Unable to perform the de novo protein structure prediction.

[sebel76]

Hi developer,

Thanks you for your program. It is quite easy to use and generate valuable results.

I want to get help with the de novo protein structure prediction using PSIPRED. I always got the same error saying that PSIPRED cannot find the output folder for .ss2 and .horiz files.

Why it is happen and how to solve it?

Below, I attached the .config and .fail file if it can help.

I observed two things:

1. It seems that EVcouplings cannot process the coupling step and downstream analyses; correct?
2. When my protein slightly differ from the experimental protein structure, the "compare" step return a protein (.pdb) with missing part.

I have a bulk of other questions:

1. What can I do if there is no experimental structure for my protein (RdDR protein) in PDB?
2. When it work properly, will PSIPRED return a 3D predicted structure file (.pdb)?
3. If not, what output file can I use to compute this and with which software?

Thanks for you help!
Sébastien

#############

dcl5.failed

#############
Traceback (most recent call last):
File "/Users/sbelanger/opt/miniconda3/lib/python3.8/site-packages/evcouplings/utils/pipeline.py", line 508, in execute_wrapped
outcfg = execute(**config)
File "/Users/sbelanger/opt/miniconda3/lib/python3.8/site-packages/evcouplings/utils/pipeline.py", line 187, in execute
outcfg = runner(**incfg)
File "/Users/sbelanger/opt/miniconda3/lib/python3.8/site-packages/evcouplings/fold/protocol.py", line 714, in run
return PROTOCOLSkwargs["protocol"]
File "/Users/sbelanger/opt/miniconda3/lib/python3.8/site-packages/evcouplings/fold/protocol.py", line 357, in standard
residues = secondary_structure(**kwargs)
File "/Users/sbelanger/opt/miniconda3/lib/python3.8/site-packages/evcouplings/fold/protocol.py", line 116, in secondary_structure
ss2_file, horiz_file = run_psipred(
File "/Users/sbelanger/opt/miniconda3/lib/python3.8/site-packages/evcouplings/fold/tools.py", line 232, in run_psipred
verify_resources(
File "/Users/sbelanger/opt/miniconda3/lib/python3.8/site-packages/evcouplings/utils/system.py", line 129, in verify_resources
raise ResourceError(
evcouplings.utils.system.ResourceError: psipred output is invalid:
/Users/sbelanger/Documents/research/orthology/prot.coevolution/dcl5/fold/psipred/dcl5.ss2, /Users/sbelanger/Documents/research/orthology/prot.coevolution/dcl5/fold/psipred/dcl5.horiz

#################

dcl5_config.txt

#################

Sample configuration file for evcouplings monomer protein prediction pipeline.

This file determines all aspects of the computation:

- which compute environment to use

- which stages of the pipeline to run

- what the settings for each of the stages are

Minimal settings required before this configuration can be executed:

- set your environment, paths to tools and databases (at the end of this file)

- under "global", set prefix and sequence_id

- run it! :)

Configuration rules:

1) Global settings override settings for stages

2) Outputs of a stage are merged into "global" and fed into the input of subsequent stages

(e.g., the alignment_file output of align will be used by the alignment_file input of couplings)

3) All settings are explicitly specified here. No hidden defaults in code.

4) Each stage is also passed the parameters in the "databases" and "tools" sections

pipeline: protein_monomer

which stages of workflow to run. Uncomment downstream stages using # (however, no stage can be run before the previous

stage has been run)

stages:

• align
• couplings
• compare
• mutate
• fold

Global job settings (which protein, region). These will override settings of the same name in each of the stages.

These are typically the settings you want to modify for each of your jobs, together with some settings in the align stage.

global:
# mandatory output prefix of the job (e.g. output/HRAS will store outputs in folder "output", using files prefixed with "HRAS")
prefix: /Users/sbelanger/Documents/research/orthology/prot.coevolution/dcl5

# mandatory sequence identifier (mandatory, even if sequence_file is given)

sequence_id: DCL5.aa

# optional FASTA file with target sequence (if blank, will fetch try to fetch sequence_id from databases.sequence_download_url)
# if sequence_file is set, sequence_id must be defined, but can be arbitrary identifier (does not have to match ID in file)

sequence_file: /Users/sbelanger/Documents/research/orthology/prot.coevolution/seq/DCL5.aa.fasta

# cut to subregion of sequence (specify as list, e.g. [24, 286], leave blank for full sequence)

region:

# Clustering threshold for downweighting redudant sequences (Meff computation). E.g. 0.8 will cluster sequences
# at a 80% sequence identity cutoff

theta: 0.8

# number of cores to use. If running through evcouplings application, will be overriden by environment.cores

cpu: 10

Specify multiple batch jobs (if empty, only a single job will be run). Each entry (e.g. b_0.75) will be appended to

global.prefix to uniquely identify the subjob. Parameters for individual stages that should be overridden for each

subjob have to be specified, for all other parameters jobs share the same values.

batch:

_b0.75:

align: {domain_threshold: 0.75, sequence_threshold: 0.75}

_b0.3:

align: {domain_threshold: 0.3, sequence_threshold: 0.3}

Sequence alignment generation/processing.

align:
# standard: iterative sequence search and postprocessing using jackhmmer.
protocol: standard

# The following fields usually do not need to be set, since "global" defines them.
# prefix:
# sequence_id:
# sequence_file:
# region:
# theta:

# index of first residue in sequence_id / sequence_file. This can be used to renumber sequences that already have
# been cut to a subsequence

first_index: 1

# Use bitscore threshold instead of E-value threshold for sequence search

use_bitscores: true

# jackhmmer domain- and sequence-level inclusion thresholds.
# if use_bitscores is True:
# - floating point number will be interpreted as a relative bitscore threshold (bits/residue)
# - integer will be interpreted as an absolute bitscore threshold
# if use_bitscore is False:
# - mantissa-exponent string or float will be interpreted literally
# - integer will be interpreted as negative of the exponent (10 -> 1E-10)

domain_threshold: 0.5
sequence_threshold: 0.5

# number of jackhmmer iterations

iterations: 5

# sequence database (specify possible databases and paths in "databases" section below)

database: uniref100

# compute the redundancy-reduced number of effective sequences (M_eff) already in the alignment stage.
# To save compute time, this computation is normally carried out in the couplings stage

compute_num_effective_seqs: false

# Filter sequence alignment at this % sequence identity cutoff. Can be used to cut computation time in
# the couplings stage (e.g. set to 95 to remove any sequence that is more than 95% identical to a sequence
# already present in the alignment). If blank, no filtering. If filtering, HHfilter must be installed.

seqid_filter:

# Only keep sequences that align to at least x% of the target sequence (i.e. remove fragments)

minimum_sequence_coverage: 50

# Only include alignment columns with at least x% residues (rather than gaps) during model inference

minimum_column_coverage: 70

# Create a file with extracted annotation from UniRef/UniProt sequence FASTA headers

extract_annotation: true
cpu:

# set to True to turn of jackhmmer bias correction

nobias: false

# if align stage has been run previously, reuse the generated raw sequence alignment coming out of jackhmmer

reuse_alignment: true

# create checkpoint files of HMM and aligment after each iteration

checkpoints_hmm: false
checkpoints_ali: false

Alternative protocol: reuse existing alignment and apply postprocessing to generate alignment that is consistent

with pipeline requirements. Uncomment, and comment all values in align section above to enable the "existing" protocol

protocol: existing

prefix:

# Path of input alignment. Alignment needs to contain region in form SEQID/start-end, or first_index must be set

input_alignment:

sequence_id:

first_index:

compute_num_effective_seqs: False

theta:

seqid_filter:

minimum_sequence_coverage: 50

minimum_column_coverage: 70

extract_annotation: True

Inference of evolutionary couplings from sequence alignment

couplings:
# current options:
# - standard (model inference using plmc)
# - mean_field (mean field direct coupling analysis, see below)
protocol: standard

# number of plmc iterations

iterations: 100

# specify custom alphabet as a string. Gap symbol must be first character

alphabet:

# Treat gaps as missing data during model inference

ignore_gaps: true

# strength of regularization on coupling parameters J

lambda_J: 0.01

# adjust for larger number of coupling parameters relative to number of fields h (multiply by model length and
# number of states)

lambda_J_times_Lq: true

# strength of regularization on fields h

lambda_h: 0.01
lambda_group:
scale_clusters:
# reuse ECs and model parameters, if this stage has been run before
reuse_ecs: true

# Sequence separation filter for generation of CouplingScores_longrange.csv table (i.e. to take out short-range
# ECs from table, only pairs with abs(i-j)>=min_sequence_distance will be kept.

min_sequence_distance: 6

# Post-inference scoring of ECs to derive probabilities
# Options are: skewnormal, normal, logistic_regression

scoring_model: logistic_regression

Alternative protocol: compute couplings with mean field direct coupling analysis

Uncomment, and comment all values in align section above to enable the mean_field protocol

# protocol: mean_field

# Options: cn, di, mi_apc, mi
# ec_score_type: cn

# Post-inference scoring of ECs to derive probabilities - only available if used_score == "cn"!
# Options are: skewnormal, normal, logistic_regression
# scoring_model: logistic_regression

# pseudo_count: 0.5
# alphabet:
# ignore_gaps: False
# reuse_ecs: True
# min_sequence_distance: 6

# Following input parameters will usually be overriden by "global" and outputs of "align" stage
# prefix:
# alignment_file:
# focus_sequence:
# focus_mode: True
# segments:
# cpu:
# theta:

Compare ECs to known 3D structures

compare:
# Current options: standard
protocol: standard

# Following parameters will be usually overriden by global settings / output of previous stage

prefix:
sequence_id:
ec_file:
target_sequence_file:

# If True, find structures by sequence alignment against the PDB, otherwise identify structures using
# sequence_id and SIFTS database (sequence_id must be UniProt AC/ID in this case)

by_alignment: true

# Leave this parameter empty to use all PDB structures for given sequence_id, otherwise
# will be limited to the given IDs (single value or list). Important: note that this acts only as a filter on the
# structures found by alignment or in the SIFTS table (!)

pdb_ids:

# Limit number of structures and chains for comparison

max_num_structures: 10
max_num_hits: 25

# compare to multimer contacts (if multiple chains of the same sequence or its homologs are present in a structure)

compare_multimer: true

# settings for sequence alignment against PDB sequences using jackhmmer
# (additional settings like iterations possible, compare to align stage)

sequence_file:
first_index:
region:
alignment_min_overlap: 20
use_bitscores: true
domain_threshold: 0.1
sequence_threshold: 0.1

# Comparison and plotting settings
# Filter that defines which atoms will be used for distance calculations. If empty/None, no filter will be
# applied (resulting in the computation of minimum atom distances between all pairs of atoms). If setting to any
# particular PDB atom type, only these atoms will be used for the computation (e.g. CA will give C_alpha distances,
# CB will give C_beta distances, etc.)

atom_filter:

# Distance cutoff (Angstrom) for a true positive pair

distance_cutoff: 5

# Only long-range pairs with abs(i-j)>= min_sequence_distance will be used for CouplingScoresCompared_longrange.csv file

min_sequence_distance: 6

# Plot contact maps with ECs above these mixture model probability cutoffs

plot_probability_cutoffs: [0.90, 0.99]

# Plot fixed numbers of ECS. Integers will be interpreted as absolute numbers, floats as fractions of L (model length)

plot_lowest_count: 0.05
plot_highest_count: 1.0
plot_increase: 0.05

# Axis boundaries of contact map plot depending on range of ECs and structure.
# Options: union, intersection, ecs, structure, [start, end] (e.g. [100, 200])

boundaries: union

# scale sizes of EC dots in scatter plot based on strength of EC score

scale_sizes: true

# draw secondary structure on contact map plots

draw_secondary_structure: true

# draw structure and alignment/EC coverage information on contact map plots

draw_coverage: true

# print information about used PDB structures on contact map plots

print_pdb_information: true

# Alignment method to use to search the PDB Seqres database. Options: jackhmmer, hmmsearch
# Set to jackhmmer to search the PDB Seqres database using jackhmmer from the target sequence only (more stringent). 
# Set to hmmsearch to search the PDB seqres database using an HMM built from the output monomer alignment (less stringent). 
# Warning: searching by HMM may result in crystal structures from very distant homologs or even unrelated sequences. 

pdb_alignment_method: jackhmmer

Settings for Mutation effect predictions

mutate:
# Options: standard
protocol: standard

# predict the following dataset file (.csv file, mutants like A102V or A102V,K199W in column "mutant")

mutation_dataset_file:

# Inputs set by global stage and output of previous stages
# prefix:
# model_file:

Settings for 3D structure prediction

fold:
# Options: standard
protocol: standard

# Options: cns_dgsa

engine: cns_dgsa

# Config file. If blank, default configuration (restraints.yml) in package will be used

folding_config_file:

# If True, limit 3D modeling only to that region of sequence that actually has sequence alignment coverage)

cut_to_alignment_region: true

# Method for secondary structure prediction (options: psipred, requires PSIPRED installation). Will be used
# to generate distance and dihedral angle restraints for local geometry.

sec_struct_method: psipred

# If secondary structure was already predicted in previous execution of configuration, reuse the file

reuse_sec_struct: true

# Instead of predicting secondary structure in pipeline, can specify a secondary structure file:
# Must be csv file with columns i (position), A_i (residue) and sec_struct_3state (secondary structure, H, E or C
# for helix, sheet or coil)

sec_struct_file:

# Do not use EC pairs as distance restraints that are geometrically incompatible with predicted secondary structure

filter_sec_struct_clashes: true

# Only use ECs with sequence distance abs(i-j) >= min_sequence_distance for folding

min_sequence_distance: 6

# Predict structures using all ECs above these probability cutoffs according to mixture model

fold_probability_cutoffs: [0.90, 0.99]

# Predict structures with selected number of ECs.
# Integers will be interpreted as absolute number of ECs, floats as a fraction of L (model length)

fold_lowest_count: 0.5
fold_highest_count: 1.3
fold_increase: 0.05

# number of trial structure to generate for each EC set

num_models: 10

# remove intermediate files created during folding and keep only final models

cleanup: true

# Inputs defined by "global" or previous stages
# prefix:
# ec_file:
# target_sequence_file:
# segments:
# remapped_pdb_files:
# cpu:

These settings allow job status tracking using a database, and result collection in an archive

management:
# URI of database
database_uri:

# unique job identifier

job_name:

# add the following output files to results archive

archive: [target_sequence_file, statistics_file, alignment_file, frequencies_file,
ec_file, ec_longrange_file, model_file, enrichment_file, evzoom_file, enrichment_pml_files,
ec_lines_pml_file, contact_map_files, ec_compared_all_file, ec_compared_longrange_file,
remapped_pdb_files, mutations_epistatic_pml_files, mutation_matrix_file, mutation_matrix_plot_files,
secondary_structure_pml_file, folding_ec_file, folded_structure_files, folding_ranking_file,
folding_comparison_file, folding_individual_comparison_files, ec_lines_compared_pml_file,
pdb_structure_hits_file, sec_struct_file]

# Delete the following output files after running the job if you don't need them, to save disk space.
# Note that this may jeopardize your ability to rerun parts of the job if intermediate files are missing.
# The following, deactivated default deletes the biggest output files.
# delete: [raw_alignment_file, model_file]

Computational environment for batch jobs (using evcouplings command line application)

environment:
# current options for engine: lsf, local, slurm (for local, only set cores and leave all other fields blank)
# If your batch engine of choice (e.g. SGE, Torque) is not available yet, please consider contributing by
# implementing it and submitting a pull request!
# Note that "cores" will override the "cpu" parameter for "global"
engine: local
queue:
cores: 10
memory:
time:

# Special setting for "local" engine to define number of workers running in parallel
# (note that "cores" has to be defined above to make sure each job only uses a defined
# number of cores). If not defined or None, will default to number of cores / cores per job;
# otherwise specify integer to limit number of workers (1 for serial execution of subjobs)
# parallel_workers: 1

# command that will be executed before running actual computation (can be used to set up environment)

configuration:

Paths to databases used by evcouplings.

databases:
# Sequence databases (only download the ones you want to use). You can also specify arbitrary databases in FASTA format
# using a database name of your choice here)
uniprot: /Users/sbelanger/Documents/research/data/reference/protein/uniprot/uniprot/uniprot_current.fasta
uniref100: /Users/sbelanger/Documents/research/data/reference/protein/uniprot/uniref100/uniref100_current.fasta
uniref90: /Users/sbelanger/Documents/research/data/reference/protein/uniprot/uniref90/uniref90_current.fasta

# URL do download sequences if sequence_file is not given. {} will be replaced by sequence_id.

sequence_download_url: http://www.uniprot.org/uniprot/{}.fasta

# Directory with PDB MMTF structures (leave blank to fetch structures from web)

pdb_mmtf_dir:

# SIFTS mapping information. Point to file paths in an existing directory, and if these files do not exist, they will be
# automatically generated and saved at the given file path (this may take a while).
# Periodically delete these files to more recent versions of SIFTS are used.

sifts_mapping_table: /Users/sbelanger/Documents/research/data/reference/protein/sifts/pdb_chain_uniprot_plus_current.csv
sifts_sequence_db: /Users/sbelanger/Documents/research/data/reference/protein/sifts/pdb_chain_uniprot_plus_current.fasta

Paths to external tools used by evcouplings. Please refer to README.md for installation instructions and which tools are required.

tools:
jackhmmer: /Users/sbelanger/opt/miniconda3/bin/jackhmmer
hmmbuild: /Users/sbelanger/opt/miniconda3/bin/hmmbuild
hmmsearch: /Users/sbelanger/opt/miniconda3/bin/hmmsearch
plmc: /usr/local/bin/plmc
hhfilter: /Users/sbelanger/opt/miniconda3/bin/hhfilter
psipred: /Users/sbelanger/Documents/software/psipred/runpsipred
cns: /Users/sbelanger/Documents/software/cns_solve_1.21/intel-x86_64bit-linux/bin/cns
maxcluster: /Users/sbelanger/Documents/software/maxcluster64bit

[thomashopf]

Hi @sebel76,

This looks like a problem with your PSIPRED installation (used for secondary structure prediction before the actual folding). I suggest to set up PSIPRED first and make sure it runs, before using it in EVcouplings.

Are those two files made, and if so, do they have any content?

/Users/sbelanger/Documents/research/orthology/prot.coevolution/dcl5/fold/psipred/dcl5.ss2, /Users/sbelanger/Documents/research/orthology/prot.coevolution/dcl5/fold/psipred/dcl5.horiz

[sebel76]

Hi,

I install PSIPRED following instructions from the developer. I compiled the program. I use the program runpsipredplus (because of my blast+). Using EVcoupling, I observed that I add to put the blast index directly to the working directory or it return a message error.

Then, I run it with EVcoupling and got the message that I sent you.
I re-run the example coming with PSIPRED. The program run. Everything looks okay with the BLAST part, but it does not return the two files (.ss2 and .horiz).

I got the following error in the terminal:
Running PSI-BLAST with sequence example/example.fasta ...
Predicting secondary structure...
../bin/chkparse: Command not found.
FATAL: Error whilst running chkparse - script terminated!

This is weird since the ../bin/chkparse program is present and run well...

Any idea to solve my issue?

Best,
Sébastien