Too many command-line arguments.

[kbrunnerLXG]

So I was having issues with alphafold while builoding the docker image and decided to try this out i was able to follow all the steps but still can not run alphafold.

bash run_alphafold.sh -d /media/aditya/New\ Volume/protein_database/ -o ./dummy_test/ -f ./example/query.fasta -t 2020-05-14 Full AlphaFold protein structure prediction script. flags:

/home/aditya/alphafold-2.3.1/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: '/home/aditya/miniconda3/envs/alphafold/bin/hhblits') --hhsearch_binary_path: Path to the HHsearch executable. (default: '/home/aditya/miniconda3/envs/alphafold/bin/hhsearch') --hmmbuild_binary_path: Path to the hmmbuild executable. (default: '/home/aditya/miniconda3/envs/alphafold/bin/hmmbuild') --hmmsearch_binary_path: Path to the hmmsearch executable. (default: '/home/aditya/miniconda3/envs/alphafold/bin/hmmsearch') --jackhmmer_binary_path: Path to the JackHMMER executable. (default: '/home/aditya/miniconda3/envs/alphafold/bin/jackhmmer') --kalign_binary_path: Path to the Kalign executable. (default: '/home/aditya/miniconda3/envs/alphafold/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') --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) --[no]run_relax: Whether to run the final relaxation step on the predicted models. Turning relax off might result in predictions with distracting stereochemical violations but might help in case you are having issues with the relaxation stage. (default: 'true') --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 .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')

Too many command-line arguments.

I have the alphafold database on a seperate NTSF formatted drive but i was in the past able to predict using this very same drive

[Lili-irtyd]

Hello, I also meet this question. I think the reason may be the space from the name of remote disk, like "New\ Volume",but I don't know how to solve it. If you know it already, please tell me.

[nlbrown62]

It looks like in this case, the space in "New\ Volume" was causing argument splitting, which can be fixed by putting double quotes around the entire path (i.e. "/media/aditya/New\ Volume/protein_database/"). I also came across the same error for another reason though. In lines 176-180 in run_alphafold.sh, if the which command is set to an alias on the user's computer (sometimes this can happen by accident), it returns an incorrect or missing argument instead of a database path. command and type tend to be more portable across systems. I've found that the following works more consistently - maybe it could be used instead of 'which'?:

# Binary path (change me if required)
hhblits_binary_path=$(command -v hhblits)
hhsearch_binary_path=$(command -v hhsearch)
jackhmmer_binary_path=$(command -v jackhmmer)
kalign_binary_path=$(command -v kalign)