Tango

TANGO is a statistical mechanics computer algorithm developed for the prediction of aggregation nucleating regions in proteins, as well as of the effect of mutations and environmental conditions on the aggregation propensity of these regions.

TANGO is based on the physico-chemical principles of b-sheet formation extended by the assumption that the core regions of an aggregate are fully buried. TANGO was benchmarked against 175 peptides of over 20 proteins and was able to predict the sequences experimentally observed to contribute to the aggregation of these proteins. TANGO also correctly predicts the aggregation propensities of several disease-related mutations in the Alzheimer´s b-peptide, human lysozyme and transthyrethin, and discriminates between b-sheet tendency and aggregation.

The success of TANGO confirms the model of intermolecular b-sheet formation as a wide-spread underlying mechanism of protein aggregation and opens the possibility of screening large databases for potential disease-related aggregation motifs, as well as optimizing recombinant protein yields by rationally out-designing protein aggregation.

TANGO was originally developed by Luis Serrano and his team at the European Molecular Biology Laboratory in Heidelberg, Germany.