TY - JOUR
T1 - A similarity-based method for predicting enzymatic functions in yeast uncovers a new AMP hydrolase
AU - Cohen, Nir
AU - Kahana, Amit
AU - Schuldiner, Maya
N1 - Publisher Copyright: © 2022 The Author(s)
PY - 2022/4/15
Y1 - 2022/4/15
N2 - Despite decades of research and the availability of the full genomic sequence of the baker's yeast Saccharomyces 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 recent 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. Here, we created a database of sensitive sequence similarity predictions for all yeast proteins. We use this information to identify candidate enzymes for known biochemical reactions whose enzymes are unidentified, and show how this provides a powerful basis for experimental validation. Using one pathway as a test case we pair a new function for the previously uncharacterized enzyme Yhr202w, as an extra-cellular AMP hydrolase in the NAD degradation pathway. Yhr202w, which we now term Smn1 for Scavenger MonoNucleotidase 1, is a highly conserved protein that is similar to the human protein E5NT/CD73, which is associated with multiple cancers. Hence, our new methodology provides a paradigm, that can be adopted to other organisms, for uncovering new enzymatic functions of uncharacterized proteins.
AB - Despite decades of research and the availability of the full genomic sequence of the baker's yeast Saccharomyces 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 recent 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. Here, we created a database of sensitive sequence similarity predictions for all yeast proteins. We use this information to identify candidate enzymes for known biochemical reactions whose enzymes are unidentified, and show how this provides a powerful basis for experimental validation. Using one pathway as a test case we pair a new function for the previously uncharacterized enzyme Yhr202w, as an extra-cellular AMP hydrolase in the NAD degradation pathway. Yhr202w, which we now term Smn1 for Scavenger MonoNucleotidase 1, is a highly conserved protein that is similar to the human protein E5NT/CD73, which is associated with multiple cancers. Hence, our new methodology provides a paradigm, that can be adopted to other organisms, for uncovering new enzymatic functions of uncharacterized proteins.
UR - http://www.scopus.com/inward/record.url?scp=85125519256&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.jmb.2022.167478
DO - https://doi.org/10.1016/j.jmb.2022.167478
M3 - مقالة
C2 - 35123996
SN - 0022-2836
VL - 434
JO - Journal of Molecular Biology
JF - Journal of Molecular Biology
IS - 7
M1 - 167478
ER -