Mercurial > repos > galaxy-australia > alphafold2
annotate docker/alphafold/README.md @ 1:6c92e000d684 draft
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
author | galaxy-australia |
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date | Tue, 01 Mar 2022 02:53:05 +0000 |
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1 ![header](imgs/header.jpg) |
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2 |
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3 # AlphaFold |
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4 |
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5 This package provides an implementation of the inference pipeline of AlphaFold |
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6 v2.0. This is a completely new model that was entered in CASP14 and published in |
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7 Nature. For simplicity, we refer to this model as AlphaFold throughout the rest |
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8 of this document. |
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9 |
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10 We also provide an implementation of AlphaFold-Multimer. This represents a work |
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11 in progress and AlphaFold-Multimer isn't expected to be as stable as our monomer |
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12 AlphaFold system. |
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13 [Read the guide](#updating-existing-alphafold-installation-to-include-alphafold-multimers) |
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14 for how to upgrade and update code. |
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15 |
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16 Any publication that discloses findings arising from using this source code or the model parameters should [cite](#citing-this-work) the |
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17 [AlphaFold paper](https://doi.org/10.1038/s41586-021-03819-2) and, if |
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18 applicable, the [AlphaFold-Multimer paper](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v1). |
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19 |
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20 Please also refer to the |
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21 [Supplementary Information](https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-021-03819-2/MediaObjects/41586_2021_3819_MOESM1_ESM.pdf) |
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22 for a detailed description of the method. |
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23 |
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24 **You can use a slightly simplified version of AlphaFold with |
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25 [this Colab |
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26 notebook](https://colab.research.google.com/github/deepmind/alphafold/blob/main/notebooks/AlphaFold.ipynb)** |
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27 or community-supported versions (see below). |
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28 |
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29 ![CASP14 predictions](imgs/casp14_predictions.gif) |
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30 |
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31 ## First time setup |
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32 |
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33 The following steps are required in order to run AlphaFold: |
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34 |
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35 1. Install [Docker](https://www.docker.com/). |
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36 * Install |
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37 [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) |
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38 for GPU support. |
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39 * Setup running |
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40 [Docker as a non-root user](https://docs.docker.com/engine/install/linux-postinstall/#manage-docker-as-a-non-root-user). |
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41 1. Download genetic databases (see below). |
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42 1. Download model parameters (see below). |
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43 1. Check that AlphaFold will be able to use a GPU by running: |
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44 |
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45 ```bash |
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46 docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi |
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47 ``` |
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48 |
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49 The output of this command should show a list of your GPUs. If it doesn't, |
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50 check if you followed all steps correctly when setting up the |
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51 [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html) |
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52 or take a look at the following |
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53 [NVIDIA Docker issue](https://github.com/NVIDIA/nvidia-docker/issues/1447#issuecomment-801479573). |
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54 |
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55 If you wish to run AlphaFold using Singularity (a common containerization platform on HPC systems) we recommend using some of the |
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56 third party Singularity setups as linked in |
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57 https://github.com/deepmind/alphafold/issues/10 or |
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58 https://github.com/deepmind/alphafold/issues/24. |
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59 |
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60 ### Genetic databases |
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61 |
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62 This step requires `aria2c` to be installed on your machine. |
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63 |
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64 AlphaFold needs multiple genetic (sequence) databases to run: |
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65 |
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66 * [BFD](https://bfd.mmseqs.com/), |
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67 * [MGnify](https://www.ebi.ac.uk/metagenomics/), |
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68 * [PDB70](http://wwwuser.gwdg.de/~compbiol/data/hhsuite/databases/hhsuite_dbs/), |
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69 * [PDB](https://www.rcsb.org/) (structures in the mmCIF format), |
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70 * [PDB seqres](https://www.rcsb.org/) – only for AlphaFold-Multimer, |
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71 * [Uniclust30](https://uniclust.mmseqs.com/), |
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72 * [UniProt](https://www.uniprot.org/uniprot/) – only for AlphaFold-Multimer, |
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73 * [UniRef90](https://www.uniprot.org/help/uniref). |
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74 |
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75 We provide a script `scripts/download_all_data.sh` that can be used to download |
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76 and set up all of these databases: |
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77 |
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78 * Default: |
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79 |
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80 ```bash |
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81 scripts/download_all_data.sh <DOWNLOAD_DIR> |
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82 ``` |
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83 |
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84 will download the full databases. |
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85 |
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86 * With `reduced_dbs`: |
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87 |
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88 ```bash |
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89 scripts/download_all_data.sh <DOWNLOAD_DIR> reduced_dbs |
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90 ``` |
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91 |
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92 will download a reduced version of the databases to be used with the |
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93 `reduced_dbs` database preset. |
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94 |
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95 :ledger: **Note: The download directory `<DOWNLOAD_DIR>` should _not_ be a |
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96 subdirectory in the AlphaFold repository directory.** If it is, the Docker build |
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97 will be slow as the large databases will be copied during the image creation. |
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98 |
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99 We don't provide exactly the database versions used in CASP14 – see the [note on |
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100 reproducibility](#note-on-reproducibility). Some of the databases are mirrored |
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101 for speed, see [mirrored databases](#mirrored-databases). |
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102 |
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103 :ledger: **Note: The total download size for the full databases is around 415 GB |
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104 and the total size when unzipped is 2.2 TB. Please make sure you have a large |
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105 enough hard drive space, bandwidth and time to download. We recommend using an |
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106 SSD for better genetic search performance.** |
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107 |
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108 The `download_all_data.sh` script will also download the model parameter files. |
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109 Once the script has finished, you should have the following directory structure: |
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110 |
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111 ``` |
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112 $DOWNLOAD_DIR/ # Total: ~ 2.2 TB (download: 438 GB) |
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113 bfd/ # ~ 1.7 TB (download: 271.6 GB) |
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114 # 6 files. |
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115 mgnify/ # ~ 64 GB (download: 32.9 GB) |
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116 mgy_clusters_2018_12.fa |
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117 params/ # ~ 3.5 GB (download: 3.5 GB) |
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118 # 5 CASP14 models, |
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119 # 5 pTM models, |
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120 # 5 AlphaFold-Multimer models, |
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121 # LICENSE, |
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122 # = 16 files. |
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123 pdb70/ # ~ 56 GB (download: 19.5 GB) |
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124 # 9 files. |
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125 pdb_mmcif/ # ~ 206 GB (download: 46 GB) |
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126 mmcif_files/ |
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127 # About 180,000 .cif files. |
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128 obsolete.dat |
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129 pdb_seqres/ # ~ 0.2 GB (download: 0.2 GB) |
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130 pdb_seqres.txt |
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131 small_bfd/ # ~ 17 GB (download: 9.6 GB) |
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132 bfd-first_non_consensus_sequences.fasta |
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133 uniclust30/ # ~ 86 GB (download: 24.9 GB) |
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134 uniclust30_2018_08/ |
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135 # 13 files. |
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136 uniprot/ # ~ 98.3 GB (download: 49 GB) |
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137 uniprot.fasta |
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138 uniref90/ # ~ 58 GB (download: 29.7 GB) |
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139 uniref90.fasta |
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140 ``` |
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141 |
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142 `bfd/` is only downloaded if you download the full databases, and `small_bfd/` |
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143 is only downloaded if you download the reduced databases. |
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144 |
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145 ### Model parameters |
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146 |
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147 While the AlphaFold code is licensed under the Apache 2.0 License, the AlphaFold |
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148 parameters are made available for non-commercial use only under the terms of the |
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149 CC BY-NC 4.0 license. Please see the [Disclaimer](#license-and-disclaimer) below |
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150 for more detail. |
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151 |
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152 The AlphaFold parameters are available from |
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153 https://storage.googleapis.com/alphafold/alphafold_params_2021-10-27.tar, and |
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154 are downloaded as part of the `scripts/download_all_data.sh` script. This script |
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155 will download parameters for: |
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156 |
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157 * 5 models which were used during CASP14, and were extensively validated for |
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158 structure prediction quality (see Jumper et al. 2021, Suppl. Methods 1.12 |
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159 for details). |
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160 * 5 pTM models, which were fine-tuned to produce pTM (predicted TM-score) and |
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161 (PAE) predicted aligned error values alongside their structure predictions |
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162 (see Jumper et al. 2021, Suppl. Methods 1.9.7 for details). |
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163 * 5 AlphaFold-Multimer models that produce pTM and PAE values alongside their |
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164 structure predictions. |
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165 |
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166 ### Updating existing AlphaFold installation to include AlphaFold-Multimers |
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167 |
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168 If you have AlphaFold v2.0.0 or v2.0.1 you can either reinstall AlphaFold fully |
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169 from scratch (remove everything and run the setup from scratch) or you can do an |
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170 incremental update that will be significantly faster but will require a bit more |
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171 work. Make sure you follow these steps in the exact order they are listed below: |
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172 |
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173 1. **Update the code.** |
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174 * Go to the directory with the cloned AlphaFold repository and run |
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175 `git fetch origin main` to get all code updates. |
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176 1. **Download the UniProt and PDB seqres databases.** |
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177 * Run `scripts/download_uniprot.sh <DOWNLOAD_DIR>`. |
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178 * Remove `<DOWNLOAD_DIR>/pdb_mmcif`. It is needed to have PDB SeqRes and |
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179 PDB from exactly the same date. Failure to do this step will result in |
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180 potential errors when searching for templates when running |
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181 AlphaFold-Multimer. |
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182 * Run `scripts/download_pdb_mmcif.sh <DOWNLOAD_DIR>`. |
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183 * Run `scripts/download_pdb_seqres.sh <DOWNLOAD_DIR>`. |
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184 1. **Update the model parameters.** |
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185 * Remove the old model parameters in `<DOWNLOAD_DIR>/params`. |
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186 * Download new model parameters using |
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187 `scripts/download_alphafold_params.sh <DOWNLOAD_DIR>`. |
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188 1. **Follow [Running AlphaFold](#running-alphafold).** |
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189 |
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190 #### API changes between v2.0.0 and v2.1.0 |
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191 |
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192 We tried to keep the API as much backwards compatible as possible, but we had to |
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193 change the following: |
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194 |
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195 * The `RunModel.predict()` now needs a `random_seed` argument as MSA sampling |
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196 happens inside the Multimer model. |
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197 * The `preset` flag in `run_alphafold.py` and `run_docker.py` was split into |
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198 `db_preset` and `model_preset`. |
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199 * The models to use are not specified using `model_names` but rather using the |
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200 `model_preset` flag. If you want to customize which models are used for each |
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201 preset, you will have to modify the the `MODEL_PRESETS` dictionary in |
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202 `alphafold/model/config.py`. |
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203 * Setting the `data_dir` flag is now needed when using `run_docker.py`. |
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204 |
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205 |
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206 ## Running AlphaFold |
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207 |
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208 **The simplest way to run AlphaFold is using the provided Docker script.** This |
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209 was tested on Google Cloud with a machine using the `nvidia-gpu-cloud-image` |
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210 with 12 vCPUs, 85 GB of RAM, a 100 GB boot disk, the databases on an additional |
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211 3 TB disk, and an A100 GPU. |
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212 |
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213 1. Clone this repository and `cd` into it. |
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214 |
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215 ```bash |
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216 git clone https://github.com/deepmind/alphafold.git |
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217 ``` |
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218 |
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219 1. Build the Docker image: |
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220 |
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221 ```bash |
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222 docker build -f docker/Dockerfile -t alphafold . |
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223 ``` |
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224 |
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225 1. Install the `run_docker.py` dependencies. Note: You may optionally wish to |
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226 create a |
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227 [Python Virtual Environment](https://docs.python.org/3/tutorial/venv.html) |
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228 to prevent conflicts with your system's Python environment. |
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229 |
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230 ```bash |
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231 pip3 install -r docker/requirements.txt |
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232 ``` |
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233 |
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234 1. Run `run_docker.py` pointing to a FASTA file containing the protein |
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235 sequence(s) for which you wish to predict the structure. If you are |
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236 predicting the structure of a protein that is already in PDB and you wish to |
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237 avoid using it as a template, then `max_template_date` must be set to be |
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238 before the release date of the structure. You must also provide the path to |
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239 the directory containing the downloaded databases. For example, for the |
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240 T1050 CASP14 target: |
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241 |
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242 ```bash |
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243 python3 docker/run_docker.py \ |
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244 --fasta_paths=T1050.fasta \ |
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245 --max_template_date=2020-05-14 \ |
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246 --data_dir=$DOWNLOAD_DIR |
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247 ``` |
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248 |
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249 By default, Alphafold will attempt to use all visible GPU devices. To use a |
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250 subset, specify a comma-separated list of GPU UUID(s) or index(es) using the |
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251 `--gpu_devices` flag. See |
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252 [GPU enumeration](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/user-guide.html#gpu-enumeration) |
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253 for more details. |
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254 |
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255 1. You can control which AlphaFold model to run by adding the |
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256 `--model_preset=` flag. We provide the following models: |
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257 |
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258 * **monomer**: This is the original model used at CASP14 with no ensembling. |
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259 |
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260 * **monomer\_casp14**: This is the original model used at CASP14 with |
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261 `num_ensemble=8`, matching our CASP14 configuration. This is largely |
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262 provided for reproducibility as it is 8x more computationally |
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263 expensive for limited accuracy gain (+0.1 average GDT gain on CASP14 |
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264 domains). |
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265 |
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266 * **monomer\_ptm**: This is the original CASP14 model fine tuned with the |
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267 pTM head, providing a pairwise confidence measure. It is slightly less |
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268 accurate than the normal monomer model. |
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269 |
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270 * **multimer**: This is the [AlphaFold-Multimer](#citing-this-work) model. |
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271 To use this model, provide a multi-sequence FASTA file. In addition, the |
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272 UniProt database should have been downloaded. |
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273 |
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274 1. You can control MSA speed/quality tradeoff by adding |
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275 `--db_preset=reduced_dbs` or `--db_preset=full_dbs` to the run command. We |
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276 provide the following presets: |
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277 |
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278 * **reduced\_dbs**: This preset is optimized for speed and lower hardware |
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279 requirements. It runs with a reduced version of the BFD database. |
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280 It requires 8 CPU cores (vCPUs), 8 GB of RAM, and 600 GB of disk space. |
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281 |
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282 * **full\_dbs**: This runs with all genetic databases used at CASP14. |
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283 |
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284 Running the command above with the `monomer` model preset and the |
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285 `reduced_dbs` data preset would look like this: |
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286 |
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287 ```bash |
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288 python3 docker/run_docker.py \ |
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289 --fasta_paths=T1050.fasta \ |
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290 --max_template_date=2020-05-14 \ |
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291 --model_preset=monomer \ |
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292 --db_preset=reduced_dbs \ |
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293 --data_dir=$DOWNLOAD_DIR |
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294 ``` |
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295 |
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296 ### Running AlphaFold-Multimer |
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297 |
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298 All steps are the same as when running the monomer system, but you will have to |
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299 |
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300 * provide an input fasta with multiple sequences, |
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301 * set `--model_preset=multimer`, |
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302 * optionally set the `--is_prokaryote_list` flag with booleans that determine |
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303 whether all input sequences in the given fasta file are prokaryotic. If that |
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304 is not the case or the origin is unknown, set to `false` for that fasta. |
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305 |
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306 An example that folds a protein complex `multimer.fasta` that is prokaryotic: |
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307 |
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308 ```bash |
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309 python3 docker/run_docker.py \ |
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310 --fasta_paths=multimer.fasta \ |
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311 --is_prokaryote_list=true \ |
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312 --max_template_date=2020-05-14 \ |
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313 --model_preset=multimer \ |
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314 --data_dir=$DOWNLOAD_DIR |
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315 ``` |
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316 |
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317 ### Examples |
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318 |
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319 Below are examples on how to use AlphaFold in different scenarios. |
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320 |
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321 #### Folding a monomer |
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322 |
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323 Say we have a monomer with the sequence `<SEQUENCE>`. The input fasta should be: |
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324 |
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325 ```fasta |
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326 >sequence_name |
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327 <SEQUENCE> |
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328 ``` |
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329 |
6c92e000d684
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330 Then run the following command: |
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331 |
6c92e000d684
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332 ```bash |
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333 python3 docker/run_docker.py \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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334 --fasta_paths=monomer.fasta \ |
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335 --max_template_date=2021-11-01 \ |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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336 --model_preset=monomer \ |
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337 --data_dir=$DOWNLOAD_DIR |
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338 ``` |
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339 |
6c92e000d684
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340 #### Folding a homomer |
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341 |
6c92e000d684
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342 Say we have a homomer from a prokaryote with 3 copies of the same sequence |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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343 `<SEQUENCE>`. The input fasta should be: |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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344 |
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345 ```fasta |
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346 >sequence_1 |
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347 <SEQUENCE> |
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348 >sequence_2 |
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349 <SEQUENCE> |
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350 >sequence_3 |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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351 <SEQUENCE> |
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352 ``` |
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353 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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354 Then run the following command: |
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355 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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356 ```bash |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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357 python3 docker/run_docker.py \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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358 --fasta_paths=homomer.fasta \ |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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359 --is_prokaryote_list=true \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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360 --max_template_date=2021-11-01 \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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361 --model_preset=multimer \ |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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362 --data_dir=$DOWNLOAD_DIR |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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363 ``` |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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364 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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365 #### Folding a heteromer |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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366 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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367 Say we have a heteromer A2B3 of unknown origin, i.e. with 2 copies of |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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368 `<SEQUENCE A>` and 3 copies of `<SEQUENCE B>`. The input fasta should be: |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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369 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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370 ```fasta |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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371 >sequence_1 |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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372 <SEQUENCE A> |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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373 >sequence_2 |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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374 <SEQUENCE A> |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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375 >sequence_3 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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376 <SEQUENCE B> |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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377 >sequence_4 |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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378 <SEQUENCE B> |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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379 >sequence_5 |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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380 <SEQUENCE B> |
6c92e000d684
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381 ``` |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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382 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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383 Then run the following command: |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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384 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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385 ```bash |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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386 python3 docker/run_docker.py \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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387 --fasta_paths=heteromer.fasta \ |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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388 --is_prokaryote_list=false \ |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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389 --max_template_date=2021-11-01 \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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390 --model_preset=multimer \ |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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391 --data_dir=$DOWNLOAD_DIR |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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392 ``` |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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393 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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394 #### Folding multiple monomers one after another |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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395 |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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396 Say we have a two monomers, `monomer1.fasta` and `monomer2.fasta`. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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397 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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398 We can fold both sequentially by using the following command: |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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399 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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400 ```bash |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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401 python3 docker/run_docker.py \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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402 --fasta_paths=monomer1.fasta,monomer2.fasta \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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403 --max_template_date=2021-11-01 \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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404 --model_preset=monomer \ |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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405 --data_dir=$DOWNLOAD_DIR |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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406 ``` |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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407 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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408 #### Folding multiple multimers one after another |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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409 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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410 Say we have a two multimers, `multimer1.fasta` and `multimer2.fasta`. Both are |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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411 from a prokaryotic organism. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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412 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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413 We can fold both sequentially by using the following command: |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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414 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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415 ```bash |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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416 python3 docker/run_docker.py \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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417 --fasta_paths=multimer1.fasta,multimer2.fasta \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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418 --is_prokaryote_list=true,true \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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419 --max_template_date=2021-11-01 \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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420 --model_preset=multimer \ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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421 --data_dir=$DOWNLOAD_DIR |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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422 ``` |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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423 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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424 ### AlphaFold output |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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425 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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426 The outputs will be saved in a subdirectory of the directory provided via the |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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427 `--output_dir` flag of `run_docker.py` (defaults to `/tmp/alphafold/`). The |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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428 outputs include the computed MSAs, unrelaxed structures, relaxed structures, |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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429 ranked structures, raw model outputs, prediction metadata, and section timings. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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430 The `--output_dir` directory will have the following structure: |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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431 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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432 ``` |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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433 <target_name>/ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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434 features.pkl |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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435 ranked_{0,1,2,3,4}.pdb |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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436 ranking_debug.json |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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437 relaxed_model_{1,2,3,4,5}.pdb |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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438 result_model_{1,2,3,4,5}.pkl |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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439 timings.json |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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440 unrelaxed_model_{1,2,3,4,5}.pdb |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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441 msas/ |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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442 bfd_uniclust_hits.a3m |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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443 mgnify_hits.sto |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
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444 uniref90_hits.sto |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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445 ``` |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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446 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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447 The contents of each output file are as follows: |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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448 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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449 * `features.pkl` – A `pickle` file containing the input feature NumPy arrays |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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450 used by the models to produce the structures. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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451 * `unrelaxed_model_*.pdb` – A PDB format text file containing the predicted |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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452 structure, exactly as outputted by the model. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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453 * `relaxed_model_*.pdb` – A PDB format text file containing the predicted |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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454 structure, after performing an Amber relaxation procedure on the unrelaxed |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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455 structure prediction (see Jumper et al. 2021, Suppl. Methods 1.8.6 for |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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456 details). |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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457 * `ranked_*.pdb` – A PDB format text file containing the relaxed predicted |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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458 structures, after reordering by model confidence. Here `ranked_0.pdb` should |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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459 contain the prediction with the highest confidence, and `ranked_4.pdb` the |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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460 prediction with the lowest confidence. To rank model confidence, we use |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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461 predicted LDDT (pLDDT) scores (see Jumper et al. 2021, Suppl. Methods 1.9.6 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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|
462 for details). |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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463 * `ranking_debug.json` – A JSON format text file containing the pLDDT values |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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464 used to perform the model ranking, and a mapping back to the original model |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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465 names. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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466 * `timings.json` – A JSON format text file containing the times taken to run |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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467 each section of the AlphaFold pipeline. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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468 * `msas/` - A directory containing the files describing the various genetic |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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469 tool hits that were used to construct the input MSA. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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|
470 * `result_model_*.pkl` – A `pickle` file containing a nested dictionary of the |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
changeset
|
471 various NumPy arrays directly produced by the model. In addition to the |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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472 output of the structure module, this includes auxiliary outputs such as: |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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|
473 |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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474 * Distograms (`distogram/logits` contains a NumPy array of shape [N_res, |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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475 N_res, N_bins] and `distogram/bin_edges` contains the definition of the |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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|
476 bins). |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
changeset
|
477 * Per-residue pLDDT scores (`plddt` contains a NumPy array of shape |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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478 [N_res] with the range of possible values from `0` to `100`, where `100` |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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|
479 means most confident). This can serve to identify sequence regions |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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|
480 predicted with high confidence or as an overall per-target confidence |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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481 score when averaged across residues. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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482 * Present only if using pTM models: predicted TM-score (`ptm` field |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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|
483 contains a scalar). As a predictor of a global superposition metric, |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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484 this score is designed to also assess whether the model is confident in |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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485 the overall domain packing. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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|
486 * Present only if using pTM models: predicted pairwise aligned errors |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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487 (`predicted_aligned_error` contains a NumPy array of shape [N_res, |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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|
488 N_res] with the range of possible values from `0` to |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
diff
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489 `max_predicted_aligned_error`, where `0` means most confident). This can |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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490 serve for a visualisation of domain packing confidence within the |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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491 structure. |
6c92e000d684
"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
galaxy-australia
parents:
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|
492 |
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493 The pLDDT confidence measure is stored in the B-factor field of the output PDB |
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494 files (although unlike a B-factor, higher pLDDT is better, so care must be taken |
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495 when using for tasks such as molecular replacement). |
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496 |
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497 This code has been tested to match mean top-1 accuracy on a CASP14 test set with |
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498 pLDDT ranking over 5 model predictions (some CASP targets were run with earlier |
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499 versions of AlphaFold and some had manual interventions; see our forthcoming |
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500 publication for details). Some targets such as T1064 may also have high |
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501 individual run variance over random seeds. |
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502 |
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503 ## Inferencing many proteins |
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504 |
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505 The provided inference script is optimized for predicting the structure of a |
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506 single protein, and it will compile the neural network to be specialized to |
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507 exactly the size of the sequence, MSA, and templates. For large proteins, the |
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508 compile time is a negligible fraction of the runtime, but it may become more |
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509 significant for small proteins or if the multi-sequence alignments are already |
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510 precomputed. In the bulk inference case, it may make sense to use our |
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511 `make_fixed_size` function to pad the inputs to a uniform size, thereby reducing |
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512 the number of compilations required. |
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513 |
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514 We do not provide a bulk inference script, but it should be straightforward to |
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515 develop on top of the `RunModel.predict` method with a parallel system for |
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516 precomputing multi-sequence alignments. Alternatively, this script can be run |
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517 repeatedly with only moderate overhead. |
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518 |
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519 ## Note on CASP14 reproducibility |
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520 |
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521 AlphaFold's output for a small number of proteins has high inter-run variance, |
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522 and may be affected by changes in the input data. The CASP14 target T1064 is a |
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523 notable example; the large number of SARS-CoV-2-related sequences recently |
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524 deposited changes its MSA significantly. This variability is somewhat mitigated |
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525 by the model selection process; running 5 models and taking the most confident. |
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526 |
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527 To reproduce the results of our CASP14 system as closely as possible you must |
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528 use the same database versions we used in CASP. These may not match the default |
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529 versions downloaded by our scripts. |
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530 |
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531 For genetics: |
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532 |
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533 * UniRef90: |
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534 [v2020_01](https://ftp.uniprot.org/pub/databases/uniprot/previous_releases/release-2020_01/uniref/) |
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535 * MGnify: |
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536 [v2018_12](http://ftp.ebi.ac.uk/pub/databases/metagenomics/peptide_database/2018_12/) |
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537 * Uniclust30: [v2018_08](http://wwwuser.gwdg.de/~compbiol/uniclust/2018_08/) |
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538 * BFD: [only version available](https://bfd.mmseqs.com/) |
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539 |
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540 For templates: |
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541 |
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542 * PDB: (downloaded 2020-05-14) |
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543 * PDB70: [2020-05-13](http://wwwuser.gwdg.de/~compbiol/data/hhsuite/databases/hhsuite_dbs/old-releases/pdb70_from_mmcif_200513.tar.gz) |
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544 |
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545 An alternative for templates is to use the latest PDB and PDB70, but pass the |
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546 flag `--max_template_date=2020-05-14`, which restricts templates only to |
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547 structures that were available at the start of CASP14. |
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548 |
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549 ## Citing this work |
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550 |
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551 If you use the code or data in this package, please cite: |
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552 |
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553 ```bibtex |
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554 @Article{AlphaFold2021, |
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555 author = {Jumper, John and Evans, Richard and Pritzel, Alexander and Green, Tim and Figurnov, Michael and Ronneberger, Olaf and Tunyasuvunakool, Kathryn and Bates, Russ and {\v{Z}}{\'\i}dek, Augustin and Potapenko, Anna and Bridgland, Alex and Meyer, Clemens and Kohl, Simon A A and Ballard, Andrew J and Cowie, Andrew and Romera-Paredes, Bernardino and Nikolov, Stanislav and Jain, Rishub and Adler, Jonas and Back, Trevor and Petersen, Stig and Reiman, David and Clancy, Ellen and Zielinski, Michal and Steinegger, Martin and Pacholska, Michalina and Berghammer, Tamas and Bodenstein, Sebastian and Silver, David and Vinyals, Oriol and Senior, Andrew W and Kavukcuoglu, Koray and Kohli, Pushmeet and Hassabis, Demis}, |
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556 journal = {Nature}, |
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557 title = {Highly accurate protein structure prediction with {AlphaFold}}, |
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558 year = {2021}, |
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559 volume = {596}, |
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560 number = {7873}, |
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561 pages = {583--589}, |
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562 doi = {10.1038/s41586-021-03819-2} |
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563 } |
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564 ``` |
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565 |
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566 In addition, if you use the AlphaFold-Multimer mode, please cite: |
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567 |
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568 ```bibtex |
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569 @article {AlphaFold-Multimer2021, |
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570 author = {Evans, Richard and O{\textquoteright}Neill, Michael and Pritzel, Alexander and Antropova, Natasha and Senior, Andrew and Green, Tim and {\v{Z}}{\'\i}dek, Augustin and Bates, Russ and Blackwell, Sam and Yim, Jason and Ronneberger, Olaf and Bodenstein, Sebastian and Zielinski, Michal and Bridgland, Alex and Potapenko, Anna and Cowie, Andrew and Tunyasuvunakool, Kathryn and Jain, Rishub and Clancy, Ellen and Kohli, Pushmeet and Jumper, John and Hassabis, Demis}, |
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571 journal = {bioRxiv} |
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572 title = {Protein complex prediction with AlphaFold-Multimer}, |
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573 year = {2021}, |
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574 elocation-id = {2021.10.04.463034}, |
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575 doi = {10.1101/2021.10.04.463034}, |
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576 URL = {https://www.biorxiv.org/content/early/2021/10/04/2021.10.04.463034}, |
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577 eprint = {https://www.biorxiv.org/content/early/2021/10/04/2021.10.04.463034.full.pdf}, |
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578 } |
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579 ``` |
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580 |
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581 ## Community contributions |
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582 |
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583 Colab notebooks provided by the community (please note that these notebooks may |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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584 vary from our full AlphaFold system and we did not validate their accuracy): |
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585 |
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586 * The [ColabFold AlphaFold2 notebook](https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb) |
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587 by Martin Steinegger, Sergey Ovchinnikov and Milot Mirdita, which uses an |
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588 API hosted at the Södinglab based on the MMseqs2 server [(Mirdita et al. |
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589 2019, Bioinformatics)](https://academic.oup.com/bioinformatics/article/35/16/2856/5280135) |
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590 for the multiple sequence alignment creation. |
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591 |
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592 ## Acknowledgements |
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593 |
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594 AlphaFold communicates with and/or references the following separate libraries |
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595 and packages: |
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596 |
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597 * [Abseil](https://github.com/abseil/abseil-py) |
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598 * [Biopython](https://biopython.org) |
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599 * [Chex](https://github.com/deepmind/chex) |
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600 * [Colab](https://research.google.com/colaboratory/) |
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601 * [Docker](https://www.docker.com) |
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602 * [HH Suite](https://github.com/soedinglab/hh-suite) |
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603 * [HMMER Suite](http://eddylab.org/software/hmmer) |
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604 * [Haiku](https://github.com/deepmind/dm-haiku) |
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605 * [Immutabledict](https://github.com/corenting/immutabledict) |
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606 * [JAX](https://github.com/google/jax/) |
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607 * [Kalign](https://msa.sbc.su.se/cgi-bin/msa.cgi) |
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608 * [matplotlib](https://matplotlib.org/) |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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609 * [ML Collections](https://github.com/google/ml_collections) |
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610 * [NumPy](https://numpy.org) |
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611 * [OpenMM](https://github.com/openmm/openmm) |
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612 * [OpenStructure](https://openstructure.org) |
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613 * [pandas](https://pandas.pydata.org/) |
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614 * [pymol3d](https://github.com/avirshup/py3dmol) |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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615 * [SciPy](https://scipy.org) |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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616 * [Sonnet](https://github.com/deepmind/sonnet) |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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617 * [TensorFlow](https://github.com/tensorflow/tensorflow) |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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618 * [Tree](https://github.com/deepmind/tree) |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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619 * [tqdm](https://github.com/tqdm/tqdm) |
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620 |
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621 We thank all their contributors and maintainers! |
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622 |
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623 ## License and Disclaimer |
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624 |
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625 This is not an officially supported Google product. |
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626 |
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627 Copyright 2021 DeepMind Technologies Limited. |
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628 |
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629 ### AlphaFold Code License |
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630 |
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631 Licensed under the Apache License, Version 2.0 (the "License"); you may not use |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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632 this file except in compliance with the License. You may obtain a copy of the |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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633 License at https://www.apache.org/licenses/LICENSE-2.0. |
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634 |
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635 Unless required by applicable law or agreed to in writing, software distributed |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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636 under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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637 CONDITIONS OF ANY KIND, either express or implied. See the License for the |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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638 specific language governing permissions and limitations under the License. |
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639 |
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640 ### Model Parameters License |
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641 |
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642 The AlphaFold parameters are made available for non-commercial use only, under |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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643 the terms of the Creative Commons Attribution-NonCommercial 4.0 International |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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644 (CC BY-NC 4.0) license. You can find details at: |
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"planemo upload for repository https://github.com/usegalaxy-au/galaxy-local-tools commit a510e97ebd604a5e30b1f16e5031f62074f23e86"
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645 https://creativecommons.org/licenses/by-nc/4.0/legalcode |
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646 |
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647 ### Third-party software |
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648 |
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649 Use of the third-party software, libraries or code referred to in the |
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650 [Acknowledgements](#acknowledgements) section above may be governed by separate |
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651 terms and conditions or license provisions. Your use of the third-party |
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652 software, libraries or code is subject to any such terms and you should check |
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653 that you can comply with any applicable restrictions or terms and conditions |
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654 before use. |
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655 |
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656 ### Mirrored Databases |
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657 |
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658 The following databases have been mirrored by DeepMind, and are available with reference to the following: |
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659 |
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660 * [BFD](https://bfd.mmseqs.com/) (unmodified), by Steinegger M. and Söding J., available under a [Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/). |
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661 |
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662 * [BFD](https://bfd.mmseqs.com/) (modified), by Steinegger M. and Söding J., modified by DeepMind, available under a [Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/). See the Methods section of the [AlphaFold proteome paper](https://www.nature.com/articles/s41586-021-03828-1) for details. |
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663 |
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664 * [Uniclust30: v2018_08](http://wwwuser.gwdg.de/~compbiol/uniclust/2018_08/) (unmodified), by Mirdita M. et al., available under a [Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/). |
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665 |
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666 * [MGnify: v2018_12](http://ftp.ebi.ac.uk/pub/databases/metagenomics/peptide_database/current_release/README.txt) (unmodified), by Mitchell AL et al., available free of all copyright restrictions and made fully and freely available for both non-commercial and commercial use under [CC0 1.0 Universal (CC0 1.0) Public Domain Dedication](https://creativecommons.org/publicdomain/zero/1.0/). |