News from CRG
In a recent article published in Nature Methods, researchers at the CRG, in collaboration with scientists at EMBL’s site in Monterotondo (Italy) and the California Institute of Technology (US), introduced a new computational tool to predict protein interactions with long non-coding RNAs, which they validated using advanced experimental techniques.
“Long non-coding RNAs interact with various proteins to mediate important cellular functions. Trying to identify these interactions can be a good starting point in order to understand the role of these molecules in the normal functioning of the cell but also in disease,” explains Gian Gaetano Tartaglia, ICREA research professor at the CRG and principal investigator of this article.
The new computational tool, which is called Global Score, allows scientists to predict where, along the sequence of a non-coding RNA, a protein will establish a physical contact. To do so, this algorithm integrates not only the global propensity of the protein to bind a particular RNA but also the local features of such a binding. “The structure of the RNA is absolutely important when predicting protein interactions. Our main challenge was to be able to work with RNA sequences regardless of their length in order to keep a complete view of their structural properties when looking for protein partners,” adds Davide Cirillo, first author of the paper. “The algorithm we have developed integrates this information and allows us not only to predict protein partners but also to prioritize them for experimental validation. This methodological advance will be crucial to better study long non-coding RNAs and their functions”, concludes the researcher.
Cirillo et al. “Quantitative predictions of protein interactions with long non-coding RNAs” Nature Methods. 14, 5-6 (2017). DOI: 10.1038/nmeth.4100