OBJECTIVE: The objective of this study was to investigate the effects of four different polyols, namely, ethylene glycol, erythritol, xylitol and sorbitol on the acid-denatured states of CGB lectin.
METHODS: CGB lectin was subjected to acid denaturation at pH 2.5 and pH 1.5, both in the absence and presence of 30% (w/v) polyols, i.e. ethylene glycol, erythritol, xylitol and sorbitol. Thermal denaturation of the acid-denatured states was also studied in the absence and presence of these polyols. Different spectroscopic probes such as tryptophan fluorescence, ANS fluorescence and far-UV CD spectral signal were used to monitor structural changes in the acid-denatured states of CGB lectin in the presence of polyols.
RESULTS: Presence of erythritol, xylitol and sorbitol in the incubation mixture was found to stabilize the lectin at both pH 2.5 and pH 1.5, as evident from the burial of the hydrophobic clusters and decreased polarity around Trp residues. These polyols also stabilized the acid-denatured states of CGB lectin against thermal denaturation by shifting the thermal transition curves towards higher temperatures. Exposure of the acid-denatured states of CGB lectin, obtained at pH 2.5 and pH 1.5 to 61°C and 51°C, respectively, induced formation of non-native β-structures, compared to that present at 25°C, and this phenomenon was significantly suppressed in the presence of these polyols. Based on the spectral data, both sorbitol and erythritol appeared to exude better stabilizing effect. On the other hand, ethylene glycol was shown to destabilize the aciddenatured states of CGB lectin.
CONCLUSION: Thermal stabilization of the lectin was noticed in the presence of erythritol, xylitol and sorbitol at both pH 2.5 and pH 1.5. These polyols also stabilize the secondary and tertiary structures of the acid-denatured CGB lectin at 25°C. Ethylene glycol was proved to be a destabilizer of the acid-denatured CGB lectin.
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 .