AMYLPRED2¶
Description¶
This module provides a function to predict the aggregation propensity of proteins, specifically the number of aggregation-prone segments on an unfolded protein sequence. AMYLPRED2 is a consensus method of different methods. In order to obtain the best balance between sensitivity and specificity, we follow the author’s guidelines to consider every 5 consecutive residues agreed among at least 5 methods contributing 1 to the aggregation propensity.
Instructions¶
- Create an account on the webserver at the AMYLPRED2 registration link.
- Create a new AMYLPRED object with your email and password initialized along with it.
- Run
ssbio.protein.sequence.properties.aggregation_propensity.AMYLPRED.get_aggregation_propensity()
on a protein sequence.
FAQs¶
What is aggregation propensity?
- The number of aggregation-prone segments on an unfolded protein sequence.
How can I install AMYLPRED2?
- AMYLPRED2 is only available as a web server. ssbio provides a wrapper for the web server and allows you to submit protein sequences to it along with caching the output files.
How do I cite AMYLPRED2?
- Tsolis AC, Papandreou NC, Iconomidou VA & Hamodrakas SJ (2013) A consensus method for the prediction of ‘aggregation-prone’ peptides in globular proteins. PLoS One 8: e54175 Available at: http://dx.doi.org/10.1371/journal.pone.0054175
How can this parameter be used on a genome-scale?
- See: Chen K, Gao Y, Mih N, O’Brien EJ, Yang L & Palsson BO (2017) Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation. Proceedings of the National Academy of Sciences 114: 11548–11553 Available at: http://www.pnas.org/content/114/43/11548.abstract
I’m having issues running AMYLPRED2…
- See the ssbio wiki for (hopefully) some solutions - or add yours in when you find the answer!
API¶
-
class
ssbio.protein.sequence.properties.aggregation_propensity.
AMYLPRED
(email, password)[source]¶ Class to submit sequences to AMYLPRED2.
Instructions:
- Create an account on the webserver at the AMYLPRED2 registration link.
- Create a new AMYLPRED object with your email and password initialized along with it.
- Run
get_aggregation_propensity
on a protein sequence.
-
email
¶ str – Account email
-
password
¶ str – Account password
Todo
- Properly implement force_rerun and caching functions
-
get_aggregation_propensity
(seq, outdir, cutoff_v=5, cutoff_n=5, run_amylmuts=False)[source]¶ Run the AMYLPRED2 web server for a protein sequence and get the consensus result for aggregation propensity.
Parameters: - seq (str, Seq, SeqRecord) – Amino acid sequence
- outdir (str) – Directory to where output files should be saved
- cutoff_v (int) – The minimal number of methods that agree on a residue being a aggregation-prone residue
- cutoff_n (int) – The minimal number of consecutive residues to be considered as a ‘stretch’ of aggregation-prone region
- run_amylmuts (bool) – If AMYLMUTS method should be run, default False. AMYLMUTS is optional as it is the most time consuming and generates a slightly different result every submission.
Returns: Aggregation propensity - the number of aggregation-prone segments on an unfolded protein sequence
Return type: int
-
run_amylpred2
(seq, outdir, run_amylmuts=False)[source]¶ Run all methods on the AMYLPRED2 web server for an amino acid sequence and gather results.
Result files are cached in
/path/to/outdir/AMYLPRED2_results
.Parameters: - seq (str) – Amino acid sequence as a string
- outdir (str) – Directory to where output files should be saved
- run_amylmuts (bool) – If AMYLMUTS method should be run, default False
Returns: Result for each method run
Return type: dict