Literature DB >> 21361378

Scoring function based approach for locating binding sites and understanding recognition mechanism of protein-DNA complexes.

M Michael Gromiha1, Kazuhiko Fukui.   

Abstract

Protein-DNA recognition plays an essential role in the regulation of gene expression. Understanding the recognition mechanism of protein-DNA complexes is a challenging task in molecular and computational biology. In this work, a scoring function based approach has been developed for identifying the binding sites and delineating the important residues for binding in protein-DNA complexes. This approach considers both the repulsive interactions and the effect of distance between atoms in protein and DNA. The results showed that positively charged, polar, and aromatic residues are important for binding. These residues influence the formation of electrostatic, hydrogen bonding, and stacking interactions. Our observation has been verified with experimental binding specificity of protein-DNA complexes and found to be in good agreement with experiments. The comparison of protein-RNA and protein-DNA complexes reveals that the contribution of phosphate atoms in DNA is twice as large as in protein-RNA complexes. Furthermore, we observed that the positively charged, polar, and aromatic residues serve as hotspot residues in protein-RNA complexes, whereas other residues also altered the binding specificity in protein-DNA complexes. Based on the results obtained in the present study and related reports, a plausible mechanism has been proposed for the recognition of protein-DNA complexes.

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Year:  2011        PMID: 21361378     DOI: 10.1021/ci1003703

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  10 in total

1.  Conformational contribution to thermodynamics of binding in protein-peptide complexes through microscopic simulation.

Authors:  Amit Das; J Chakrabarti; Mahua Ghosh
Journal:  Biophys J       Date:  2013-03-19       Impact factor: 4.033

2.  Comparative Analysis of the IclR-Family of Bacterial Transcription Factors and Their DNA-Binding Motifs: Structure, Positioning, Co-Evolution, Regulon Content.

Authors:  Inna A Suvorova; Mikhail S Gelfand
Journal:  Front Microbiol       Date:  2021-06-10       Impact factor: 5.640

3.  GntR Family of Bacterial Transcription Factors and Their DNA Binding Motifs: Structure, Positioning and Co-Evolution.

Authors:  Inna A Suvorova; Yuri D Korostelev; Mikhail S Gelfand
Journal:  PLoS One       Date:  2015-07-07       Impact factor: 3.240

4.  Exploiting a reduced set of weighted average features to improve prediction of DNA-binding residues from 3D structures.

Authors:  Yi Xiong; Junfeng Xia; Wen Zhang; Juan Liu
Journal:  PLoS One       Date:  2011-12-08       Impact factor: 3.240

5.  Sequence and structural features of binding site residues in protein-protein complexes: comparison with protein-nucleic acid complexes.

Authors:  M Michael Gromiha; N Saranya; S Selvaraj; B Jayaram; Kazuhiko Fukui
Journal:  Proteome Sci       Date:  2011-10-14       Impact factor: 2.480

6.  Structure based approach for understanding organism specific recognition of protein-RNA complexes.

Authors:  Raju Nagarajan; Sonia Pankaj Chothani; Chandrasekaran Ramakrishnan; Masakazu Sekijima; M Michael Gromiha
Journal:  Biol Direct       Date:  2015-03-07       Impact factor: 4.540

7.  PreDBA: A heterogeneous ensemble approach for predicting protein-DNA binding affinity.

Authors:  Wenyi Yang; Lei Deng
Journal:  Sci Rep       Date:  2020-01-28       Impact factor: 4.379

8.  Novel approach for selecting the best predictor for identifying the binding sites in DNA binding proteins.

Authors:  R Nagarajan; Shandar Ahmad; M Michael Gromiha
Journal:  Nucleic Acids Res       Date:  2013-06-20       Impact factor: 16.971

9.  A new supervised over-sampling algorithm with application to protein-nucleotide binding residue prediction.

Authors:  Jun Hu; Xue He; Dong-Jun Yu; Xi-Bei Yang; Jing-Yu Yang; Hong-Bin Shen
Journal:  PLoS One       Date:  2014-09-17       Impact factor: 3.240

Review 10.  PDBparam: Online Resource for Computing Structural Parameters of Proteins.

Authors:  R Nagarajan; A Archana; A Mary Thangakani; S Jemimah; D Velmurugan; M Michael Gromiha
Journal:  Bioinform Biol Insights       Date:  2016-06-14
  10 in total

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