Probabilistic divergence of a template-based modelling methodology from the ideal protocol

Protein structural information is essential for the detailed mapping of a functional protein network. For higher modelling accuracy and quicker implementation, template-based algorithms have been extensively deployed redefined. The methods only assess predicted structure against its native state/template do not estimate each step. A divergence measure therefore postulated to theoretical optimal benchmark. By freezing domain boundaries, measures are most crucial steps algorithm. To precisely refine score using weighting constants, big data analysis could further be deployed.