An Improved Protein Decoy Set for Testing Energy Functions for Protein Structure Prediction

ABSTRACT We have improved the original Ro-setta centroid/backbone decoy set by increasing the number of proteins and frequency of near native models and by building on sidechains and minimiz-ing clashes. The new set consists of 1,400 model structures for 78 different and diverse protein tar-gets and provides a challenging set for the testing and evaluation of scoring functions. We evaluated the extent to which a variety of all-atom energy functions could identify the native and close-to-native structures in the new decoy sets. Of various implicit solvent models, we found that a solvent-accessible surface area–based solvation provided the best enrichment and discrimination of close-to-native decoys. The combination of this solvation treatment with Lennard Jones terms and the origi-nal Rosetta energy provided better enrichment and discrimination than any of the individual terms. The results also highlight the differences in accu-racy of NMR and X-ray crystal structures: a large energy gap was observed between native and non-native conformations for X-ray structures but not for NMR structures. Proteins 2003;53:76–87