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MultiFOLD, ModFOLDdock and MultiFOLD_refine: prediction, quality assessment and refinement of protein tertiary and quaternary structure models

\n\nA docker container for the MultiFOLD, ModFOLDdock and MultiFOLD_refine methods developed by the McGuffin group for CASP15.\n\n

Please cite the relevant papers:

\nMultiFOLD reference:\nMcGuffin, L. J., Edmunds N. S., Genc, A. G., Alharbi, S. M. A., Salehe, B. R. and Adiyaman, R. (2023) Prediction of protein structures, functions and interactions using the IntFOLD7, MultiFOLD and ModFOLDdock servers. Nucleic Acids Research. gkad297. DOI PubMed\n\nModFOLDdock reference:\nEdmunds, 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\n\nMultiFOLD_refine reference:\nAdiyaman, 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 \n\n

Requirements

\n\nThe latest version of Docker and the NVIDIA Container Toolkit.\n\nNOTE: 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.\n\n

Setup

\nOptionally set the input and output paths in your shell (alternatively just include the full paths when you run):\n\nexport MF_IN=/location/for/your/input/fasta_files/\n\nexport MF_OUT=/location/for/your/output/files/\n\n(Note: The commands below can be also be run without sudo by following the Docker Engine post-installation steps.)\n\n

Run standard MultiFOLD for 3D modelling of multimers from sequences in FASTA format

\n\nsudo docker run --gpus all -v $MF_IN:/MultiFOLD_input -v $MF_OUT:/MultiFOLD_output mcguffin/multifold /MultiFOLD/run_MultiFOLD_docker.sh targetname fastafile stoichiometry\n\ne.g. Run MultiFOLD for CASP15 target \"T1124\" with the FASTA file \"T1124.fasta\" and stoichiometry \"A2\" as follows:\n\nsudo 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\n\nNote: 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.,\n\nsudo 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\n\nMultiFOLD output:\nThe output for each job will be found in $MF_OUT within a unique subdirectory named according to the time and date of submission plus the extension \"\\_TS\". Your final results file will be in CASP TS format and can be found within the \"MultiFOLD_TS_\" subdirectory with a filename containing the unique sequence ID for your job and ending with the extension \"_TS.txt\" e.g.\n\n$MF_OUT/10_52_22_729_17-1-2023_TS/MultiFOLD_TS_4blo8v5uerbok3qm/4blo8v5uerbok3qm_TS.txt\n\nAll 3D models in PDB format can be found within the MultiFOLD_models/ subdirectory e.g.\n\n$MF_OUT/10_52_22_729_17-1-2023_TS/MultiFOLD_TS_4blo8v5uerbok3qm/MultiFOLD_models/\n\n

Run MultiFOLD_refine for refining 3D models of complexes with known stoichiometry

\n\nsudo 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\n\ne.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:\n\nsudo 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\n\nMultiFOLD_refine output:\nThe output for each job will be found in $MF_OUT within a unique subdirectory named according to the time and date of submission plus the extension \"\\_REF\". Your final results file will be in CASP TS format and can be found within the \"MultiFOLD_TS_\" subdirectory with a filename containing the unique sequence ID for your job and ending with the extension \"_TS.txt\" e.g.\n\n$MF_OUT/12_45_32_944_19-1-2023_REF/MultiFOLD_TS_mlnme2t4e9p9imog/mlnme2t4e9p9imog_TS.txt\n\nAll 3D models in PDB format can be found within the MultiFOLD_models/ subdirectory e.g.\n\n$MF_OUT/10_52_22_729_17-1-2023_TS/12_45_32_944_19-1-2023_REF/MultiFOLD_TS_mlnme2t4e9p9imog/MultiFOLD_models/\n\n

Run ModFOLDdock for estimating the quality of 3D models of complexes

\n\nsudo 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\n\nFor estimating the quality of a single model:\n\ne.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:\n\nsudo 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 \n\nFor estimating the quality of multiple models:\n\ne.g. Run ModFOLDdock for CASP15 target \"T1124\" with the FASTA file \"T1124.fasta\" on multiple models \"T1124o.tar.gz\" with stoichiometry \"A2\" as follows:\n\nsudo 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\n\nModFOLDdock output:\nThe output for each job will be found in $MF_OUT within a unique subdirectory named according to the time and date of submission plus the extension \"\\_QA\". Your final results file will be in CASP15 QA format and can be found within this subdirectory with a filename containing the unique sequence ID for your job and ending with the extensions: \"_QA.txt\" for standard ModFOLDdock jobs, \"_R_QA.txt\" for ModFOLDdockR jobs, or \"_S_QA.txt\" for ModFOLDdockS jobs e.g.\n\n$MF_OUT/16_58_50_246_19-1-2023_QA/mlnme2t4e9p9imog_QA.txt,\n\n$MF_OUT/16_58_50_246_19-1-2023_QA/mlnme2t4e9p9imog_R_QA.txt,\n\nor\n\n$MF_OUT/10_47_48_35_19-1-2023_QA/mlnme2t4e9p9imog_S_QA.txt\n\n

Contact

\nProf. Liam J. McGuffin","has_starred","hub_user","immutable_tags_settings",{"_78":11,"_79":80},"enabled","rules",[81],".*","is_automated","permissions",{"_85":17,"_86":11,"_87":11},"read","write","admin","user","storage_size",62869763340,"orgData","recentTags",[94],{"_95":48,"_96":97,"_98":99,"_100":101,"_102":103,"_104":105,"_54":121,"_122":97,"_123":29,"_124":60,"_39":125,"_126":127,"_128":112,"_129":121,"_130":69,"_131":17},"content_type","creator",1506247,"digest","sha256:65b0e11e69826049a6662cbe10890acf2d0eb6fa44bd810de72dd8eb8d7733b8","full_size",58931958934,"id",277130377,"images",[106],{"_107":108,"_98":99,"_109":110,"_111":112,"_113":114,"_115":116,"_117":110,"_118":-5,"_119":101,"_66":69,"_120":-5},"architecture","amd64","features","","last_pulled","2026-09-23T00:10:18.111058558Z","last_pushed","2023-11-17T14:14:47Z","os","linux","os_features","os_version","size","variant","2023-11-17T14:14:46.483067Z","last_updater","last_updater_username","media_type","latest","repository",17892379,"tag_last_pulled","tag_last_pushed","tag_status","v2","sbxKitMetadata","isPotentialSpam","isHubSbxKitsEnabled","showSbxLogoOverride","sbxTrademarkText","displaySecurityMetadata","tagAttestations","tagsHaveAttestations",[],"routes/_layout.r.$namespace.$reponame.tags",{"_34":143,"_152":153,"_139":162,"_163":11},{"_36":144,"_46":147,"_49":50,"_51":52,"_53":11,"_54":55,"_56":57,"_58":148,"_39":31,"_28":29,"_61":62,"_63":48,"_64":65,"_66":67,"_68":69,"_70":-5,"_71":65,"_72":73,"_74":11,"_75":29,"_76":149,"_82":11,"_83":151,"_88":29,"_89":90},[145,146],{"_39":40,"_41":42},{"_39":44,"_41":45},[48],[60],{"_78":11,"_79":150},[81],{"_85":17,"_86":11,"_87":11},"tags",{"_154":67,"_155":-5,"_156":-5,"_157":158},"count","next","previous","results",[159],{"_95":48,"_96":97,"_98":99,"_100":101,"_102":103,"_104":160,"_54":121,"_122":97,"_123":29,"_124":60,"_39":125,"_126":127,"_128":112,"_129":121,"_130":69,"_131":17},[161],{"_107":108,"_98":99,"_109":110,"_111":112,"_113":114,"_115":116,"_117":110,"_118":-5,"_119":101,"_66":69,"_120":-5},[],"canDeleteTags","actionData","errors"]

mcguffin/multifold

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