Prediction, Quality Assessment and Refinement of Protein Tertiary and Quaternary Structure Models
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A docker container for the MultiFOLD, ModFOLDdock and MultiFOLD_refine methods developed by the McGuffin group for CASP15.
ModFOLDdock reference: Edmunds, N. S., Alharbi, S. M. A., Genc, A. G., Adiyaman, R. and McGuffin, L. J. (2023) Estimation of Model Accuracy in CASP15 Using the ModFOLDdock Server. Proteins, Epub ahead of print. DOI PubMed
MultiFOLD_refine reference: Adiyaman, R., Edmunds, N. S., Genc, A. G., Alharbi, S. M. A. and McGuffin, L. J. (2023) Improvement of protein tertiary and quaternary structure predictions using the ReFOLD refinement method and the AlphaFold2 recycling process. Bioinformatics Advances, vbad078. DOI
The latest version of Docker and the NVIDIA Container Toolkit.
NOTE: This version has been tested to work on Ubuntu 20.04 with NVIDIA T4, A10 and A100 GPUs (Turing and Ampere micro-architecture). Later builds will include support for newer GPUs.
export MF_IN=/location/for/your/input/fasta_files/
export MF_OUT=/location/for/your/output/files/
(Note: The commands below can be also be run without sudo by following the Docker Engine post-installation steps.)
sudo docker run --gpus all -v $MF_IN:/MultiFOLD_input -v $MF_OUT:/MultiFOLD_output mcguffin/multifold /MultiFOLD/run_MultiFOLD_docker.sh targetname fastafile stoichiometry
e.g. Run MultiFOLD for CASP15 target "T1124" with the FASTA file "T1124.fasta" and stoichiometry "A2" as follows:
sudo docker run --gpus all -v $MF_IN:/MultiFOLD_input -v $MF_OUT:/MultiFOLD_output mcguffin/multifold /MultiFOLD/run_MultiFOLD_docker.sh T1124 T1124.fasta A2
Note: regarding the stochiometry parameter, a monomer=A1, a homodimer=A2, a homotrimer=A3, etc. A heterodimer=A1B1, a heterotrimer=A1B1C1, etc. You can also model targets with more complex stoichiometries, such as a dimer of dimers=A2B2, a trimer and dimer=A3B2, a nonamer and trimer=A9B3, and so on. You must provide a sequence in the FASTA file for each subunit in your complex. If the stoichiometry is not known, then you can use the parameter "unknown" and it will be predicted from templates, e.g.,
sudo docker run --gpus all -v $MF_IN:/MultiFOLD_input -v $MF_OUT:/MultiFOLD_output mcguffin/multifold /MultiFOLD/run_MultiFOLD_docker.sh T1124 T1124.fasta unknown
MultiFOLD output: The output for each job will be found in $MF_OUT within a unique subdirectory named according to the time and date of submission plus the extension "_TS". Your final results file will be in CASP TS format and can be found within the "MultiFOLD_TS_" subdirectory with a filename containing the unique sequence ID for your job and ending with the extension "_TS.txt" e.g.
$MF_OUT/10_52_22_729_17-1-2023_TS/MultiFOLD_TS_4blo8v5uerbok3qm/4blo8v5uerbok3qm_TS.txt
All 3D models in PDB format can be found within the MultiFOLD_models/ subdirectory e.g.
$MF_OUT/10_52_22_729_17-1-2023_TS/MultiFOLD_TS_4blo8v5uerbok3qm/MultiFOLD_models/
sudo docker run --gpus all -v $MF_IN:/MultiFOLD_input -v $MF_OUT:/MultiFOLD_output mcguffin/multifold /MultiFOLD/run_MultiFOLD_refine_docker.sh targetname fastafile modelfile stoichiometry recycles
e.g. Run MultiFOLD_refine for CASP15 target "T1124" with the FASTA file "T1124.fasta" on the model "T1124TS180_1o.pdb" with stoichiometry "A2" for "12" recycles as follows:
sudo docker run --gpus all -v $MF_IN:/MultiFOLD_input -v $MF_OUT:/MultiFOLD_output mcguffin/multifold /MultiFOLD/run_MultiFOLD_refine_docker.sh T1124 T1124.fasta T1124TS180_1o.pdb A2 12
MultiFOLD_refine output: The output for each job will be found in $MF_OUT within a unique subdirectory named according to the time and date of submission plus the extension "_REF". Your final results file will be in CASP TS format and can be found within the "MultiFOLD_TS_" subdirectory with a filename containing the unique sequence ID for your job and ending with the extension "_TS.txt" e.g.
$MF_OUT/12_45_32_944_19-1-2023_REF/MultiFOLD_TS_mlnme2t4e9p9imog/mlnme2t4e9p9imog_TS.txt
All 3D models in PDB format can be found within the MultiFOLD_models/ subdirectory e.g.
$MF_OUT/10_52_22_729_17-1-2023_TS/12_45_32_944_19-1-2023_REF/MultiFOLD_TS_mlnme2t4e9p9imog/MultiFOLD_models/
sudo docker run --gpus all -v $MF_IN:/MultiFOLD_input -v $MF_OUT:/MultiFOLD_output mcguffin/multifold /MultiFOLD/run_ModFOLDdock_docker.sh targetname fastafile modelfile stoichiometry
For estimating the quality of a single model:
e.g. Run ModFOLDdock for CASP15 target "T1124" with the FASTA file "T1124.fasta" on the single model "T1124TS180_1o.pdb" with stoichiometry "A2" as follows:
sudo docker run --gpus all -v $MF_IN:/MultiFOLD_input -v $MF_OUT:/MultiFOLD_output mcguffin/multifold /MultiFOLD/run_ModFOLDdock_docker.sh T1124 T1124.fasta T1124TS180_1o.pdb A2
For estimating the quality of multiple models:
e.g. Run ModFOLDdock for CASP15 target "T1124" with the FASTA file "T1124.fasta" on multiple models "T1124o.tar.gz" with stoichiometry "A2" as follows:
sudo docker run --gpus all -v $MF_IN:/MultiFOLD_input -v $MF_OUT:/MultiFOLD_output mcguffin/multifold /MultiFOLD/run_ModFOLDdock_docker.sh T1124 T1124.fasta T1124o.tar.gz A2
ModFOLDdock output: The output for each job will be found in $MF_OUT within a unique subdirectory named according to the time and date of submission plus the extension "_QA". Your final results file will be in CASP15 QA format and can be found within this subdirectory with a filename containing the unique sequence ID for your job and ending with the extensions: "_QA.txt" for standard ModFOLDdock jobs, "_R_QA.txt" for ModFOLDdockR jobs, or "_S_QA.txt" for ModFOLDdockS jobs e.g.
$MF_OUT/16_58_50_246_19-1-2023_QA/mlnme2t4e9p9imog_QA.txt,
$MF_OUT/16_58_50_246_19-1-2023_QA/mlnme2t4e9p9imog_R_QA.txt,
or
$MF_OUT/10_47_48_35_19-1-2023_QA/mlnme2t4e9p9imog_S_QA.txt
Content type
Image
Digest
sha256:65b0e11e6…
Size
54.9 GB
Last updated
almost 3 years ago
docker pull mcguffin/multifold