Literature DB >> 17277419

DNA deformation energy as an indirect recognition mechanism in protein-DNA interactions.

Kimberly A Aeling1, Nicholas R Steffen, Matthew Johnson, G Wesley Hatfield, Richard H Lathrop, Donald F Senear.   

Abstract

Proteins that bind to specific locations in genomic DNA control many basic cellular functions. Proteins detect their binding sites using both direct and indirect recognition mechanisms. Deformation energy, which models the energy required to bend DNA from its native shape to its shape when bound to a protein, has been shown to be an indirect recognition mechanism for one particular protein, Integration Host Factor (IHF). This work extends the analysis of deformation to two other DNA-binding proteins, CRP and SRF, and two endonucleases, I-CreI and I-PpoI. Known binding sites for all five proteins showed statistically significant differences in mean deformation energy as compared to random sequences. Binding sites for the three DNA-binding proteins and one of the endonucleases had mean deformation energies lower than random sequences. Binding sites for I-PpoI had mean deformation energy higher than random sequences. Classifiers that were trained using the deformation energy at each base pair step showed good cross-validated accuracy when classifying unseen sequences as binders or nonbinders. These results support DNA deformation energy as an indirect recognition mechanism across a wider range of DNA-binding proteins. Deformation energy may also have a predictive capacity for the underlying catalytic mechanism of DNA-binding enzymes.

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17277419     DOI: 10.1109/TCBB.2007.1000

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  2 in total

1.  A theoretical investigation of DNA dynamics and desolvation kinetics for zinc finger proteinZif268.

Authors:  Shayoni Dutta; Yoshita Agrawal; Aditi Mishra; Jaspreet Kaur Dhanjal; Durai Sundar
Journal:  BMC Genomics       Date:  2015-12-09       Impact factor: 3.969

2.  iProDNA-CapsNet: identifying protein-DNA binding residues using capsule neural networks.

Authors:  Binh P Nguyen; Quang H Nguyen; Giang-Nam Doan-Ngoc; Thanh-Hoang Nguyen-Vo; Susanto Rahardja
Journal:  BMC Bioinformatics       Date:  2019-12-27       Impact factor: 3.169

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.