Update version in colab

PiperOrigin-RevId: 480643781
Change-Id: Id4bfa90b71cd59b148a3c2a61ddb65c41192712b

notebooks/AlphaFold.ipynb

@@ -8,11 +8,11 @@
       "source": [
         "# AlphaFold Colab\n",
         "\n",
-        "This Colab notebook allows you to easily predict the structure of a protein using a slightly simplified version of [AlphaFold v2.1.0](https://doi.org/10.1038/s41586-021-03819-2). \n",
+        "This Colab notebook allows you to easily predict the structure of a protein using a slightly simplified version of [AlphaFold v2.2.4](https://doi.org/10.1038/s41586-021-03819-2). \n",
         "\n",
-        "**Differences to AlphaFold v2.1.0**\n",
+        "**Differences to AlphaFold v2.2.4**\n",
         "\n",
-        "In comparison to AlphaFold v2.1.0, this Colab notebook uses **no templates (homologous structures)** and a selected portion of the [BFD database](https://bfd.mmseqs.com/). We have validated these changes on several thousand recent PDB structures. While accuracy will be near-identical to the full AlphaFold system on many targets, a small fraction have a large drop in accuracy due to the smaller MSA and lack of templates. For best reliability, we recommend instead using the [full open source AlphaFold](https://github.com/deepmind/alphafold/), or the [AlphaFold Protein Structure Database](https://alphafold.ebi.ac.uk/).\n",
+        "In comparison to AlphaFold v2.2.4, this Colab notebook uses **no templates (homologous structures)** and a selected portion of the [BFD database](https://bfd.mmseqs.com/). We have validated these changes on several thousand recent PDB structures. While accuracy will be near-identical to the full AlphaFold system on many targets, a small fraction have a large drop in accuracy due to the smaller MSA and lack of templates. For best reliability, we recommend instead using the [full open source AlphaFold](https://github.com/deepmind/alphafold/), or the [AlphaFold Protein Structure Database](https://alphafold.ebi.ac.uk/).\n",
         "\n",
         "**This Colab has a small drop in average accuracy for multimers compared to local AlphaFold installation, for full multimer accuracy it is highly recommended to run [AlphaFold locally](https://github.com/deepmind/alphafold#running-alphafold).** Moreover, the AlphaFold-Multimer requires searching for MSA for every unique sequence in the complex, hence it is substantially slower. If your notebook times-out due to slow multimer MSA search, we recommend either using Colab Pro or running AlphaFold locally.\n",
         "\n",