The significance of the protdeform score for structure prediction and alignment

Abstract

Background: When a researcher uses a program to align two proteins and gets a score, one of her main concerns is how often the program gives a similar score to pairs that are or are not in the same fold. This issue was analysed in detail recently for the program TM-align with its associated TM-score. It was shown that because the TM-score is length independent, it allows a P-value and a hit probability to be defined depending only on the score. Also, it was found that the TM-scores of gapless alignments closely follow an Extreme Value Distribution (EVD). The program ProtDeform for structural protein alignment was developed recently and is characterised by the ability to propose different transformations of different protein regions. Our goal is to analyse its associated score to allow a researcher to have objective reasons to prefer one aligner over another, and carry out a better interpretation of the output. Results: The study on the ProtDeform score reveals that it is length independent in a wider score range than TM-scores and that PD-scores of gapless (random) alignments also approximately follow an EVD. On the CASP8 predictions, PD-scores and TM-scores, with respect to native structures, are highly correlated (0.95), and show that around a fifth of the predictions have a quality as low as 99.5% of the random scores. Using the Gold Standard benchmark, ProtDeform has lower probabilities of error than TM-align both at a similar speed. The analysis is extended to homology discrimination showing that, again, ProtDeform offers higher hit probabilities than TM-align. Finally, we suggest using three different P-values according to the three different contexts: Gapless alignments, optimised alignments for fold discrimination and that for superfamily discrimination. In conclusion, PD-scores are at the very least as valuable for prediction scoring as TM-scores, and on the protein classification problem, even more reliable. © 2011 Rocha, Alberich.