A regression framework incorporating quantitative and negative interaction data improves quantitative prediction of
Xiaojian Shao1, Chris S H Tan, Courtney Voss
1Department of Applied Mathematics, College of Science, China Agricultural University, Beijing, 100083, China.
Bioinformatics (Oxford, England)
|December 4, 2010
Summary
We developed a novel framework to predict protein interactions involving PDZ domains and their peptide ligands. Incorporating negative interaction data improves prediction accuracy, highlighting the importance of sequence similarity.
Area of Science:
- Molecular Biology
- Bioinformatics
- Systems Biology
Background:
- Protein interactions mediated by peptide recognition domains are crucial for biological processes.
- Understanding binding strength is key for building accurate protein interaction networks.
- PDZ domains are a large family of peptide recognition domains involved in numerous cellular functions.
Purpose of the Study:
- To develop a novel regression framework for quantitatively predicting interactions between PDZ domains and peptide ligands.
- To leverage both quantitative and qualitative (negative) interaction data for improved prediction accuracy.
- To infer relative binding strengths for previously unseen PDZ domains and peptides based on primary sequence.
Main Methods:
- Developed a novel regression framework utilizing primary sequence information.
- Incorporated both positive (quantitative) and negative (qualitative) interaction data for mouse PDZ domains.
- Employed cross-validated hold-out testing and testing with novel PDZ domain-peptide interactions.
Main Results:
- Demonstrated the ability to infer relative binding strengths for unseen PDZ domains and peptides using existing data.
- Showed that incorporating negative interaction data significantly improves quantitative prediction performance.
- Identified sequence similarity as a critical determinant of prediction accuracy.
Conclusions:
- The developed framework accurately predicts PDZ domain-peptide interactions using primary sequence data.
- Negative interaction data enhances the predictive power of quantitative models.
- Future experimental efforts should focus on underrepresented PDZ domain subfamilies to further improve prediction accuracy.
Related Concept Videos
02:04Protein-protein Interfaces
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
01:30Quantitative Aspects of Drug-Receptor Interaction
The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower Kd...
02:26Protein Networks
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...