Abstract
Many biological processes are mediated by protein-protein interactions (PPIs). Because protein domains are the building blocks of proteins, PPIs likely rely on domain-domain interactions (DDIs). Several attempts exist to infer DDIs from PPI networks but the produced datasets are heterogeneous and sometimes not accessible, while the PPI interactome data keeps growing.We describe a new computational approach called “PPIDM” (Protein-Protein Interactions Domain Miner) for inferring DDIs using multiple sources of PPIs. The approach is an extension of our previously described “CODAC” (Computational Discovery of Direct Associations using Common neighbors) method for inferring new edges in a tripartite graph. The PPIDM method has been applied to seven widely used PPI resources, using as “Gold-Standard” a set of DDIs extracted from 3D structural databases. Overall, PPIDM has produced a dataset of 84,552 non-redundant DDIs. Statistical significance (p-value) is calculated for each source of PPI and used to classify the PPIDM DDIs in Gold (9,175 DDIs), Silver (24,934 DDIs) and Bronze (50,443 DDIs) categories. Dataset comparison reveals that PPIDM has inferred from the 2017 releases of PPI sources about 46% of the DDIs present in the 2020 release of the 3did database, not counting the DDIs present in the Gold-Standard. The PPIDM dataset contains 10,229 DDIs that are consistent with more than 13,300 PPIs extracted from the IMEx database, and nearly 23,300 DDIs (27.5%) that are consistent with more than 214,000 human PPIs extracted from the STRING database. Examples of newly inferred DDIs covering more than 10 PPIs in the IMEx database are provided.Further exploitation of the PPIDM DDI reservoir includes the inventory of possible partners of a protein of interest and characterization of protein interactions at the domain level in combination with other methods. The result is publicly available at http://ppidm.loria.fr/.
Highlights
Many biological processes from metabolic pathways to cellular signaling are mediated by protein-protein interactions (PPIs)
We study the coverage of PPIs from curated (IMEx) or non curated (STRING) databases by PPIDM domain-domain interactions (DDIs) and we compare with DOMINE to the advantage of PPIDM
The June2017, January2018, January2019 and April2020 releases of 3did were used after subtracting the Gold-Standard data set (7,254 DDIs), in order to check how many inferred DDIs correspond to DDIs in 3did that were not used as Gold-Standard during PPIDM generation, and how many inferred DDIs correspond to DDIs that were not known from 3did at the time PPDIM was generated
Summary
Many biological processes from metabolic pathways to cellular signaling are mediated by protein-protein interactions (PPIs). The experimental determination and analysis of such interactions are often difficult and time-consuming. The developments in high-throughput gene sequencing techniques have created a huge gap between the ever increasing number of known protein sequences and the knowledge of their function and of their biological interactions. There is much interest in developing computational approaches to predict PPIs. Because protein domains are the building blocks of proteins, PPIs mainly rely on given combinations of domain-domain interactions (DDIs). Predicting and modelling PPIs should benefit from a systematic inventory of all possible DDIs
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