Intrinsically disordered proteins (IDPs) challenge the traditional view of protein structure, lacking a stable tertiary structure yet playing pivotal roles in various biological processes. To address the growing need for a comprehensive resource, we developed IDEAL (https://ideal-db.org/), a curated database of IDPs. IDEAL leverages semantic web technologies like RDF and SPARQL to enhance accessibility and interoperability. Here, we introduce the design of the newly constructed RDF dataset that represents the biological processes associated with IDPs.
Intrinsically disordered proteins (IDPs) form a dynamic protein class lacking a fixed
threedimensional structure in the isolated state, allowing diverse conformations upon
interacting with other molecules. Vital in cellular processes like signaling and regulation, IDEAL
(http://www.ideal-db.org/) is a significant repository for experimentally verified IDPs and
intrinsically disordered regions (IDRs) [
In order to depict processes associated with IDPs, we have introduced two primary classes: ”State” and ”BiologicalProcess.” The ”State” class encompasses components such as proteins, SWAT4HCLS 2024 nucleic acids, etc., including their complexes. In the case of a component being a complex, the subunits are categorized by the ”Subcomponent” class. The ”BiologicalProcess” class is linked to ”ProcessType,” with instances including ”catalyze,” ”associate,” ”dissociate,” ”translocate,” among others. Furthermore, the ”BiologicalProcess” class is associated with the ”Object” class, which identifies the facilitator of the given biological process.
Figure 1 illustrates two instances of these processes. The left panel demonstrates a process where a complex is formed from the IDP APP and APBB1. APP and APBB1 are classified by the ”Component” class in the first ”State,” connected to a ”BiologicalProcess” with ”ProcessType” as ”associate.” This ”BiologicalProcess” is linked to the second ”State,” which contains a complex of APP and APBB1 as its components. Similarly, the catalyze process of phosphorylation facilitated by MAPK10 can be represented using the ”State” and ”BiologicalProcess” classes.
In addition to relying on the notes of ProcessType in XML and RDF, we can verify it by examining the relationship between the two connected ”States” and the corresponding ”BiologicalProcess.” For instance, if the first ”State” comprises two protein components, and the second ”State” includes a complex, the inferred ”ProcessType” would be ”association.” In cases where the ifrst ”State” involves a protein and the second ”State” involves a phosphorylated protein, the determined ”ProcessType” would be ”catalyze.” We have designed such rules for verifying the ”ProcessType” based on the characteristics of the associated ”States.”
This work was supported by JSPS KAKENHI grant number 21K12148 and 20H05932..