Scoring function for automated assessment of protein structure template quality

TLDR

The authors introduce the TM‑score, a new protein template quality metric that extends GDT and MaxSub while removing size dependence to better evaluate template and model accuracy. They compute TM‑score by scaling distances with protein size and assessing all residue pairs, and benchmark it on 1,489 templates generated by PROSPECTOR_3 with models built by MODELLER and TASSER. TM‑score shows a stronger correlation with final model quality than GDT/MaxSub, aligns closely with expert visual assessment in CASP5, and serves as a valuable complement to automated prediction evaluation. The TM‑score program is freely available at http://bioinformatics.buffalo.edu/TM-score.

Abstract

We have developed a new scoring function, the template modeling score (TM-score), to assess the quality of protein structure templates and predicted full-length models by extending the approaches used in Global Distance Test (GDT)1 and MaxSub.2 First, a protein size-dependent scale is exploited to eliminate the inherent protein size dependence of the previous scores and appropriately account for random protein structure pairs. Second, rather than setting specific distance cutoffs and calculating only the fractions with errors below the cutoff, all residue pairs in alignment/modeling are evaluated in the proposed score. For comparison of various scoring functions, we have constructed a large-scale benchmark set of structure templates for 1489 small to medium size proteins using the threading program PROSPECTOR_3 and built the full-length models using MODELLER and TASSER. The TM-score of the initial threading alignments, compared to the GDT and MaxSub scoring functions, shows a much stronger correlation to the quality of the final full-length models. The TM-score is further exploited as an assessment of all 'new fold' targets in the recent CASP5 experiment and shows a close coincidence with the results of human-expert visual assessment. These data suggest that the TM-score is a useful complement to the fully automated assessment of protein structure predictions. The executable program of TM-score is freely downloadable at http://bioinformatics.buffalo.edu/TM-score.