Alphapulldown

There is only a single fix: generating features with mmseqs2 previously did not work because of 399
Many thanks to [kashyapchhatbar](https://github.com/kashyapchhatbar) for finding this out and reporting!

1. Merged updated manual, credits to gilep
2. Fixed bug: predictions for homo-oligomers using whole ranges.
3. `ranking_debug.json`: save iptm for multimers OR ptm for monomers.
4. Added `modelcif` dependency to the `pulldown.docker` file and github actions.
5. Used system.entities instead of system.target_entities for `convert_to_modelcif.py`.
6. Added tests for `modelcif` and `run_multimer_jobs.py`.
7. Used the correct docker image from `kosinskilab` for the analysis pipeline.

1. Removed dependencies from the result pickles.
2. Fixed the "key error" while running the create_notebook.py. Thanks for the help from DimaMolod and the report from gebauer
3. Beautified and updated the manual. Thanks for the work from gilep . The updated manual is close to be finished and will be merged soon after the release once it's proof-read.
4. Updated the singularity image of the analysis pipeline so that it handles the exceptions caused by monomeric models.

You could download this version by running pip install alphapulldown==2.0.0b3

**Note**: please download the new singularity image: [alpha-analysis.sif](https://www.embl-hamburg.de/AlphaPulldown/downloads/alpha-analysis.sif) . Since all the dependencies in the result files are removed in this version, there is no need to build two singularity images for jax version 0.3 and jax version 0.4, as in the previous versions.

If you have created models using the versions prior to the alphapulldown==2.0.0b3, please rerun the run_multimer_jobs.py before using the updated the singularity image. The rerun will be quick as only the result pickles are to be changed.

New features added:
1. Added calculation of average PAE value of interface residues to analysis_pipeline
2. Added calculation of average plDDT value of interface residues to analysis_pipeline
3. Added calculation of binding energy via pyRosetta value of interfaces to analysis_pipeline
4. Updated pyTest thanks for the help from DimaMolod

Bugs fixed:
1. Fixed crashes caused by monomer 312
2. Fixed wrong contents in the plotted PAE images 312
3. Fixed wrong calculation of iptm-ptm and iptm scores when using padding mode 312

Notice:
Apart from installing the beta version of alphapulldown from pypi, using pip install alphapulldown==2.0.0b2, please re-download the alpha-analysis singularity images again this time.
If your results are from AlphaPulldown prior to version 1.0.0, please use the link: [`alpha-analysis_jax_0.3.sif`](https://www.embl-hamburg.de/AlphaPulldown/downloads/alpha-analysis_jax_0.3.sif).
If your results are from AlphaPulldown with version >=1.0.0, please use the link: [`alpha-analysis_jax_0.4.sif`](https://www.embl-hamburg.de/AlphaPulldown/downloads/alpha-analysis_jax_0.4.sif).

New features added:
1. Refactorised the codes; introduced folding_backend 303 thanks for the help from maurerv and DimaMolod
2. Allow the user to pad input matrices to desired number of MSAs and desired number of residues to speed up overall modelling process and avoid unnecessary re-compiling of AlphaFold neural network.
3. New way of modelling with customised structure templates without the need of recalculating the features again. 268
4. Separated post-modelling processes from prediction process 297 by DimaMolod
5. Supports full mmseqs2 mode i.e. without the need of local structural template database when using mmseqs mode 233

Bugs fixed:
1. Fixed incorrect colour scheme when ploting structures in jupyter-notebook 304 thanks for the help from gchojnowski and report from gilep
2. Fixed operands broadcast error when the features are created by mmseqs2 287 thanks for the report from Qrouger
3. Updated alpha-analysis.sif to avoid crashes when no model satisfies the cutoff value 307
4. Fix the config.cfg to avoid installing tensorflow versions that are not compatible with GPUs without latest CUDA. 298 Thanks for the help from kashyapchhatbar

Notice:
Apart from installing the beta version of alphapulldown from pypi, using pip install alphapulldown==2.0.0b1, please re-download the alpha-analysis singularity images again.
If your results are from AlphaPulldown prior to version 1.0.0, please use the link: [`alpha-analysis_jax_0.3.sif`](https://www.embl-hamburg.de/AlphaPulldown/downloads/alpha-analysis_jax_0.3.sif).
If your results are from AlphaPulldown with version >=1.0.0, please use the link: [`alpha-analysis_jax_0.4.sif`](https://www.embl-hamburg.de/AlphaPulldown/downloads/alpha-analysis_jax_0.4.sif).