AlphaFold

O AlphaFold é um software de modelagem de estrutura proteicas utilizando redes neurais artificiais (Deep Learning). Ele também é capaz de modelar multímeros e complexos.

Para mais informações sobre o uso do AlphaFold acesse o repositório.

Abaixo descrevemos resumidamente como rodar o AlphaFold no MARVIN (marvin.cnpem.br). Está nos planos tornar a tarefa mais fácil e amigável aos usuários, por isso, essa página irá mudar ao longo do tempo.

Como usar

Para utilizar o AlphaFold são necessários os seguintes passos:

1. criar uma pasta contendo o arquivo fasta da(s) proteína(s) para modelar. ex fasta_dir
2. criar um script da tarefa para submetê-la ao SLURM através do sbatch

Abaixo um exemplo da tarefa para submissão. Após salvar o arquivo (ex. nova_tarefa_alphafold.sh), fazemos a submissão para que ele entre na fila de execucão com o comando sbatch (ex. sbatch nova_tarefa_alphafold.sh).

#!/bin/sh
#SBATCH --job-name=alphafold
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=4
#SBATCH --partition=short-gpu-small
#SBATCH --mem-per-cpu=8G
#SBATCH --gres=gpu:1g.5gb:1

# essa variável aponta para o banco de dados utilizado pelo alphafold (NÃO ALTERE)   
ALPHAFOLD_DB=/public/alphafold_db_20220825

# imagem do singularity onde o alphafold está instalá-do (NÃO ALTERE)
ALPHAFOLD_SIF=/opt/images/alphafold/alphafold-2_3_2.sif

# essa variável aponta para o arquivo fasta (MUDE PARA O SEU ARQUIVO) 
FASTA_FILE=./fasta_dir/P01308.fasta

# nome da pasta onde os modelos e resultados serão salvos (PODE MUDAR PARA UM NOME QUE ESCOLHER)
OUTPUT_DIR=./results

# comando de execução do AlphaFold
singularity run --nv -B $ALPHAFOLD_DB:/database $ALPHAFOLD_SIF \
    --fasta_paths=$FASTA_FILE \
    --output_dir=$OUTPUT_DIR \
    --data_dir=/database/ \
    --template_mmcif_dir=/database/pdb_mmcif/mmcif_files/ \
    --obsolete_pdbs_path=/database/pdb_mmcif/obsolete.dat \
    --uniref90_database_path=/database/uniref90/uniref90.fasta \
    --mgnify_database_path=/database/mgnify/mgy_clusters_2018_12.fa \
    --pdb70_database_path=/database/pdb70/pdb70 \
    --uniclust30_database_path=/database/uniclust30/uniclust30_2018_08/uniclust30_2018_08 \
    --bfd_database_path=/database/bfd/bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt \
    --max_template_date=`date +'%Y-%m-%d'` \
    --use_gpu_relax 

Abaixo estão os argumentos aceitos pelo AlphaFold.

❯ singularity run ~/singularity-defs/singularity-alphafold/alphafold.sif --helpshort
Full AlphaFold protein structure prediction script.
flags:

/opt/alphafold/run_alphafold.py:
  --[no]benchmark: Run multiple JAX model evaluations to obtain a timing that excludes the compilation time, which should be
    more indicative of the time required for inferencing many proteins.
    (default: 'false')
  --bfd_database_path: Path to the BFD database for use by HHblits.
  --data_dir: Path to directory of supporting data.
  --db_preset: <full_dbs|reduced_dbs>: Choose preset MSA database configuration - smaller genetic database config (reduced_dbs)
    or full genetic database config  (full_dbs)
    (default: 'full_dbs')
  --fasta_paths: Paths to FASTA files, each containing a prediction target that will be folded one after another. If a FASTA
    file contains multiple sequences, then it will be folded as a multimer. Paths should be separated by commas. All FASTA
    paths must have a unique basename as the basename is used to name the output directories for each prediction.
    (a comma separated list)
  --hhblits_binary_path: Path to the HHblits executable.
    (default: '/usr/bin/hhblits')
  --hhsearch_binary_path: Path to the HHsearch executable.
    (default: '/usr/bin/hhsearch')
  --hmmbuild_binary_path: Path to the hmmbuild executable.
    (default: '/usr/bin/hmmbuild')
  --hmmsearch_binary_path: Path to the hmmsearch executable.
    (default: '/usr/bin/hmmsearch')
  --jackhmmer_binary_path: Path to the JackHMMER executable.
    (default: '/usr/bin/jackhmmer')
  --kalign_binary_path: Path to the Kalign executable.
    (default: '/usr/bin/kalign')
  --max_template_date: Maximum template release date to consider. Important if folding historical test sets.
  --mgnify_database_path: Path to the MGnify database for use by JackHMMER.
  --model_preset: <monomer|monomer_casp14|monomer_ptm|multimer>: Choose preset model configuration - the monomer model, the
    monomer model with extra ensembling, monomer model with pTM head, or multimer model
    (default: 'monomer')
  --models_to_relax: <all|best|none>: The models to run the final relaxation step on. If `all`, all models are relaxed, which
    may be time consuming. If `best`, only the most confident model is relaxed. If `none`, relaxation is not run. Turning off
    relaxation might result in predictions with distracting stereochemical violations but might help in case you are having
    issues with the relaxation stage.
    (default: 'best')
  --num_multimer_predictions_per_model: How many predictions (each with a different random seed) will be generated per model.
    E.g. if this is 2 and there are 5 models then there will be 10 predictions per input. Note: this FLAG only applies if
    model_preset=multimer
    (default: '5')
    (an integer)
  --obsolete_pdbs_path: Path to file containing a mapping from obsolete PDB IDs to the PDB IDs of their replacements.
  --output_dir: Path to a directory that will store the results.
  --pdb70_database_path: Path to the PDB70 database for use by HHsearch.
  --pdb_seqres_database_path: Path to the PDB seqres database for use by hmmsearch.
  --random_seed: The random seed for the data pipeline. By default, this is randomly generated. Note that even if this is set,
    Alphafold may still not be deterministic, because processes like GPU inference are nondeterministic.
    (an integer)
  --small_bfd_database_path: Path to the small version of BFD used with the "reduced_dbs" preset.
  --template_mmcif_dir: Path to a directory with template mmCIF structures, each named <pdb_id>.cif
  --uniprot_database_path: Path to the Uniprot database for use by JackHMMer.
  --uniref30_database_path: Path to the UniRef30 database for use by HHblits.
  --uniref90_database_path: Path to the Uniref90 database for use by JackHMMER.
  --[no]use_gpu_relax: Whether to relax on GPU. Relax on GPU can be much faster than CPU, so it is recommended to enable if
    possible. GPUs must be available if this setting is enabled.
  --[no]use_precomputed_msas: Whether to read MSAs that have been written to disk instead of running the MSA tools. The MSA
    files are looked up in the output directory, so it must stay the same between multiple runs that are to reuse the MSAs.
    WARNING: This will not check if the sequence, database or configuration have changed.
    (default: 'false')

Try --helpfull to get a list of all flags.

Versões disponíveis

data de atualização: 2023-05-02