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gezmijvargasokrypton
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calculating actifpTM only for interface residues, based on the predicted distogram (sokrypton#671)
* version of extended metrics, doesnt work because of tracing and dynamic conflict * pairwise actifptm, iptm and chain-ptm calculation and plotting * setting back poetry files to original * updated version * adding extended metrics calculation * added command line arguments for actifptm * import differently in colabdesign and colabfold * fixed actifptm plot titles * added actifptm * added extended metrics to run function * using/not using probabilities fixed * working version of cull complex actifptm, with plots * working actifptm, including for the whole complex * actifptm with contacts not to crash without contacts between chains * actifptm with contacts not to crash without contacts between chains * removed unnecessary print * small fixes * fixes * correct script for af2 ptm * updated calculation of font sizes in figure * actifptm doesnt crash with models without ptm * not crashing with base af2 (no ptm) models, renamed extended to extra * Update AlphaFold2.ipynb --------- Co-authored-by: jvarga <[email protected]> Co-authored-by: Sergey O <[email protected]>
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AlphaFold2.ipynb

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"metadata": {
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"accelerator": "GPU",
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"colab": {
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"name": "AlphaFold2.ipynb",
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"provenance": [],
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"machine_shape": "hm",
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"gpuType": "T4",
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"include_colab_link": true
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"gpuType": "A100"
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},
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"kernelspec": {
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"display_name": "Python 3",
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}
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"cell_type": "code",
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"source": [
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"#@markdown ### Advanced settings\n",
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"model_type = \"auto\" #@param [\"auto\", \"alphafold2_ptm\", \"alphafold2_multimer_v1\", \"alphafold2_multimer_v2\", \"alphafold2_multimer_v3\", \"deepfold_v1\"]\n",
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"model_type = \"auto\" #@param [\"auto\", \"alphafold2_ptm\", \"alphafold2_multimer_v1\", \"alphafold2_multimer_v2\", \"alphafold2_multimer_v3\", \"deepfold_v1\", \"alphafold2\"]\n",
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"#@markdown - if `auto` selected, will use `alphafold2_ptm` for monomer prediction and `alphafold2_multimer_v3` for complex prediction.\n",
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"#@markdown Any of the mode_types can be used (regardless if input is monomer or complex).\n",
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"num_recycles = \"3\" #@param [\"auto\", \"0\", \"1\", \"3\", \"6\", \"12\", \"24\", \"48\"]\n",
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"#@markdown - max amber relax iterations, `0` = unlimited (AlphaFold2 default, can take very long)\n",
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"pairing_strategy = \"greedy\" #@param [\"greedy\", \"complete\"] {type:\"string\"}\n",
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"#@markdown - `greedy` = pair any taxonomically matching subsets, `complete` = all sequences have to match in one line.\n",
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"\n",
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"calc_extra_ptm = False #@param {type:\"boolean\"}\n",
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"#@markdown - return pairwise chain iptm/actifptm\n",
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"\n",
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"#@markdown #### Sample settings\n",
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"#@markdown - enable dropouts and increase number of seeds to sample predictions from uncertainty of the model.\n",
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" input_features_callback=input_features_callback,\n",
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" save_recycles=save_recycles,\n",
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" user_agent=\"colabfold/google-colab-main\",\n",
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" calc_extra_ptm=calc_extra_ptm,\n",
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")\n",
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"results_zip = f\"{jobname}.result.zip\"\n",
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"os.system(f\"zip -r {results_zip} {jobname}\")"
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "33g5IIegij5R",
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"cellView": "form"
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},
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"source": [
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"#@title Package and download results\n",
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"#@markdown If you are having issues downloading the result archive, try disabling your adblocker and run this cell again. If that fails click on the little folder icon to the left, navigate to file: `jobname.result.zip`, right-click and select \\\"Download\\\" (see [screenshot](https://pbs.twimg.com/media/E6wRW2lWUAEOuoe?format=jpg&name=small)).\n",
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" uploaded.Upload()\n",
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" print(f\"Uploaded {jobname}.result.zip to Google Drive with ID {uploaded.get('id')}\")"
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],
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"metadata": {
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"cellView": "form",
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"id": "R_AH6JSXaeb2"
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},
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"execution_count": null,
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"outputs": []
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},

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