Protein structure validation using a semi-empirical method

Current practice of validating predicted protein structural model is knowledge-based where scoring parameters are derived from already known structures to obtain decision on validation out of this structure information. For example, the scoring parameter, Ramachandran Score gives percentage conformity with steric-property higher value of which implies higher acceptability. On the other hand, Force-Field Energy Score gives conformity with energy-wise stability higher value of which implies lower acceptability. Naturally, setting these two scoring parameters as target objectives sometimes yields a set of multiple models for the same protein for which acceptance based on a particular parameter, say, Ramachandran score, may not satisfy well with the acceptance of the same model based on other parameter, say, energy score. The confusion set of such models can further be resolved by introducing some parameters value of which are easily obtainable through experiment on the same protein. In this piece of work it was found that the confusion regarding final acceptance of a model out of multiple models of the same protein can be removed using a parameter Surface Rough Index which can be obtained through semi-empirical method from the ordinary microscopic image of heat denatured protein.