A package for making graph representations of proteinstructures.
Project description
# protein-graph
Computes a molecular graph for protein structures.
## why?
Proteins fold into 3D structures, and have a natural graph representation: amino acids are nodes, and biochemical interactions are edges.
I wrote this package as part of a larger effort to do graph convolutional neural networks on protein structures (represented as graphs). However, that's not the only thing I can foresee doing with this.
One may be interested in the topology of proteins across species and over evolutionary time. This package can aid in answering this question.
## how do I install this package?
Currently only `pip`-installable:
```bash
$ pip install proteingraph
```
## how do I use this package?
This package assumes that you have a standard protein structure file (e.g. a PDB file). This may be a file generated after solving the NMR or crystal structure of a protein, or it may be generated from homology modelling.
Once that has been generated, the molecular graph can be generated using Python code.
```python
from proteingraph import ProteinInteractionNetwork
p = ProteinInteractionNetwork('my_model.pdb')
```
Because the `ProteinInteractionNetwork` class inherits from NetworkX's `Graph` class, all methods that `Graph` has are inherited by `ProteinInteractionNetwork`, and it behaves just as a NetworkX graph does.
What this means is that all graph-theoretic metrics (e.g. degree centrality, betweenness centrality etc.) can be computed on the `ProteinInteractionNetwork` object.
See the HIV1 homology model example in the `examples/` directory for a minimal example.
Computes a molecular graph for protein structures.
## why?
Proteins fold into 3D structures, and have a natural graph representation: amino acids are nodes, and biochemical interactions are edges.
I wrote this package as part of a larger effort to do graph convolutional neural networks on protein structures (represented as graphs). However, that's not the only thing I can foresee doing with this.
One may be interested in the topology of proteins across species and over evolutionary time. This package can aid in answering this question.
## how do I install this package?
Currently only `pip`-installable:
```bash
$ pip install proteingraph
```
## how do I use this package?
This package assumes that you have a standard protein structure file (e.g. a PDB file). This may be a file generated after solving the NMR or crystal structure of a protein, or it may be generated from homology modelling.
Once that has been generated, the molecular graph can be generated using Python code.
```python
from proteingraph import ProteinInteractionNetwork
p = ProteinInteractionNetwork('my_model.pdb')
```
Because the `ProteinInteractionNetwork` class inherits from NetworkX's `Graph` class, all methods that `Graph` has are inherited by `ProteinInteractionNetwork`, and it behaves just as a NetworkX graph does.
What this means is that all graph-theoretic metrics (e.g. degree centrality, betweenness centrality etc.) can be computed on the `ProteinInteractionNetwork` object.
See the HIV1 homology model example in the `examples/` directory for a minimal example.
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