Dual artificial intelligence methods-based analysis of the impact of domain oscillations on functions of ficin protein

Abstract

Thermal oscillations observed in proteins are acknowledged as essential to managing the biological capabilities of this complex molecule. However, their behavior and characteristics are yet to be clarified. In this research, affinities of tetrapeptides in active areas of ficin, where domain oscillations were observed, were analyzed using dual artificial intelligence methods and computer simulations. The results show that the oscillations were able to handle temporal alteration of their affinities in its active areas. Moreover, it was inferred that the improvement in the flexibility of the β strand between the domains would enhance the oscillations and reduce the optimal temperature. Finally, the decision tree presented important attributes that would play key roles in molecular design.