PASTA 2.0 Predicts Amyloid STructural Aggregation with enhanced functionality and sequence based properties. It predicts the most aggregation-prone portions and the corresponding β-strand inter-molecular pairing for multiple input sequences. In addition, it predicts intrinsic protein disorder and secondary structure efficiently allowing analyses of complementary sequence properties. The PASTA energy threshold was recalibrated on a larger set of peptides and is given as a function of sensitivity and specificity. Finally, an option to perform intra-protein aggregation (i.e. protein-proteinaggregation) is possible.

Please cite

Ian Walsh, Flavio Seno, Silvio C.E. Tosatto and Antonio Trovato.
PASTA2: An improved server for protein aggregation prediction
Nucleic Acids Research, 2014 Jul;42(Web Server issue):W301-7.

Antonio Trovato, Fabrizio Chiti, Amos Maritan and Flavio Seno
Insight into the structure of Amyloid fibrils from the Analysis of Globular Proteins
Plos Computational Biology 12, 1608-1618 (2006), USA


The BACH-server allows to use the BACHSCORE tool with the aim of discriminating the best model of a protein (the native state or a structure very similar to it) among a large set of alternative conformations. The tool uses the BACH++ (Bayesian Analysis Conformation Hunt) knowledge-based potential, an all atom energy score based on 1091 parameters derived by a statistical analysis of a small set of experimentally observed proteins. The original BACH scoring function was introduced in [1], whereas the BACH++ upgraded scoring function used in BACHSCORE is presented in [2]. The BACH-server provides direct access to the BACH++ energy function. Both single models and sets of models (submitted as a single zip file or collectively selected from a dropdown list) can be analyzed. Input model files need to be in pdb (Protein Data Bank) format. An energy score is associated to all models in the set and then used to rank them: conformations with lowest energies are predicted to be more similar to the native state.

Please cite:

[1] P. Cossio, D. Granata, A. Laio, F. Seno and, A. Trovato
"A simple and efficient statistical potential for scoring ensembles of protein structures"
Scientific Reports 2, Art. N. 050901 (2012)

[2] E. Sarti, S. Zamuner, P. Cossio, A. Laio, F. Seno, and A. Trovato
"BACHSCORE. A tool for evaluating efficiently and reliably the quality of large sets of protein structures"
Computer Physics Communications 184, 2860 (2013)