quantaosun / dock-md-fep Goto Github PK

In case of the CUDA version error.

CUDA_ERROR_UNSUPPORTED_PTX_VERSION (222)

There are two ways to get rid of this

1. Use nvidia-smi to print out your cuda version. In my case, it is 11.2. Use conda list | grep cudatoolkit to print out the cudatoolkit version, in my case it is 11.7. You see, the difference between the cuda driver and cuatoolkit version is where this problem lies. An easy way to fix this, is to change cudatoolkit to the same 11.2 version. by conda install -c conda-forge cudatoolkit=11.2

2. Alternatively, you could modify the yaml file to change CUDA to OpenCL, if your platform supports OpenCL. However, this might not be as fast as CUDA in terms of utilizing GPU power.

It has been constantly observed, that open babel some times added more H atoms to some complex aromatic structures, for example,
a pyridine was added more H it should, or failed to Kekulize the aromatic ring. In such cases, please use pymol or Maestro to open
the wrong ligand_H.pdb to fix the problem. If Maestro was used, you can just use ProteinPrep to recover the correct aromatic order then save it to overwrite the wrong one.

It should be mentioned that the probability you encounter such an issue is not very high if your small molecule contains not many N atoms in your ring system. All the errors observed has been related to N or O atom that is inside or adjacent to the ring system.

Hi quantao,
Your script is really helpful. Can you provide a local version instead of colab version script? Since GPU resource on colab can not be freely available all the time. Many thanks!

This error will not be encountered unless you use explicit-1000_per_interation_doubled_lambda.yml instead of the default implicit-1000_per_interation_doubled_lambda.yml.

This issue is a reminder to myself, and you are welcome to solve this if you have a better position than me.

This issue is doubted to be related to the PBC setting from Amber files used in OpenMM. The way openMM expected PBC and the way Amber defines PBC might conflict. But I must say, sometimes it just works, and sometimes it does not, so the nature of this error is unclear to me.

One thing for sure is once we switch explicit solvent to implicit, this error is gone.

An possible error has been noticed, still working on it

ValueError                                Traceback (most recent call last)

[<ipython-input-4-7aaef16462be>](https://localhost:8080/#) in <module>
     34   ppdb.to_pdb(path="temp.pdb", records=['ATOM', 'HETATM'], gz=False, append_newline=True)
     35 
---> 36   mol= [m for m in pybel.readfile(filename="temp.pdb", format='pdb')][0]
     37   mol.calccharges
     38   mol.addh()

[/usr/local/lib/python3.8/site-packages/openbabel/pybel.py](https://localhost:8080/#) in readfile(format, filename, opt)
    157             obconversion.AddOption(k, obconversion.INOPTIONS, str(v))
    158     if not formatok:
--> 159         raise ValueError("%s is not a recognised Open Babel format" % format)
    160     if not os.path.isfile(filename):
    161         raise IOError("No such file: '%s'" % filename)

ValueError: pdb is not a recognised Open Babel format

Directly installing the packages from the ipynb file may not work, because many packages have not been updated to the newer python environment. You can work it out yourself but it would take some time to do so, Please use the environment.yml file (which has fixed the python to 3.8.16 for example, but if using colab, the python is up-to-date version maybe 3.11 in April 2024 and cause incompatible issues with other packages) when possible, and it should still work until April 2024.

Also, it is a bit slow even with v100 colab provided to run the simulation, please consider use RTX4090 is recommended when availiable.

Using this workflow on colab is handy but requires installation every time, which is not handy at all. To address this problem, one way is to install the whole workflow locally.

conda create --name Dock-MD-FEP python=3.8
conda activate Dock-MD-FEP
(Dock-MD-FEP)conda install juyter --yes
(Dock-MD-FEP)pip install $everything
(Dock-MD-FEP)conda install $everything
(Dock-MD-FEP) jupyter lab Dock-MD-FEP_local_installation.ipynb

After starting the Dock-MD-FEP_local_installation.ipynb, firstly, we need to import all the packages we have installed, and later you don't have to install those packages again.

In a perfect world, you only need to customise the input cell with a proper PDB id and SMILES to represent the small molecule you need to dock and simulate. All the rest should be run automatically by clicking run them all with one click.

Hi,

I am getting the following error, during the yank step.

AttributeError: 'MBAR' object has no attribute 'getFreeEnergyDifferences'

I am running the program locally