ExoPred is a web-based tool that implements a Random Forest algorithm trained in a dataset that containing 2992 vertebrata exosome proteins collected from EXOCARTA and UNIPROT. Those ones including N-terminal signal peptide and/or transmembrane regions were discarted. Likewise, we reduce sequence similarity so that exosome proteins do not share more than 80% identity. This dataset also contains 2961vertebrata non-exosome proteins randomly collected from UNIPROT and obeyed to the same criteria than exosome proteins.
The ExoPred interface has been designed for simple and intuitive use.ExoPred first runs a BLASTP  against the UNIPROT database and process the BLAST output to identify the UNIPROT identifier (ID) of protein hits with identity higher than 90% and over 90% of their entire length. After these identifiers, ExoPred will then retrieve taxa and sub-cellular location information from UNIPROT annotations and transfer it to the relevant input query proteins. ExoPred will also detect those proteins with leader sequence and transmembrane regions using SignalP  and TMHMM  and predict sub-cellular locations using PSORT  . The model for predicting exosome secretion is only executed on proteins from vertebrate and without a signal peptide or transmembrane regions.
The input data for ExoPred can be one or several protein sequences in FASTA format, as it is show in the example, which can be pasted or uploaded to the server. All the input sequences have to be in UPPER LETTER and in one-letter amino acid code. To run the server, click the "RUN" button.
>7B2_PIG Neuroendocrine protein 7B2 OS=Sus scrofa OX=9823 GN=SCG5 PE=1 SV=2
In ExoPred, users can also select:
Here follows a representative output with all the information the user can obtain.
ExoPred output consists of a table reporting by default whether input proteins are from vertebrate (Y/N), contain a signal peptide (Y/N) or transmembrane regions (Y/N) and can be secreted via exosomes (Y/N). As show in previously, ExoPred will also show the sub-cellular location of input proteins annotated in UNIPROT and predicted by PSORT if the relevant options were checked at submission. Exosome secretion predictions will show as NA (not available) for input proteins that do not meet the criteria mentioned above. For proteins without UNIPROT equivalents, ExoPred will still determine whether they can be secreted by exosomes as long as they have no predicted signal peptide or transmembrane regions. In these cases, the field taxa, and UNIPROT sub-cellular-location when selected, will show as not found.
1) Henrik Nielsen. Predicting Secretory Proteins with SignalP. 2017.In Kihara, D (ed). Protein Function Prediction (Methods in Molecular Biology vol. 1611) pp. 59-73, Springer.
2) A. Krogh, B. Larsson, G. von Heijne, and E. L. L. Sonnhammer. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. Journal of Molecular Biology, 305(3):567-580, January 2001.
3) Horton, P., Park, K. J., Obayashi, T., Fujita, N., Harada, H., Adams-Collier, C. J., & Nakai, K. (2007). WoLF PSORT: protein localization predictor. Nucleic acids research, 35(Web Server issue), W585–W587.
4) Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990). Basic local alignment search tool. Journal of molecular biology, 215(3), 403–410.
For questions about this site: