Computational prediction of RNA-protein interactions

Yıl 2016, Cilt: 4 Sayı: 3, 0 - 0, 01.10.2016

Hilal Kazan

https://doi.org/10.21541/apjes.92217

Öz

RNA-protein interactions play critical roles in diverse cellular processes including post-transcriptional regulation of gene expression and infection by pathogens. As such, characterization of RNA-protein interactions will lead to a better understanding of these mechanisms and associated diseases.  Experimental methods to determine RNA-protein interactions remain tedious and expensive. An alternative strategy is to use computational methods to predict RNA-protein interactions. Here, we develop a random forest model that uses sequence information of an RNA-protein pair to determine whether they will interact or not. We evaluate our model with three diverse datasets including one dataset that has never been used for this purpose before. For the two other datasets, our model gives a better performance than existing methods. We also show that including features that represent the physico-chemical properties of the protein or RNA secondary structure. Altogether, these results show that RNA-protein interactions can be predicted accurately with computational models. 

Kaynakça

• G. Varani and K. Nagai, “RNA recognition by RNP proteins during RNA processing”, Annu. Rev. Biophys. Biomol. Struct., vol. 27, pp. 407-445, 1998.
• T. Glisovic, J.L. Bachorik, J. Yong and G. Dreyfuss, “RNA-binding proteins and post-transcriptional gene regulation.”, FEBS letters, vol. 582 , no14, pp. 1977–1986, June 2008.
• D. Moras, “Aminoacyl-tRNA synthetases.”, Curr. Opin. Struct. Biol., vol 2, pp. 138-142., 1992.
• P.B. Moore “The three-dimensional structure of the ribosome and its components.”, Annu. Rev. Biophys. Biomol. Struct., vol. 27, pp. 35–58, 1998.
• B. Tian, P. C. Bevilacqua, A. Diegelman-Parente and M. B. Mathews, “The double-stranded-RNA-binding motif: interference and much more.”, Nat. Rev. Mol. Cell Biol. vol. 5, pp.1013-1023, 2004.
• K.E. Lukong, K.W. Chang, E.W. Khandjian and S. Richard. “RNA-binding proteins in human genetic disease.” Trends Genet. vol. 24, no. 8 pp. 416-425, 2008.
• J.D. Keene, J.M. Komisarow and M.B. Friedersdorf. “RIP-Chip: the isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts.”, Nat Proc, vol. 1 no.1, pp:302-307, 2006.
• J. Ule, K. Jensen, A. Mele, and, R. B. Darnell. “CLIP: A method for identifying protein-RNA interaction sites in living cells”. Methods, vol. 37, pp. 376–386, 2005.
• M. Hafner et al., "Transcriptome-wide identification of RNA-Binding protein and MicroRNA target sites by PAR-CLIP," Cell, vol. 141, no. 1, pp. 129–141, Apr. 2010.
• D. Ray et al., ”A compendium of RNA-binding motifs for decoding gene regulation.“ Nature, vol. 499, pp.172– 177, 2013.
• V. Pancaldi and J Bahler (2011) In silico characterization and prediction of global protein-mRNA interactions in yeast. Nucleic Acids Research. vol. 39, no. 14, pp. 5286-5836. 2011.
• Y. Wang, X. Chen, Z. Liu, Q. Huang, D. Xu, and X. Zhang, "De novo prediction of RNA-protein interactions from sequence information," Molecular BioSystems., vol. 9, no. 1, pp. 133–42, Nov. 2012.
• V. Suresh, L. Liu, D. Adjeroh, and X. Zhou, "RPI-Pred: Predicting ncRNA-protein interaction using sequence and structural information," Nucleic Acids Research, vol. 43, no. 3, Feb. 2015.
• Q. Lu et al., "Computational prediction of associations between long non-coding RNAs and proteins," BMC Genomics, vol. 14, no. 1, p. 651, 2013.
• B. Lewis et al., "PRIDB: A Protein-RNA interface database," Nucleic Acids Research., vol. 39, Nov. 2010.
• D. J. Hogan, D. P. Riordan, A. P. Gerber, D. Herschlag, and P. O. Brown, "Diverse RNA-Binding proteins interact with functionally related sets of RNAs, suggesting an extensive regulatory system," PLoS Biology, vol. 6, no. 10, p. e255, Oct. 2008.
• J. Shen et al., "Predicting protein-protein interactions based only on sequences information," Proceedings of the National Academy of Sciences of the United States of America., vol. 104, no. 11, pp. 4337–41, Mar. 2007.
• S. Bernhart, I. Hofacker, and P. Stadler, "Local RNA base pairing probabilities in large sequences," Bioinformatics (Oxford, England)., vol. 22, no. 5, pp. 614–5, Dec. 2005.
• S. J. Lange et al., "Global or local? Predicting secondary structure and accessibility in mRNAs," Nucleic Acids Research, vol. 40, no. 12, p. 5215-5226, Feb. 2012.
• Breiman, L. “Random forests.” Machine Learning. vol. 45, pp. 5-32, 2001.
• S. Jones, D. Daley, N. Luscombe, H. Berman, and J. Thornton, "Protein-RNA interactions: A structural analysis," Nucleic Acids Research., vol. 29, no. 4, pp. 943–54, Feb. 2001.