Structure, Biochemistry, Proteins, JMB, Protein Sci., Nat. Struct. Bio.
Abstract
-> predicting effects of mutations in protein complexes is important.
-> B:B* well characterized e.g....
-> COMBINE predictive models.
-> compare to other methods.
-> model delta_G, delta_H and delta_S.
-> insights into important energetic factors.
Introduction
-> background
-> protein-protein binding energy evaluation methods and uses.
-> COMBINE method.
-> B:B* case.
-> literature search: 1-3 literature summary of all theorectical studies of B:B* system.
Methods
1. Modelling of mutant complexes.
-> protein sequence
-> protonation state
-> hydration
-> different comformations for some mutants.
-> Energy minimization
-> validation: x-ray structures of mutants.
2. COMBIEN analysis
-> matrix preparation. (BUW/no scaling)
-> PLS+FFD
-> validation: external test set.
-> delta_G, delta_H and delta_S (20 complexes)
Results
Table 1: similar to Table 1 of OppA paper
Table 2: performance of models
Figure 1: B:B* wildtype complex, showing location of mutations.
Figure 2: PCA?
Figure 3: predicted vs experimental: delta_G, delta_H and delta_S, outliers?
Figure 4: PLS coefficients showing important variables
Figure 5: ? specific aspects?
Discussion
-> Hotspots: How do these amino acids contribute in COMBINE?
-> how optimal is binding of B:B*? suggestions for improving binding?
-> contribution of electrostatics to binding affinity? (compare to literature)
-> compare to other theoretical methods
-> contributions of interfacial water molecules
-> extension of other protein complexes PrivacyImprint