An automated decision‐tree approach to predicting protein interaction hot spots
- 6 June 2007
- Vol. 68 (4), 813-823
- https://doi.org/10.1002/prot.21474
Abstract
Protein–protein interactions can be altered by mutating one or more “hot spots,” the subset of residues that account for most of the interface's binding free energy. The identification of hot spots requires a significant experimental effort, highlighting the practical value of hot spot predictions. We present two knowledge‐based models that improve the ability to predict hot spots: K‐FADE uses shape specificity features calculated by the Fast Atomic Density Evaluation (FADE) program, and K‐CON uses biochemical contact features. The combined K‐FADE/CON (KFC) model displays better overall predictive accuracy than computational alanine scanning (Robetta–Ala). In addition, because these methods predict different subsets of known hot spots, a large and significant increase in accuracy is achieved by combining KFC and Robetta–Ala. The KFC analysis is applied to the calmodulin (CaM)/smooth muscle myosin light chain kinase (smMLCK) interface, and to the bone morphogenetic protein‐2 (BMP‐2)/BMP receptor‐type I (BMPR‐IA) interface. The results indicate a strong correlation between KFC hot spot predictions and mutations that significantly reduce the binding affinity of the interface. Proteins 2007.Keywords
This publication has 30 references indexed in Scilit:
- Protein–Protein Interactions: Hot Spots and Structurally Conserved Residues often Locate in Complemented Pockets that Pre-organized in the Unbound States: Implications for DockingJournal of Molecular Biology, 2004
- Predicting Changes in the Stability of Proteins and Protein Complexes: A Study of More Than 1000 MutationsJournal of Molecular Biology, 2002
- Electrostatic aspects of protein–protein interactionsCurrent Opinion in Structural Biology, 2000
- The Protein Data BankNucleic Acids Research, 2000
- Anatomy of hot spots in protein interfacesJournal of Molecular Biology, 1998
- Functional Consequences of Truncating Amino Acid Side Chains Located at a Calmodulin-Peptide InterfaceOnline Journal of Public Health Informatics, 1997
- Characterizing the microenvironment surrounding protein sitesProtein Science, 1995
- Knowledge-based artificial neural networksArtificial Intelligence, 1994
- Aromatic-Aromatic Interaction: A Mechanism of Protein Structure StabilizationScience, 1985
- The Predictive Sample Reuse Method with ApplicationsJournal of the American Statistical Association, 1975