ColabFold / AlphaFold2_advanced on your local PC (or macOS)

Yoshitaka Moriwaki

Last update: Dec 22, 2022

Related tags

Miscellaneous localcolabfold

Overview

LocalColabFold

ColabFold / AlphaFold2_advanced on your local PC (or macOS)

Installation

For Linux

Make sure curl and wget commands are already installed on your PC. If not present, you need install them at first. For Ubuntu, type sudo apt -y install curl wget.
Download install_colabfold_linux.sh from this repository:
```
$ wget https://raw.githubusercontent.com/YoshitakaMo/localcolabfold/main/install_colabfold_linux.sh
```
and run it in the directory where you want to install:
```
$ bash install_colabfold_linux.sh
```
About 5 minutes later, colabfold directory will be created. Do not move this directory after the installation.
Type cd colabfold to enter the directory.
Modify the variables such as sequence = 'PIAQIHILEGRSDEQKETLIREVSEAISRSLDAPLTSVRVIITEMAKGHFGIGGELASK', jobname = "test", and etc. in runner.py for your prediction. For more information, please refer to the original ColabFold / AlphaFold2_advanced.
To run the prediction, type
```
$ colabfold-conda/bin/python3.7 runner.py
```
in the colabfold directory. The result files will be created in the predition__ in the colabfold directory. After the prediction finished, you may move the results from the colabfold directory.

For macOS

Caution: Due to the lack of Nvidia GPU/CUDA driver, the structure prediction on macOS are 5-10 times slower than on Linux+GPU. For the test sequence (58 a.a.), it may take 30 minutes. However, it may be useful to play with it before preparing Linux+GPU environment.

You can check whether your Mac is Intel or Apple Silicon by typing uname -m on Terminal.

$ uname -m
x86_64 # Intel
arm64  # Apple Silicon

Please use the correct installer for your Mac.

For Mac with Intel CPU

Install Homebrew if not present:

$ /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

Install wget command using Homebrew:
```
$ brew install wget
```
Download install_colabfold_intelmac.sh from this repository:
```
$ wget https://raw.githubusercontent.com/YoshitakaMo/localcolabfold/main/install_colabfold_intelmac.sh
```
and run it in the directory where you want to install:
```
$ bash install_colabfold_intelmac.sh
```
About 5 minutes later, colabfold directory will be created. Do not move this directory after the installation.
The rest procedure is the same as "For Linux".

For Mac with Apple Silicon (M1 chip)

Note: This installer is experimental because most of the dependent packages are not fully tested on Apple Silicon Mac.

Install Homebrew if not present:

$ /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

Install wget command using Homebrew:
```
$ brew install wget
```
Install miniforge command using Homebrew:
```
$ brew install --cask miniforge
```
Download install_colabfold_M1mac.sh from this repository:
```
$ wget https://raw.githubusercontent.com/YoshitakaMo/localcolabfold/main/install_colabfold_M1mac.sh
```
and run it in the directory where you want to install:
```
$ bash install_colabfold_M1mac.sh
```
About 5 minutes later, colabfold directory will be created. Do not move this directory after the installation.
Type cd colabfold to enter the directory.
Modify the variables such as sequence = 'PIAQIHILEGRSDEQKETLIREVSEAISRSLDAPLTSVRVIITEMAKGHFGIGGELASK', jobname = "test", and etc. in runner.py for your prediction. For more information, please refer to the original ColabFold / AlphaFold2_advanced.
To run the prediction, type
```
$ colabfold-conda/bin/python3.8 runner.py
```
in the colabfold directory. The result files will be created in the predition__ in the colabfold directory. After the prediction finished, you may move the results from the colabfold directory.

A Warning message appeared when you run the prediction:

You are using an experimental build of OpenMM v7.5.1.
This is NOT SUITABLE for production!
It has not been properly tested on this platform and we cannot guarantee it provides accurate results.

This message is due to Apple Silicon, but I think we can ignore it.

Advantages of LocalColabFold

Structure inference and relaxation will be accelerated if your PC has Nvidia GPU and CUDA drivers.
No Time out (90 minutes and 12 hours), No GPU limitations.
You don't need prepare the large database required for native AlphaFold2.

FAQ

What else do I need to do before installation? Do I need sudo privileges?
- No, except for installation of curl and wget commands.
Do I need to prepare the large database such as PDB70, BFD, Uniclust30, MGnify...?
- No. it is not necessary. Generation of MSA is performed by the MMseqs2 web server, just as implemented in ColabFold.
Are the pLDDT score and PAE figures available?
- Yes, they will be generated just like the ColabFold.
Is it possible to predict homooligomers and complexes?
- Yes, the sequence input is the same as ColabFold. See ColabFold / AlphaFold2_advanced.
Is it possible to create MSA by jackhmmer?
- No, it is not currently supported.
I want to run the predictions step-by-step like Google Colab.
- You can use VSCode and Python plugin to do the same. See https://code.visualstudio.com/docs/python/jupyter-support-py.
Is this available on Windows 10?
- You can run LocalColabFold on your Windows 10 with WSL2.

Tutorials & Presentations

ColabFold Tutorial presented at the Boston Protein Design and Modeling Club. [video] [slides].

Acknowledgments

The original colabfold was created by Sergey Ovchinnikov (@sokrypton), Milot Mirdita (@milot_mirdita) and Martin Steinegger (@thesteinegger).

How do I reference this work?

Mirdita M, Ovchinnikov S and Steinegger M. ColabFold - Making protein folding accessible to all. bioRxiv, doi: 10.1101/2021.08.15.456425 (2021)
I, Yoshitaka Moriwaki, am credited in the acknowlegment of the paper.
John Jumper, Richard Evans, Alexander Pritzel, et al. - Highly accurate protein structure prediction with AlphaFold. Nature, 1–11, doi: 10.1038/s41586-021-03819-2 (2021)

Comments

Question:
What is your question? During the execution of the Local-ColabFold by the following command, it encounters a problem. The error file was attached. $ colabfold_batch --amber --templates --num-recycle 3 --use-gpu-relax --zip inputfile outputdir/

Computational environment

OS: [Ubuntu 22.04]

CUDA version if Linux (11.7)

colabfold_error.txt
opened by biotech70 41

Error in recent colabfold_batch with --templates option

Hi Yoshitaka-san,

I tried your latest colabfold_batch code. With the following command, following your instruction in main page:

$ colabfold_batch --amber --templates --num-recycle 3 input_fasta/test.fasta af2_output

The input_fasta/test.fasta contains this:


$ cat input_fasta/test.fasta
>Gvb.fl_hhaw_x1.s1
HHAWEPEKKKPEGMKDQPSKQHHAW
>Gvb.fl_hhaw_x1.s10
HHAWSNYDERKQNGRYYIWKEHHAW

But I get the following error. How can I resolve it?

$ colabfold_batch --amber --templates --num-recycle 3  input_fasta/test.fasta af2_output
WARNING: You are welcome to use the default MSA server, however keep in mind that it's a limited shared resource only capable of processing a few thousand MSAs per day. Please submit jobs only from a single IP address. We reserve the right to limit access to the server case-by-case when usage exceeds fair use.

If you require more MSAs, please host your own API and pass it to `--host-url`
2021-12-06 15:40:37,273 Found 8 citations for tools or databases
2021-12-06 15:40:46,439 Query 1/2: Gvb.fl_hhaw_x1.s1 (length 25)
COMPLETE: 100%|████████████████████████████████████████████████████████████████████████████████████████| 150/150 [elapsed: 00:02 remaining: 00:00]
0	no_templates_found
2021-12-06 15:40:48,450 Could not get MSA/templates for Gvb.fl_hhaw_x1.s1: expected str, bytes or os.PathLike object, not NoneType
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/colabfold/batch.py", line 603, in run
    host_url,
  File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/colabfold/batch.py", line 428, in get_msa_and_templates
    query_seqs_unique[index],
  File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/colabfold/batch.py", line 93, in mk_template
    obsolete_pdbs_path=None,
  File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/alphafold/data/templates.py", line 836, in __init__
    if not glob.glob(os.path.join(self._mmcif_dir, '*.cif')):
  File "/home/ubuntu/anaconda3/lib/python3.7/posixpath.py", line 80, in join
    a = os.fspath(a)
TypeError: expected str, bytes or os.PathLike object, not NoneType
2021-12-06 15:40:48,451 Query 2/2: Gvb.fl_hhaw_x1.s10 (length 25)
2021-12-06 15:40:49,415 Sleeping for 9s. Reason: RATELIMIT
2021-12-06 15:40:59,395 Sleeping for 8s. Reason: RATELIMIT
2021-12-06 15:41:08,362 Sleeping for 5s. Reason: RATELIMIT
2021-12-06 15:41:14,342 Sleeping for 5s. Reason: RATELIMIT
2021-12-06 15:41:20,315 Sleeping for 10s. Reason: RATELIMIT
COMPLETE: 100%|████████████████████████████████████████████████████████████████████████████████████████| 150/150 [elapsed: 00:43 remaining: 00:00]
0	no_templates_found
2021-12-06 15:41:32,334 Could not get MSA/templates for Gvb.fl_hhaw_x1.s10: expected str, bytes or os.PathLike object, not NoneType
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/colabfold/batch.py", line 603, in run
    host_url,
  File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/colabfold/batch.py", line 428, in get_msa_and_templates
    query_seqs_unique[index],
  File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/colabfold/batch.py", line 93, in mk_template
    obsolete_pdbs_path=None,
  File "/home/ubuntu/anaconda3/lib/python3.7/site-packages/alphafold/data/templates.py", line 836, in __init__
    if not glob.glob(os.path.join(self._mmcif_dir, '*.cif')):
  File "/home/ubuntu/anaconda3/lib/python3.7/posixpath.py", line 80, in join
    a = os.fspath(a)
TypeError: expected str, bytes or os.PathLike object, not NoneType
2021-12-06 15:41:32,334 Done

opened by gundalav 29

Command-line version of AF2-Multimer?

Hi Yoshitaka-san,

As you mentioned AF2-Multimerseem to be available now. Is there a way we can port it to command line version? Just like your great AF2_advanced.

G.V.

opened by gundalav 21
ValueError: Could not find CIFs in ...
What is your question? The program raise this error all of a sudden. The problem pop up today and it ran quite well before. I saw the similar issue here but I didn't see any new version released so I assume this is not the problem of my current version?

Computational environment

OS: centOS7

CUDA version if Linux 11.1.74
opened by TieliangGan 14
Error when relaxing: jax._src.traceback_util.UnfilteredStackTrace: TypeError: take requires ndarray or scalar arguments, got at position 0.

Hi, I just updated my code to the last commit and it works fine with the default num_relax = "None", but not with num_relax = "Top5":

colabfold-conda/bin/python3.7 runner.py 2021-09-28 07:03:03.449188: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0 2021-09-28 07:03:05.429501: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcuda.so.1 2021-09-28 07:03:05.589721: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1733] Found device 0 with properties: pciBusID: 0000:0a:00.0 name: NVIDIA GeForce GTX 1080 Ti computeCapability: 6.1 coreClock: 1.582GHz coreCount: 28 deviceMemorySize: 10.92GiB deviceMemoryBandwidth: 451.17GiB/s 2021-09-28 07:03:05.589805: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-09-28 07:03:05.592761: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1733] Found device 1 with properties: pciBusID: 0000:42:00.0 name: NVIDIA GeForce GTX 1080 Ti computeCapability: 6.1 coreClock: 1.582GHz coreCount: 28 deviceMemorySize: 10.91GiB deviceMemoryBandwidth: 451.17GiB/s 2021-09-28 07:03:05.592788: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0 2021-09-28 07:03:05.603415: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublas.so.11 2021-09-28 07:03:05.603500: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublasLt.so.11 2021-09-28 07:03:05.610883: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcufft.so.10 2021-09-28 07:03:05.613852: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcurand.so.10 2021-09-28 07:03:05.625022: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcusolver.so.11 2021-09-28 07:03:05.628477: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcusparse.so.11 2021-09-28 07:03:05.629806: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudnn.so.8 2021-09-28 07:03:05.633270: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-09-28 07:03:05.639817: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2021-09-28 07:03:05.642759: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1871] Adding visible gpu devices: 0, 1 2021-09-28 07:03:14.784927: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2021-09-28 07:03:14.786213: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1258] Device interconnect StreamExecutor with strength 1 edge matrix: 2021-09-28 07:03:14.786232: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1264] 2021-09-28 07:03:14.860397: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 3393245000 Hz ColabFold on Linux homooligomer: '1' total_length: '59' working_directory: 'prediction_test_a5e17' running mmseqs2 0%| | 0/5 [elapsed: 00:00 remaining: ?] model_1_ptm_seed_0 recycles:3 tol:0.06 pLDDT:96.25 pTMscore:0.76 model_2_ptm_seed_0 recycles:3 tol:0.12 pLDDT:96.98 pTMscore:0.76 model_3_ptm_seed_0 recycles:3 tol:0.08 pLDDT:97.48 pTMscore:0.78 model_4_ptm_seed_0 recycles:3 tol:0.12 pLDDT:96.54 pTMscore:0.77 model_5_ptm_seed_0 recycles:3 tol:0.18 pLDDT:96.27 pTMscore:0.78 model rank based on pLDDT rank_1_model_3_ptm_seed_0 pLDDT:97.48 rank_2_model_2_ptm_seed_0 pLDDT:96.98 rank_3_model_4_ptm_seed_0 pLDDT:96.54 rank_4_model_5_ptm_seed_0 pLDDT:96.27 rank_5_model_1_ptm_seed_0 pLDDT:96.25 0%| | 0/5 [elapsed: 00:00 remaining: ?] Traceback (most recent call last): File "runner.py", line 758, in relaxed_pdb_lines, _, _ = amber_relaxer.process(prot=outs[key]["unrelaxed_protein"]) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/relax/relax.py", line 62, in process max_outer_iterations=self._max_outer_iterations) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/relax/amber_minimize.py", line 482, in run_pipeline ret.update(get_violation_metrics(prot)) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/relax/amber_minimize.py", line 356, in get_violation_metrics structural_violations, struct_metrics = find_violations(prot) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/relax/amber_minimize.py", line 343, in find_violations "clash_overlap_tolerance": 1.5, # Taken from model config. File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/model/folding.py", line 758, in find_structural_violations atomtype_radius, batch['residx_atom14_to_atom37']) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/model/utils.py", line 39, in batched_gather return take_fn(params, indices) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/model/utils.py", line 36, in take_fn = lambda p, i: jnp.take(p, i, axis=axis) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/_src/numpy/lax_numpy.py", line 5384, in take mode) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/_src/traceback_util.py", line 162, in reraise_with_filtered_traceback return fun(*args, **kwargs) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/_src/api.py", line 414, in cache_miss donated_invars=donated_invars, inline=inline) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/core.py", line 1618, in bind return call_bind(self, fun, *args, **params) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/core.py", line 1609, in call_bind outs = primitive.process(top_trace, fun, tracers, params) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/core.py", line 1621, in process return trace.process_call(self, fun, tracers, params) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/core.py", line 615, in process_call return primitive.impl(f, *tracers, **params) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/interpreters/xla.py", line 623, in _xla_call_impl *unsafe_map(arg_spec, args)) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/linear_util.py", line 262, in memoized_fun ans = call(fun, *args) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/interpreters/xla.py", line 694, in _xla_callable return lower_xla_callable(fun, device, backend, name, donated_invars, *arg_specs).compile().unsafe_call File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/interpreters/xla.py", line 703, in lower_xla_callable fun, abstract_args, pe.debug_info_final(fun, "jit")) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/interpreters/partial_eval.py", line 1522, in trace_to_jaxpr_final jaxpr, out_avals, consts = trace_to_subjaxpr_dynamic(fun, main, in_avals) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/interpreters/partial_eval.py", line 1500, in trace_to_subjaxpr_dynamic ans = fun.call_wrapped(*in_tracers) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/linear_util.py", line 166, in call_wrapped ans = self.f(*args, **dict(self.params, **kwargs)) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/_src/numpy/lax_numpy.py", line 5390, in _take _check_arraylike("take", a) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/_src/numpy/lax_numpy.py", line 559, in _check_arraylike raise TypeError(msg.format(fun_name, type(arg), pos)) jax._src.traceback_util.UnfilteredStackTrace: TypeError: take requires ndarray or scalar arguments, got <class 'list'> at position 0.

The stack trace below excludes JAX-internal frames. The preceding is the original exception that occurred, unmodified.

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "runner.py", line 758, in relaxed_pdb_lines, _, _ = amber_relaxer.process(prot=outs[key]["unrelaxed_protein"]) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/relax/relax.py", line 62, in process max_outer_iterations=self._max_outer_iterations) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/relax/amber_minimize.py", line 482, in run_pipeline ret.update(get_violation_metrics(prot)) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/relax/amber_minimize.py", line 356, in get_violation_metrics structural_violations, struct_metrics = find_violations(prot) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/relax/amber_minimize.py", line 343, in find_violations "clash_overlap_tolerance": 1.5, # Taken from model config. File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/model/folding.py", line 758, in find_structural_violations atomtype_radius, batch['residx_atom14_to_atom37']) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/model/utils.py", line 39, in batched_gather return take_fn(params, indices) File "/usr/local/alphafold/localcolabfold/colabfold/alphafold/model/utils.py", line 36, in take_fn = lambda p, i: jnp.take(p, i, axis=axis) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/_src/numpy/lax_numpy.py", line 5384, in take mode) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/_src/numpy/lax_numpy.py", line 5390, in _take _check_arraylike("take", a) File "/usr/local/alphafold/localcolabfold/colabfold/colabfold-conda/lib/python3.7/site-packages/jax/_src/numpy/lax_numpy.py", line 559, in _check_arraylike raise TypeError(msg.format(fun_name, type(arg), pos)) TypeError: take requires ndarray or scalar arguments, got <class 'list'> at position 0.

Any idea of what could be the problem? Thank you!

opened by lucajovine 13
jaxlib version 0.1.74 required
Hi, thank you for a great effort. I have a problem after installing on Linux CentOS with message related to the jaxlib version:

ValueError: jaxlib is version 0.1.72, but this version of jax requires version 0.1.74.

And if I try to run update script it returns error as well:

bash-4.2$ pwd /hpc/shared/colabfold_batch bash-4.2$ ls bin colabfold-conda conda stereo_chemical_props.txt update_linux.sh bash-4.2$ ./update_linux.sh Error! colabfold-conda directory is not present in .
opened by andzajan 11
LocalColabFold

While installing LocalColabFold in the workstation with Ubuntu19.10, I get this message below at the end:

install_colabbatch_linux.sh: line 50: cd: /home/dilraj/Desktop/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold: No such file or directory sed: can't read batch.py: No such file or directory install_colabbatch_linux.sh: line 52: cd: /home/dilraj/Desktop/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/alphafold/relax: No such file or directory sed: can't read amber_minimize.py: No such file or directory

Here is a complete log file from the installation AF2_install.txt

When I try to execute "colabfold_batch --help", I get this: ./colabfold_batch: 7: /home/dilraj/Desktop/colabfold_batch/colabfold-conda/bin/colabfold_batch: not found

Is the installation not complete? I will be grateful if you can provide me pointers as to what I could do to fix this issue. Please let me know if you need any further information from my end.

Best, Dilraj

opened by Dilrajl 10
how to unleash my full GPU power

Hi, there. I have 2 RTX2080Ti(11G) GPUs with CUDA-11.2, when i input a sequence less than 1000 amino acids, it can run normally but only one of my GPU works. When i tried a ~1200 sequence or complex it will throw 'ResourceExhausted' error. So the problem is how do i let all my GPUs work and be able to calculate larger sequence or complex?

opened by WJluluxiu 10
Can't finish bash install_colabbatch_M1mac.sh

Hello,

There's an error poping up when trying to bash this step. I have attached the screenshots underneath. Basically, it just shows I didn't install miniforge, which I just did.

opened by LeeCW89 8
multimer model error:config_dict.py", line 903, in __getitem__ field = self._fields[key] KeyError: 'data'

Hi,

I am able to predict a protein file but when I try the multimer model, I use: /home/qiushi/localcolabfold/colabfold_batch/bin/colabfold_batch \ > --amber \ > --templates \ > --num-recycle 1 \ > --model-type AlphaFold2-multimer \ > /home/qiushi/RESC6/complex.fasta \ > /home/qiushi/RESC6/complexdir

I got this error:

If you require more MSAs, please host your own API and pass it to --host-url 2022-03-06 18:21:09,433 Running colabfold 1.2.0 (46ae46946d771af1745d55c2c40050e8f54f5e17) 2022-03-06 18:21:09,434 Found 8 citations for tools or databases 2022-03-06 18:21:16,481 Query 1/2: T1084 (length 73) 2022-03-06 18:21:17,725 Sleeping for 9s. Reason: PENDING COMPLETE: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 150/150 [elapsed: 00:12 remaining: 00:00]2022-03-06 18:21:29,021 Sequence 0 found no templates 2022-03-06 18:21:29,021 Running model_3 Traceback (most recent call last): File "/home/qiushi/localcolabfold/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/ml_collections/config_dict/config_dict.py", line 903, in getitem field = self._fields[key] KeyError: 'data' During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/qiushi/localcolabfold/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/ml_collections/config_dict/config_dict.py", line 827, in getattr return self[attribute] File "/home/qiushi/localcolabfold/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/ml_collections/config_dict/config_dict.py", line 909, in getitem raise KeyError(self._generate_did_you_mean_message(key, str(e))) KeyError: "'data'" During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/qiushi/localcolabfold/colabfold_batch/colabfold-conda/bin/colabfold_batch", line 8, in sys.exit(main()) File "/home/qiushi/localcolabfold/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold/batch.py", line 1386, in main save_pair_representations=args.save_pair_representations, File "/home/qiushi/localcolabfold/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold/batch.py", line 1102, in run prediction_callback=prediction_callback, File "/home/qiushi/localcolabfold/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold/batch.py", line 198, in predict_structure use_templates, File "/home/qiushi/localcolabfold/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold/batch.py", line 132, in batch_input eval_cfg = model_config.data.eval File "/home/qiushi/localcolabfold/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/ml_collections/config_dict/config_dict.py", line 829, in getattr raise AttributeError(e) AttributeError: "'data'"

any idea how to make it work?

THanks

opened by liuqs1990 8
running localcolabfold without network access

Hello,

I woould like to run localcolabfold on a cluster which compute nodes does not have internet access.

problem is one of the first step is to try to download pickled msa info from https://a3m.mmseqs.com. that of course fail is there a way to have a local non network option ?

regards

Eric

opened by EricDeveaud 7
Question: Installation problems. Numpy?
Installation Problems? I had several issues while installing it. The first was that because I have spaces in some of my parent directories, the installation code could not point to the correct directories. I fixed this by changing the CURRENTPATH to '.'

I then was able to finish the installation, but ran into an issue with running collabfold_batch where packages seem incompatible.

Computational environment

OS: $ uname -m x86_64

To Reproduce Steps to reproduce the behavior:

My directory setup looks like: Parent_dir ->colabfold_batch .....-update_intelmac.sh .....->colabfold_batch ..........->bin ..........->colabfold-conda ..........->conda

I navigate to the directory Parent_dir/colabfold_batch/colabfold_batch

I then execute the following line and am met with this error message

colabfold_batch --help Traceback (most recent call last): File "/Users/beallma/miniconda3/bin/colabfold_batch", line 5, in <module> from colabfold.batch import main File "/Users/beallma/miniconda3/lib/python3.8/site-packages/colabfold/batch.py", line 33, in <module> from alphafold.common import protein, residue_constants File "/Users/beallma/miniconda3/lib/python3.8/site-packages/alphafold/common/protein.py", line 19, in <module> from alphafold.common import residue_constants File "/Users/beallma/miniconda3/lib/python3.8/site-packages/alphafold/common/residue_constants.py", line 774, in <module> restype_atom37_to_rigid_group = np.zeros([21, 37], dtype=np.int) File "/Users/beallma/miniconda3/lib/python3.8/site-packages/numpy/__init__.py", line 284, in __getattr__ raise AttributeError("module {!r} has no attribute " AttributeError: module 'numpy' has no attribute 'int

Expected behavior When I run collabfold_batch I expect to be directed to the help menu so I can see the parameterlist. Thank you for any help you can provide! I am looking forward to running this program locally because of the constraints on Google Colab. This seems like it will be a great resource.
opened by allmanbrent 0
How to understand squeue convergence and Sequence identity to query

Dear authors hello I finished a work based on localcolabfold , it's amazing that it's so fast ，but I have a question, in output directory I found 1_coverage.png, in this picture, how to understand “squeue converage and Sequence identity to query”

opened by zhoujingyu13687306871 0
Convert to core_ml format?

Sorry, everyone, I am new to big projects such as alpha fold, and I am also a beginner at ml. Though, I wonder if it is possible to convert the alpha fold model to apple's core_ml model and take advantage of the headwear acceleration in both the intel and m1 models.

opened by rnogy 0

Getting pxtas cuda mismatch warning

What is your question? Getting this error:

2022-12-16 18:31:30.311235: W external/org_tensorflow/tensorflow/compiler/xla/service/gpu/nvptx_compiler.cc:497] The NVIDIA driver's CUDA version is 11.
0 which is older than the ptxas CUDA version (11.6.124). Because the driver is older than the ptxas version, XLA is disabling parallel compilation, whic
h may slow down compilation. You should update your NVIDIA driver or use the NVIDIA-provided CUDA forward compatibility packages.

But I have 11.6 installed? I think this also causes me to be unable to use GPU-accelerated AMBER relaxation.

Computational environment Output of gcc --version is

gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

Output of /usr/local/cuda/bin/nvcc --version is

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Tue_Mar__8_18:18:20_PST_2022
Cuda compilation tools, release 11.6, V11.6.124
Build cuda_11.6.r11.6/compiler.31057947_0

opened by Abhishaike 3

Question:Failed to establish connection: HTTPSConnectionPool
Hello,

I am using localcolabfold and I am experiencing for the first time failure in establishing connection with the API, after a couple of weeks not using localcolabfold. I've been using it for a long time now without experiencing this issue. You will find below what it systematically returns for all my jobs. Thank you in advance for your help:

Module GCCcore/10.2.0, zlib/1.2.11, binutils/2.35, numactl/2.0.13, XZ/5.2.5, libxml2/2.9.10, libpciaccess/0.16, hwloc/2.2.0, libevent/2.1.12, UCX/1.9.0, libfabric/1.11.0, PMIx/3.1.5, GCC/10.2.0, CUDA/11.3.1, OpenMPI/4.0.5, GCC/10.2.0, OpenMPI/4.0.5, CUDA/11.3.1, OpenMPI/4.0.5 unloaded. Module GCCcore/10.2.0zlib/1.2.11binutils/2.35numactl/2.0.13XZ/5.2.5libxml2/2.9.10libpciaccess/0.16hwloc/2.2.0libevent/2.1.12UCX/1.9.0libfabric/1.11.0PMIx/3.1.5GCC/10.2.0CUDA/11.3.1OpenMPI/4.0.5GCC/10.2.0OpenMPI/4.0.5CUDA/11.3.1OpenMPI/4.0.5 loaded. sbatch run_colabfold_AF2Mv2_unpaired_paired_Human_Barabasi_top_signi_predicted_missing_links_dms.sh 4 Submitted batch job 31762849 WARNING: You are welcome to use the default MSA server, however keep in mind that it's a limited shared resource only capable of processing a few thousand MSAs per day. Please submit jobs only from a single IP address. We reserve the right to limit access to the server case-by-case when usage exceeds fair use.

If you require more MSAs:

You can precompute all MSAs with colabfold_search or

You can host your own API and pass it to --host-url 2022-12-10 12:23:38,061 Running colabfold 1.3.0 (7ebcbe62e8d88400b0e75aa0878dce2ff3a6c71f) 2022-12-10 12:23:38,929 --max-msa can not be used in combination with AlphaFold2-multimer (--max-msa ignored) 2022-12-10 12:23:41,743 Found 7 citations for tools or databases 2022-12-10 12:23:45,211 Query 1/1: O60674_P08581 (length 2522)

0%| | 0/300 [elapsed: 00:00 remaining: ?] SUBMIT: 0%| | 0/300 [elapsed: 00:00 remaining: ?] SUBMIT: 0%| | 0/300 [elapsed: 02:07 remaining: ?] 2022-12-10 12:25:52,518 Could not get MSA/templates for O60674_P08581: HTTPSConnectionPool(host='api.colabfold.com', port=443): Max retries exceeded with url: /ticket/msa (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x2b0fd6a80790>: Failed to establish a new connection: [Errno 110] Connection timed out')) Traceback (most recent call last): File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/connection.py", line 175, in _new_conn (self._dns_host, self.port), self.timeout, **extra_kw File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/util/connection.py", line 95, in create_connection raise err File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/util/connection.py", line 85, in create_connection sock.connect(sa) TimeoutError: [Errno 110] Connection timed out

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/connectionpool.py", line 710, in urlopen chunked=chunked, File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/connectionpool.py", line 386, in _make_request self._validate_conn(conn) File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/connectionpool.py", line 1042, in _validate_conn conn.connect() File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/connection.py", line 358, in connect self.sock = conn = self._new_conn() File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/connection.py", line 187, in _new_conn self, "Failed to establish a new connection: %s" % e urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x2b0fd6a80790>: Failed to establish a new connection: [Errno 110] Connection timed out

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/requests/adapters.py", line 499, in send timeout=timeout, File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/connectionpool.py", line 788, in urlopen method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2] File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/urllib3/util/retry.py", line 592, in increment raise MaxRetryError(_pool, url, error or ResponseError(cause)) urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='api.colabfold.com', port=443): Max retries exceeded with url: /ticket/msa (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x2b0fd6a80790>: Failed to establish a new connection: [Errno 110] Connection timed out'))

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold/batch.py", line 1429, in run host_url, File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold/batch.py", line 860, in get_msa_and_templates host_url=host_url, File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold/colabfold.py", line 140, in run_mmseqs2 out = submit(seqs_unique, mode, N) File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold/colabfold.py", line 80, in submit res = requests.post(f'{host_url}/{submission_endpoint}', data={'q':query,'mode': mode}) File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/requests/api.py", line 115, in post return request("post", url, data=data, json=json, **kwargs) File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/requests/api.py", line 59, in request return session.request(method=method, url=url, **kwargs) File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/requests/sessions.py", line 587, in request resp = self.send(prep, **send_kwargs) File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/requests/sessions.py", line 701, in send r = adapter.send(request, **kwargs) File "/lustre/ssd/ws/iabdelha-IA-AF-SSD-workspace/alphafold/data/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/requests/adapters.py", line 565, in send raise ConnectionError(e, request=request) requests.exceptions.ConnectionError: HTTPSConnectionPool(host='api.colabfold.com', port=443): Max retries exceeded with url: /ticket/msa (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x2b0fd6a80790>: Failed to establish a new connection: [Errno 110] Connection timed out')) 2022-12-10 12:25:52,525 Done
opened by IlyesAbdelhamid 1

Question: Is localcolabfold working on MacOS with Intel now?

What is your question? Describe your question here.

Computational environment

OS: macOS

To Reproduce I am trying to run: $ colabfold_batch --amber --templates --num-recycle 3 --use-gpu-relax $fasta_file ./outputs

Expected behavior But I get the following error:

2022-12-09 15:44:46,834 Running colabfold 1.3.0 (5cadd359d5f878cee88db2d4555826a5e3eea24f)
Traceback (most recent call last):
  File "/Users/jakub/colabfold_batch/colabfold-conda/bin/colabfold_batch", line 8, in <module>
    sys.exit(main())
  File "/Users/jakub/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/colabfold/batch.py", line 1735, in main
    from jax.lib import xla_bridge
  File "/Users/jakub/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/jax/__init__.py", line 35, in <module>
    from jax import config as _config_module
  File "/Users/jakub/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/jax/config.py", line 17, in <module>
    from jax._src.config import config  # noqa: F401
  File "/Users/jakub/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/jax/_src/config.py", line 27, in <module>
    from jax._src import lib
  File "/Users/jakub/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/jax/_src/lib/__init__.py", line 77, in <module>
    minimum_jaxlib_version=jax.version._minimum_jaxlib_version)
  File "/Users/jakub/colabfold_batch/colabfold-conda/lib/python3.7/site-packages/jax/_src/lib/__init__.py", line 63, in check_jaxlib_version
    raise RuntimeError(msg)
RuntimeError: jaxlib is version 0.3.10, but this version of jax requires version >= 0.3.22.

I tried to uninstall colabfold and install again, tried to follow the steps of how "to fix this issue, please upgrade your jax and jaxlib", but the line:

${COLABFOLDDIR}/colabfold-conda/bin/python3.7 -m pip install https://storage.googleapis.com/jax-releases/cuda11/jaxlib-0.3.25+cuda11.cudnn82-cp37-cp37m-manylinux2014_x86_64.whl

does not work on macos. I also tried to install jax via pip and it says that my version is 0.3.25. Do you maybe know what could be the problem?

opened by jakubotreba 2

Releases(v1.4.0)

v1.4.0(Jun 18, 2022)
Update to be compatible with jax == 0.3.13 and jaxlib==0.3.10(+cuda).

Source code(tar.gz)
Source code(zip)
v1.3.0(Apr 11, 2022)
Add dependency of kalign 3.3.2 for M1 Mac (https://github.com/YoshitakaMo/localcolabfold/commit/6cd1a38a32f654c8cef06d4cdd1c353ce62960b7)

Use https instead of git for M1 Mac (https://github.com/YoshitakaMo/localcolabfold/commit/0ad333ffa24a9896361a54d8d2e18a493ec68184, https://github.com/YoshitakaMo/localcolabfold/issues/78)

Use 'Agg' for non-GUI backend (https://github.com/YoshitakaMo/localcolabfold/commit/f7f06d94952106e7b819e38420ed19052e3561d2)

Source code(tar.gz)
Source code(zip)
v1.2.1(Feb 8, 2022)
Fix missing pip install scipy for Apple M1 mac (issue #55)

Apply the GPU relaxation patch again for update_linux.sh when updating alphafold-colabfold

Source code(tar.gz)
Source code(zip)
v1.2.0(Dec 21, 2021)
Compatible with the latest pip installable colabfold that runs locally.

Add update scripts.

Source code(tar.gz)
Source code(zip)
v1.2.0-alpha(Dec 4, 2021)
Compatible with the latest pip installable colabfold that runs locally.

Source code(tar.gz)
Source code(zip)
v1.0.0(Nov 13, 2021)

LocalColabFold compatible with AlphaFold2_advanced on Nov.5, 2021.
Source code(tar.gz)
Source code(zip)