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

  1. Create an account on the webserver at the AMYLPRED2 registration link.
  2. Create a new AMYLPRED object with your email and password initialized along with it.
  3. 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:

  1. Create an account on the webserver at the AMYLPRED2 registration link.
  2. Create a new AMYLPRED object with your email and password initialized along with it.
  3. 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

parse_method_results(results_file, met)[source]

Parse the output of a AMYLPRED2 result file.

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