ConSurf Conservation Analysis

Version: 1.0.0

Commit Hash: 5c200df9fdf7d2c4d5722c0cd0b65b4d7b3db52d

Author: Toan Phung

Category: analysis

Subcategory: protein-conservation

Protein sequence conservation analysis using ConSurf standalone. Identifies conserved and variable regions in protein sequences based on homology search and multiple sequence alignment. Based on: Ashkenazy et al. (2016) Nucleic Acids Res 44(W1):W344-W350. Repository: https://github.com/Rostlab/ConSurf

README

ConSurf Conservation Analysis

Installation

⬇️ Click here to install in Cauldron (requires Cauldron to be running)

Repository: https://github.com/noatgnu/consurf-standalone-plugin

Manual installation:

  1. Open Cauldron
  2. Go to Plugins → Install from Repository
  3. Paste: https://github.com/noatgnu/consurf-standalone-plugin
  4. Click Install

ID: consurf-conservation
Version: 1.0.0
Category: analysis
Author: Toan Phung

Description

Protein sequence conservation analysis using ConSurf standalone. Identifies conserved and variable regions in protein sequences based on homology search and multiple sequence alignment. Based on: Ashkenazy et al. (2016) Nucleic Acids Res 44(W1):W344-W350. Repository: https://github.com/Rostlab/ConSurf

Runtime

  • Environments: docker

  • Entrypoint: /opt/miniconda/bin/conda run -n consurf_env --no-capture-output python /workspace/stand_alone_consurf/stand_alone_consurf.py

Inputs

Name Label Type Required Default Visibility
query_sequence Query Protein Sequence file Yes - Always visible
fasta_database Protein FASTA Database file Yes - Always visible
algorithm Homolog Search Algorithm select (HMMER, BLAST) Yes HMMER Always visible
max_homologs Maximum Homologs number (min: 10, max: 500, step: 10) Yes 150 Always visible
substitution_model Substitution Model select (BEST, JTT, LG, WAG, cpREV, mtREV, Dayhoff) Yes BEST Always visible
max_id Maximum Sequence Identity (%) number (min: 50, max: 100, step: 5) Yes 95 Always visible
min_id Minimum Sequence Identity (%) number (min: 1, max: 50, step: 5) Yes 35 Always visible
cutoff E-value Cutoff number (min: 0, max: 1, step: 0) Yes 0.0001 Always visible
max_iterations Maximum Iterations number (min: 1, max: 5, step: 1) Yes 1 Always visible
maximum_likelihood Use Maximum Likelihood boolean No false Always visible
closest Use Closest Homologs Only boolean No false Always visible
msa_file Multiple Sequence Alignment (Optional) file No - Always visible
alignment_program Alignment Program select (MAFFT, MUSCLE, CLUSTALW) No - Always visible
structure_file PDB Structure File (Optional) file No - Always visible
chain PDB Chain ID text No A Always visible
query_name Query Sequence Name text No - Always visible

Input Details

Query Protein Sequence (query_sequence)

Protein sequence in FASTA format for conservation analysis

Protein FASTA Database (fasta_database)

Database of protein sequences for homolog search (e.g., UniRef90, UniProt)

Homolog Search Algorithm (algorithm)

Algorithm for searching homologous sequences

  • Options: HMMER, BLAST

Maximum Homologs (max_homologs)

Maximum number of homologous sequences to include in MSA

Substitution Model (substitution_model)

Amino acid substitution model for conservation calculation

  • Options: BEST, JTT, LG, WAG, cpREV, mtREV, Dayhoff

Maximum Sequence Identity (%) (max_id)

Maximum sequence identity threshold for homolog filtering

Minimum Sequence Identity (%) (min_id)

Minimum sequence identity threshold for homolog filtering

E-value Cutoff (cutoff)

E-value threshold for homolog search significance

Maximum Iterations (max_iterations)

Number of PSI-BLAST iterations (if BLAST selected)

Use Maximum Likelihood (maximum_likelihood)

Use maximum likelihood method for rate calculation (slower but more accurate)

Use Closest Homologs Only (closest)

Select only the closest homologs based on similarity

Multiple Sequence Alignment (Optional) (msa_file)

Pre-computed MSA file. If provided, skips homolog search and alignment steps

Alignment Program (alignment_program)

Program for multiple sequence alignment (used if MSA not provided)

  • Options: MAFFT, MUSCLE, CLUSTALW

PDB Structure File (Optional) (structure_file)

Protein structure file for mapping conservation to 3D structure

PDB Chain ID (chain)

Chain identifier in PDB file (e.g., A, B, C)

  • Placeholder: A

Query Sequence Name (query_name)

Custom name for the query sequence in outputs

  • Placeholder: MyProtein

Outputs

Name File Type Format Description
consurf_outputs Consurf_Outputs.zip data zip Complete ConSurf analysis results archive
conservation_grades *_consurf_grades.txt data txt Per-residue conservation grades and scores
msa_variety msa_aa_variety_percentage.csv data csv Amino acid variation percentage at each position in MSA
query_copy query.fasta data fasta Copy of input query sequence

Requirements

  • Python Version: >=3.8

Example Data

This plugin includes example data for testing:

  max_iterations: 1
  chain: A
  query_name: LRRK2_HUMAN
  algorithm: HMMER
  max_homologs: 50
  substitution_model: BEST
  maximum_likelihood: false
  query_sequence: example/Q5S007.fasta.txt
  fasta_database: example/LRRK2_Mammalia.txt
  structure_file: example/AF-Q5S007-F1-model_v6.pdb
  max_id: 95
  min_id: 35
  cutoff: 0.0001

Load example data by clicking the Load Example button in the UI.

Usage

Via UI

  1. Navigate to analysis → ConSurf Conservation Analysis
  2. Fill in the required inputs
  3. Click Run Analysis

Via Plugin System

const jobId = await pluginService.executePlugin('consurf-conservation', {
  // Add parameters here
});