Quality assessment

ProQ is a neural network based predictor that based on a number of structural features predicts the quality of a protein model. ProQ is optimized to find correct models in contrast to other methods which are optimized to find native structures. Two quality measures are predicited LGscore and MaxSub.

LGscore is -log of a P-value and MaxSub ranges from 0-1, were 0 is insignificant and 1 very significant.

Different ranges of quality:

Correct
LGscore > 1.5
MaxSub > 0.1

Good
LGscore > 3
MaxSub > 0.5

Very good
LGscore > 5
MaxSub > 0.8

Pcons is a Model Quality Assessment Program (MQAP) this means that it ranks protein models by assessing their quality. Pcons uses a sets of possible protein models as input. These models can and should be produced using various methods and approaches. The Pcons protocol analyzes the set of protein models and looks for recurring three-dimensional structural patterns. Based on this analysis each model is assigned a score reflecting how common its three-dimmensional structural patterns are in the whole ensemble of possible models.