Add AlphaFold3 to software guides

Author: grvlbit

docs/software/packages/alphafold3.md

@@ -0,0 +1,172 @@
+# AlphaFold3
+
+AlphaFold3 is a cutting-edge AI system developed by DeepMind for predicting protein structures with high accuracy. Building on its predecessors, AlphaFold3 integrates additional molecular modeling capabilities, making it a powerful tool for structural biology research.
+
+This guide provides step-by-step instructions on setting up and running AlphaFold3 on UBELIX using Slurm.
+
+## Directory Structure Setup
+
+Before running AlphaFold3, set up the necessary directory structure.
+
+1. Choose a suitable location for AlphaFold3. For example:
+   ```bash
+   export AF3_ROOT=~/alphafold3/
+   ```
+2. Create the required directories:
+   ```bash
+   mkdir -p $AF3_ROOT
+   mkdir -p $AF3_ROOT/input             # Store input JSON files
+   mkdir -p $AF3_ROOT/output            # Store generated structure outputs
+   mkdir -p $AF3_ROOT/model_parameters  # Store downloaded model parameters
+   mkdir -p $AF3_ROOT/databases         # Store public databases
+   ```
+
+## Cloning the AlphaFold3 Repository
+
+Clone the official AlphaFold3 source code from GitHub:
+
+```bash
+cd $AF3_ROOT
+git clone https://github.com/google-deepmind/alphafold3.git src
+```
+
+## Creating the Slurm Submission Script
+
+Create a Slurm submission script (e.g., `run_alphafold3.sh`) for running AlphaFold3 on a GPU node.
+
+1. Navigate to the project directory:
+   ```bash
+   cd $AF3_ROOT
+   ```
+2. Create `run_alphafold3.sh` and add the following content:
+   ```bash
+   #!/bin/bash
+   #SBATCH --job-name="alphafold3_job"
+   #SBATCH --time=01:00:00
+   #SBATCH --partition=gpu
+   #SBATCH --gres=gpu:rtx4090:1
+   #SBATCH --cpus-per-task=16
+   #SBATCH --mem-per-cpu=5760M
+
+   module load CUDA/12.6
+
+   singularity exec \
+        --nv \
+        --bind $PWD/input:/root/af_input \
+        --bind $PWD/output:/root/af_output \
+        --bind $PWD/model_parameters:/root/models \
+        --bind $PWD/databases:/root/public_databases \
+        /storage/software/singularity/containers/alphafold3.sif \
+        python src/run_alphafold.py \
+        --json_path=/root/af_input/fold_input.json \
+        --model_dir=/root/models \
+        --db_dir=/root/public_databases \
+        --output_dir=/root/af_output
+   ```
+4. Save and close the file
+
+## Downloading Public Databases
+
+AlphaFold3 requires publicly available databases for structure prediction.
+
+!!! danger "Danger: Very large databases"
+
+    The AlphaFold3 databases are nearly 650GB in size. To avoid redundant downloads and conserve storage, it is recommended that a single copy be maintained in a shared workspace for the entire lab. Check with colleagues and supervisors if a copy of the databases is already accessible to you!
+
+    === "Link existing databases"
+
+        If the public databases are already available, simply create a symbolic
+        link to their location:
+
+        ```bash
+        cd $AF3_ROOT
+        ln -s /path/to/workspace/databases databases
+        ```
+
+    === "Install databases to shared workspace"
+
+        1. Navigate to the shared workspace to store the dabases, e.g.:
+           ```bash
+           cd /path/to/workspace/alphafold3/databases
+           ```
+        2. Download the database fetch script:
+           ```bash
+           wget https://raw.githubusercontent.com/google-deepmind/alphafold3/refs/heads/main/fetch_databases.sh
+           ```
+        3. Make the script executable and run it:
+           ```bash
+           chmod u+x fetch_databases.sh
+           ./fetch_databases.sh databases
+           ```
+         4. Continue with lining existing databases
+           ```bash
+           cd $AF3_ROOT
+           ln -s /path/to/workspace/databases databases
+           ```
+
+    === "Install databases to user home "
+
+        1. Navigate to the AlphaFold3 project directory:
+           ```bash
+           cd $AF3_ROOT
+           ```
+        2. Download the database fetch script:
+           ```bash
+           wget https://raw.githubusercontent.com/google-deepmind/alphafold3/refs/heads/main/fetch_databases.sh
+           ```
+        3. Make the script executable and run it:
+           ```bash
+           chmod u+x fetch_databases.sh
+           ./fetch_databases.sh databases
+           ```
+
+## Downloading Model Parameters
+
+AlphaFold3 model parameters need to be downloaded separately. To request access to the model parameters, please complete this [form](https://forms.gle/svvpY4u2jsHEwWYS6). Access will be granted at Google DeepMind’s sole discretion. You may only use AlphaFold 3 model parameters if received directly from Google. Use is subject to these [terms of use](https://github.com/google-deepmind/alphafold3/blob/main/WEIGHTS_TERMS_OF_USE.md).
+
+Ensure they are stored in the `model_parameters` directory:
+
+```bash
+cd $AF3_ROOT/model_parameters
+# Download and extract model parameters following official AlphaFold3 instructions.
+```
+
+## Preparing Input File
+
+AlphaFold3 requires a JSON input file containing sequence and configuration details. Create an input file at `input/fold_input.json`:
+
+Example:
+
+```json
+{
+  "name": "2PV7",
+  "sequences": [
+    {
+      "protein": {
+        "id": ["A", "B"],
+        "sequence": "GMRESYANENQFGFKTINSDIHKIVIVGGYGKLGGLFARYLRASGYPISILDREDWAVAESILANADVVIVSVPINLTLETIERLKPYLTENMLLADLTSVKREPLAKMLEVHTGAVLGLHPMFGADIASMAKQVVVRCDGRFPERYEWLLEQIQIWGAKIYQTNATEHDHNMTYIQALRHFSTFANGLHLSKQPINLANLLALSSPIYRLELAMIGRLFAQDAELYADIIMDKSENLAVIETLKQTYDEALTFFENNDRQGFIDAFHKVRDWFGDYSEQFLKESRQLLQQANDLKQG"
+      }
+    }
+  ],
+  "modelSeeds": [1],
+  "dialect": "alphafold3",
+  "version": 1
+}
+```
+
+## Submitting the Job
+
+Once everything is set up, submit the job to Slurm:
+
+```bash
+sbatch run_alphafold3.sh
+```
+
+## Output Location
+
+Once the job is complete, the predicted structures will be available in:
+
+```
+$AF3_ROOT/output/
+```
+