Current protein forcefields like the ones seen in CHARMM or Xplor-NIH have many terms that include bonded and non-bonded terms. Yet the forcefields do not take into account the use of hydrogen bonds which are important for secondary structure creation and stabilization of proteins. SCOPE is an open-source program that generates proteins from rotamer space. It then creates a forcefield that uses only non-bonded and hydrogen bond energy terms to create a profile for a given protein. The profiles can then be used in an artificial neural network to create a linear model which is funneled to the true protein conformation.

Computational approaches to modeling protein structures have made significant advances over the past decade. However, the current limitation in modeling protein structures is to produce protein structures consistently below the limit of 6Å compared to their native structure. Therefore improvement of protein structures consistently below the 6Å limit using simulation of biophysical forces is of significant interest. Current protein force fields such as those implemented in CHARMM, AMBER, and NAMD have been deemed complete, yet their use in ab initio approaches to protein structure determination has been unsuccessful. Here we introduce a new approach in evaluation of protein structures based on analysis of energy profiles produced by the SCOPE software package. The latest version of SCOPE produces a hydrogen bond profile that is substantially more informative than a single hydrogen bond energy value. We demonstrate how analysis of SCOPE’s energy profile by an Artificial Neural Network (ANN) shows a significant improvement compared to the traditional force-based approaches to evaluation of structures. The ANN based analysis of SCOPE’s energy profile showed identification of structures to within 1.5-3.0Å of the native structure. These results have been obtained by testing structures in the same Homology, Topology, Architecture, or Class of the CATH family.