Abstract

Neural network predictors of protein disorder using primary sequence information were developed and applied to the Swiss Protein Database. More than 15,000 proteins were predicted to contain disordered regions of at least 40 consecutive amino acids, with more than 1,000 having especially high scores indicating disorder. These results support proposals that consideration of structure-activity relationships in proteins need to be broadened to include unfolded or disordered protein.