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A tool to get structural information about light chain amyloids

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About HMMSTUFF

HMMSTUFF is a tool to help researchers to make the best use of the limited data available about light chain amyloids. Given a light chain amyloid, it tells you if there is a similar chain with experimentally solved structure.

If you use HMMSTUFF in your research, please consider citing:

Installation

Package installation should only take a few minutes with any of these methods (pip, source).

A foldX binary, which can be downloaded from https://foldxsuite.crg.eu/, is required

Installing HMMSTUFF with pip:

We suggest to create a local conda environment where to install chaplin. it can be done with:

conda create -n hmmstuff python=3.7

and activated with

conda activate hmmstuff

or

source activate hmmstuff

Install hmmstuff using

pip install hmmstuff

The procedure will install hmmstuff in your computer.

Installing chaplin from source:

If you want to install hmmstuff from this repository, you need to install the dependencies first.

pip install numpy scikit-learn transformers pomegranate==0.14.0

Finally, you can clone the repository with the following command:

git clone https://github.com/grogdrinker/hmmstuff/

Using chaplin into a python script

the pip installation will install a python library that is directly usable (at least on linux and mac. Most probably on windows as well if you use a conda environemnt).

HMMSTUFF can be imported as a python module

from HMMSTUFF.HMMSTUFF import HMMSTUFF # import the library
# put your input sequences in a dictionary
sequences = {"seq1":"AVSVALGQTVRITCQGDSLRSYSASWYEEKPGQAPVLVIFRAAAARFSGSSSGNTASLTITGAQAEDEADYYCNSRDSSANHQAAAAVFGGGTKLTV",
             "seq2":"AVSVALGQTVRITCQGDSLRSYSASWYQQKPGQAPVLVIFRAAAARFSGSSSGNTASLTITGAQAEDEADYYCNSRDSSANHVFGGGTKLTV",
             "seq3":"SELTQDPAVSVALGQTVRITCQGDSLRSYYASWYQQKSGQAPVLVIYSYNNRPSGIPDRFSGSNSGNTASLTITGAQAEDEADYYCNSRDSSGHHLVFGGGTKLTVLGQPKAAPS",
             "seq4":"MKYLLPTAAAGLLL"} 

hmmstuff = HMMSTUFF() # create the main HMMSTUFF object

# to get a fast evaluation of the sequences, run:
results = hmmstuff.evaluate_sequences(sequences)
# it is gonna tell you, for each sequence, if a structure can be created or not.
# It will also provide a dictionary of results with information: the best template (even if not good enouth to run a structure), the score of the HMM and an alignment with the best template

# to get an evaluation of the sequences, and eventually run the structure prediction, run:
results = hmmstuff.predict_structures(sequences,foldx_bin="Your/FoldX/Bin/path",folder_out_pdbs="Your/output/path/")
#remember that for this study, foldX 4 has been used and a Rotabase.txt file is required to be found in the same folder of the FoldX binary. The code might work with FoldX5 as well, but it has not been tested.

Help

For bug reports, features addition and technical questions please contact gabriele.orlando@kuleuven.be

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