.

scholarly journals Residues in the Swi5 Zinc Finger Protein That Mediate Cooperative DNA Binding with the Pho2 Homeodomain Protein

1998 ◽  
Vol 18 (11) ◽  
pp. 6436-6446 ◽  
Author(s):  
Leena T. Bhoite ◽  
David J. Stillman
Keyword(s):  
Amino Acid ◽  
Dna Binding ◽  
Zinc Finger ◽  
Transcriptional Activation ◽  
Binding Proteins ◽  
Zinc Finger Protein ◽  
Interaction Analysis ◽  
Dna Binding Proteins ◽  
Two Hybrid

ABSTRACT The Swi5 zinc finger and the Pho2 homeodomain DNA-binding proteins bind cooperatively to the HO promoter.Pho2 (also known as Bas2 or Grf10) activates transcription of diverse genes, acting with multiple distinct DNA-binding proteins. We have performed a genetic screen to identify amino acid residues in Swi5 that are required for synergistic transcriptional activation of a reporter construct in vivo. Nine unique amino acid substitutions within a 24-amino-acid region of Swi5, upstream of the DNA-binding domain, reduce expression of promoters that require both Swi5 and Pho2 for activation. In vitro DNA binding experiments show that the mutant Swi5 proteins bind DNA normally, but some mutant Swi5 proteins (resulting from SWI5* mutations) show reduced cooperative DNA binding with Pho2. In vivo experiments show that these SWI5* mutations sharply reduce expression of promoters that require both SWI5 and PHO2, while expression of promoters that require SWI5 but arePHO2 independent is largely unaffected. This suggests that these SWI5* mutations do not affect the ability of Swi5 to bind DNA or activate transcription but specifically affect the region of Swi5 required for interaction with Pho2. Two-hybrid experiments show that amino acids 471 to 513 of Swi5 are necessary and sufficient for interaction with Pho2 and that the SWI5* point mutations cause a severe reduction in this two-hybrid interaction. Analysis of promoter activation by these mutants suggests that this small region of Swi5 has at least two distinct functions, conferring specificity for activation of the HO promoter and for interaction with Pho2.

Identify DNA-Binding Proteins with Optimal Chou’s Amino Acid Composition

2012 ◽  
Vol 19 (4) ◽  
pp. 398-405 ◽  
Author(s):  
Xiao-Wei Zhao ◽  
Xiang-Tao Li ◽  
Zhi-Qiang Ma ◽  
Ming-Hao Yin
Keyword(s):  
Amino Acid ◽  
Dna Binding ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Binding Proteins ◽  
Dna Binding Proteins

scholarly journals Prediction of DNA binding proteins using local features and long-term dependencies with primary sequences based on deep learning

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11262
Author(s):  
Guobin Li ◽  
Xiuquan Du ◽  
Xinlu Li ◽  
Le Zou ◽  
Guanhong Zhang ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Deep Learning ◽  
Dna Binding ◽  
Binding Proteins ◽  
Prediction Models ◽  
Short Term Memory ◽  
Local Features ◽  
Dna Binding Proteins ◽  
Superior Performance

DNA-binding proteins (DBPs) play pivotal roles in many biological functions such as alternative splicing, RNA editing, and methylation. Many traditional machine learning (ML) methods and deep learning (DL) methods have been proposed to predict DBPs. However, these methods either rely on manual feature extraction or fail to capture long-term dependencies in the DNA sequence. In this paper, we propose a method, called PDBP-Fusion, to identify DBPs based on the fusion of local features and long-term dependencies only from primary sequences. We utilize convolutional neural network (CNN) to learn local features and use bi-directional long-short term memory network (Bi-LSTM) to capture critical long-term dependencies in context. Besides, we perform feature extraction, model training, and model prediction simultaneously. The PDBP-Fusion approach can predict DBPs with 86.45% sensitivity, 79.13% specificity, 82.81% accuracy, and 0.661 MCC on the PDB14189 benchmark dataset. The MCC of our proposed methods has been increased by at least 9.1% compared to other advanced prediction models. Moreover, the PDBP-Fusion also gets superior performance and model robustness on the PDB2272 independent dataset. It demonstrates that the PDBP-Fusion can be used to predict DBPs from sequences accurately and effectively; the online server is at http://119.45.144.26:8080/PDBP-Fusion/.

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