Welcome to the “one stop shop” for Saccharomyces cerevisiae protein sensitive sequence similarity predictions!
Despite decades of research and the availability of the full genomic sequence of the bakers yeast S. cerevisiae, still a large fraction of its genome is not functionally annotated. This hinders our ability to fully understand cellular activity and suggests that many additional processes await discovery. The last years have shown an explosion of high-quality genomic and structural data from multiple organisms, ranging from bacteria to mammals. New computational methods now allow us to integrate these data and extract meaningful insights into the functional identity of uncharacterized proteins in yeast.
Hence, we took advantage of a powerful available tool: HHSearch (Steinegger et al., 2019) a sensitive sequence prediction algorithm. We used HHSearch to compare all yeast proteins to known datasets of structures. Using this approach, we found that over 5000 of S. Cerevisiae proteins have predicted similar proteins in non-fungi organisms and 40% of S. Cerevisiae proteins had predicted similar proteins in the human proteome.
Here, we created a database enabling you to rapidly retrieve such sensitive sequence similarity predictions for all yeast proteins. It is important to stress again that we did not create the prediction algorithm used here but rather used the powerful algorithm of HHSearch (Steinegger et al., 2019). However, we find that it is very useful to employ our web-based platform tool to rapidly retrieve similarity information for multiple proteins.
You are welcome to search for any specific protein or a list of proteins or download all of the source data.