RESULTS: In this study, we established an ensemble computational model for discriminating the near-native docking pose of APKs named "AnkPlex". A dataset of APKs was generated from seven X-ray APKs, which consisted of 3 internal domains, using the reliable docking tool ZDOCK. The dataset was composed of 669 and 44,334 near-native and non-near-native poses, respectively, and it was used to generate eleven informative features. Subsequently, a re-scoring rank was generated by AnkPlex using a combination of a decision tree algorithm and logistic regression. AnkPlex achieved superior efficiency with ≥1 near-native complexes in the 10 top-rankings for nine X-ray complexes compared to ZDOCK, which only obtained six X-ray complexes. In addition, feature analysis demonstrated that the van der Waals feature was the dominant near-native pose out of the potential ankyrin-protein docking poses.
CONCLUSION: The AnkPlex model achieved a success at predicting near-native docking poses and led to the discovery of informative characteristics that could further improve our understanding of the ankyrin-protein complex. Our computational study could be useful for predicting the near-native poses of binding proteins and desired targets, especially for ankyrin-protein complexes. The AnkPlex web server is freely accessible at http://ankplex.ams.cmu.ac.th .
OBJECTIVE: To augment the affinity of AnkGAG1D4 scaffold towards its CA target, through computational predictions and experimental designs.
METHOD: Three dimensional structure of the binary complex formed by AnkGAG1D4 docked to the CA was used as a model for van der Waals (vdW) binding energy calculation. The results generated a simple guideline to select the amino acids for modifications. Following the predictions, modified AnkGAG1D4 proteins were produced and further evaluated for their CA-binding activity, using ELISA-modified method and bio-layer interferometry (BLI).
RESULTS: Tyrosine at position 56 (Y56) in AnkGAG1D4 was experimentally identified as the most critical residue for CA binding. Rational substitutions of this residue diminished the binding affinity. However, vdW calculation preconized to substitute serine for tyrosine at position 45. Remarkably, the affinity for the viral CA was significantly enhanced in AnkGAG1D4-S45Y mutant, with no alteration of the target specificity.
CONCLUSIONS: The S-to-Y mutation at position 45, based on the prediction of interacting amino acids and on vdW binding energy calculation, resulted in a significant enhancement of the affinity of AnkGAG1D4 ankyrin for its CA target. AnkGAG1D4-S45Y mutant represented the starting point for further construction of variants with even higher affinity towards the viral CA, and higher therapeutic potential in the future.