PAPA - a program for predicting prion-forming proteins

PAPA predicts the prion-forming propensity of a protein using a sliding-window approach. Using a set of known prion-forming and non-prion-forming domains the prion propensity of each amino acid was established. Each position in a protein is characterized by the average prion propensity in a length fourty-one window around it. Prediction scores are computed by averaging the scores of fourty-one consecutive windows, and the maximum across the protein is its prion-forming propensity. Segments with a score above 0.05 have a high probability of forming prion-like aggregates. The default setting only scores segments that are predicted to be disordered according to FoldIndex; if no such segment is found, PAPA provides a prion propensity score of -1. This disorder requirement can be turned off. Please note that PAPA has only been validated for Q/N-rich sequences.

Download

The papa program is a command-line Python script available here. To test the program you can download a few of the sequences mentioned in the paper.

Usage

Typical papa usage:

python papa.py -o results_file fasta_file

where:

fasta_file:: path to a fasta-format file containing the protein sequences
results_file:: path to a file containing the output The output is a comma delimited file whose columns are: sequence id, maximum score, position. Maximum score is the largest window score, and position is the position where it occurs.

For full usage type: python papa.py -h. Note that windows users may need to provide the full

License

GPLv3

All programs in this collection are free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.

Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No. 1023771. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation (NSF).