dSPRINT: predicting DNA, RNA, ion, peptide and small molecule interaction sites within protein domains.

TitledSPRINT: predicting DNA, RNA, ion, peptide and small molecule interaction sites within protein domains.
Publication TypeJournal Article
Year of Publication2021
AuthorsEtzion-Fuchs, A, Todd, DA, Singh, M
JournalNucleic Acids Res
Volume49
Issue13
Paginatione78
Date Published2021 07 21
ISSN1362-4962
KeywordsBinding Sites, DNA, Humans, Ions, Ligands, Machine Learning, Peptides, Protein Domains, RNA
Abstract

<p>Domains are instrumental in facilitating protein interactions with DNA, RNA, small molecules, ions and peptides. Identifying ligand-binding domains within sequences is a critical step in protein function annotation, and the ligand-binding properties of proteins are frequently analyzed based upon whether they contain one of these domains. To date, however, knowledge of whether and how protein domains interact with ligands has been limited to domains that have been observed in co-crystal structures; this leaves approximately two-thirds of human protein domain families uncharacterized with respect to whether and how they bind DNA, RNA, small molecules, ions and peptides. To fill this gap, we introduce dSPRINT, a novel ensemble machine learning method for predicting whether a domain binds DNA, RNA, small molecules, ions or peptides, along with the positions within it that participate in these types of interactions. In stringent cross-validation testing, we demonstrate that dSPRINT has an excellent performance in uncovering ligand-binding positions and domains. We also apply dSPRINT to newly characterize the molecular functions of domains of unknown function. dSPRINT's predictions can be transferred from domains to sequences, enabling predictions about the ligand-binding properties of 95% of human genes. The dSPRINT framework and its predictions for 6503 human protein domains are freely available at http://protdomain.princeton.edu/dsprint.</p>

DOI10.1093/nar/gkab356
Alternate JournalNucleic Acids Res
PubMed ID33999210
PubMed Central IDPMC8287948
Grant ListR01 GM076275 / GM / NIGMS NIH HHS / United States
T32 HG003284 / HG / NHGRI NIH HHS / United States