ArticleBiology direct2015
Structure based approach for understanding organism specific recognition of protein-RNA complexes.
Article in Biology direct, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 17 citations in OpenAlex.
- Bioinformatics classification of mutations in patients with Mucopolysaccharidosis IIIA.Metabolic brain disease · 2019Article
- Computational insights of K1444N substitution in GAP-related domain of NF1 gene associated with neurofibromatosis type 1 disease: a molecular modeling and dynamics approach.Metabolic brain disease · 2018Article
- A structural dissection of protein-RNA interactions based on different RNA base areas of interfaces.RSC advances · 2018Article
- Exploring the molecular basis of RNA recognition by the dimeric RNA-binding protein via molecular simulation methods.RNA biology · 2016Article
- PDBparam: Online Resource for Computing Structural Parameters of Proteins.Bioinformatics and biology insights · 2016Review
- DNA-binding protein prediction using plant specific support vector machines: validation and application of a new genome annotation tool.Nucleic acids research · 2015Article
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Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundProtein-RNA interactions perform diverse functions within the cell. Understanding the recognition mechanism of protein-RNA complexes has been a challenging task in molecular and computational biology. In earlier works, the recognition mechanisms have been studied for a specific complex or using a set of non-redundant complexes. In this work, we have constructed 18 sets of same protein-RNA complexes belonging to different organisms from Protein Data Bank (PDB). The similarities and differences in each set of complexes have been revealed in terms of various sequence and structure based features such as root mean square deviation, sequence homology, propensity of binding site residues, variance, conservation at binding sites, binding segments, binding motifs of amino acid residues and nucleotides, preferred amino acid-nucleotide pairs and influence of neighboring residues for binding.
resultsWe found that the proteins of mesophilic organisms have more number of binding sites than thermophiles and the binding propensities of amino acid residues are distinct in E. coli, H. sapiens, S. cerevisiae, thermophiles and archaea. Proteins prefer to bind with RNA using a single residue segment in all the organisms while RNA prefers to use a stretch of up to six nucleotides for binding with proteins. We have developed amino acid residue-nucleotide pair potentials for different organisms, which could be used for predicting the binding specificity. Further, molecular dynamics simulation studies on aspartyl tRNA synthetase complexed with aspartyl tRNA showed specific modes of recognition in E. coli, T. thermophilus and S. cerevisiae.
conclusionBased on structural analysis and molecular dynamics simulations we suggest that the mode of recognition depends on the type of the organism in a protein-RNA complex.
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