Example PyMol API output
========================

Here are shown the output generated for the cdk2.fasta alignment file in the examples directory using the PyMol API.

.. code-block:: python
    
    from Polyphony.Pymol import Pymol_Viz
    cdk2 = Pymol_Viz("cdk2.fasta","cdk2")
    
    
.. code-block:: python

    cdk2.colour_by_variability()

.. image:: images/colour_by_variability.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.colour_by_variability

.. code-block:: python

    cdk2.colour_by_average_bfactor()


.. image:: images/colour_by_average_bfactor.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.colour_by_average_bfactor

.. code-block:: python

    cdk2.colour_by_seq_variability()


.. image:: images/colour_by_seq_variability.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.colour_by_seq_variability
    
.. code-block:: python

    cdk2.colour_by_Ramachandran_region()


.. image:: images/colour_by_Ramachandran_region.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.colour_by_Ramachandran_region
    
.. code-block:: python

    cdk2.colour_by_contacts(type="crystal_contacts")


.. image:: images/colour_by_contacts.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.colour_by_contacts
    
.. code-block:: python

    cdk2.colour_by_pockets()


.. image:: images/colour_by_pockets.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.colour_by_pockets
    
.. code-block:: python

    cdk2.colour_by_druggable_pockets()


.. image:: images/colour_by_druggable_pockets.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.colour_by_druggable_pockets
        
.. code-block:: python

    cdk2.colour_by_pca(max_pc_chains_to_ignore=15, components=[0])


.. image:: images/colour_by_pca_plot.png
    :scale: 40 %
    :align: center


.. image:: images/colour_by_pca.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.colour_by_pca


.. code-block:: python

    cdk2.colour_conserved_segments(20, separation=50)


.. image:: images/colour_conserved_segments.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.colour_conserved_segments
        

Show the 20 residue pairs, separated by at least 50 residues, with most correlated backbone conformations.

.. code-block:: python

    cdk2.show_correlated_backbones(20, separation=50)


.. image:: images/show_correlated_backbones.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.show_correlated_backbones
        

Show the 50 residue pairs, separated by at least 5 residues, with most correlated side-chain conformations.

.. code-block:: python

    cdk2.show_correlated_sidechains(50, separation=5)


.. image:: images/show_correlated_sidechains.png
    :scale: 40 %
    :align: center

.. automethod:: Polyphony.Pymol.Pymol_Viz.show_correlated_sidechains
        
Show backbone regions and sidechains that change conformation when cyclin is bound to cdk2

.. code-block:: python

    from Polyphony.Pymol import Pymol_Viz
    cdk2 = Pymol_Viz("clust_1H26_A_90.fasta","cdk2")
    #
    # group by Piccolo annotated protein-protein interactions
    groups = cdk2.group_biggest_clusters(property="ppi")
    active = groups[0]+groups[1]
    inactive = groups[2]
    #
    # default structure is without cyclin bound
    cdk2.colour_by_amplification(property="backbone", groups=[active,inactive])
    cdk2.colour_by_amplification(property="sidechain", groups=[active,inactive])
    #
    # load structure representative of cyclin bound state
    active_rep = cdk2.get_representative_structure([active])
    cdk2.load_structures([active_rep])
    cdk2.colour_by_amplification(property="backbone", groups=[active,inactive], chain_id=active_rep)
    cdk2.colour_by_amplification(property="sidechain", groups=[active,inactive], chain_id=active_rep)


.. image:: images/active_inactive.png
    :scale: 40 %
    :align: center
    
Do similar for p38, after clustering by backbone conformation

.. code-block:: python

    # Read in alignment
    p38 = Pymol_Viz("../p38/clust_1A9U_A_90.fasta","p38")
    # Cluster by backbone conformation in 2 largest groups [0,1] and then into largest subgroups [2,3] and [4,5], [6] contains outliers
    p38_groups = p38.group_biggest_clusters(3)
    p38_group_names = p38.ids_for_groups(p38_groups)
    p38_b1 = p38_groups[0]
    p38_b2 = p38_groups[1]
    p38_b11 = p38_groups[2]
    p38_b12 = p38_groups[3]
    p38_b21 = p38_groups[4]
    p38_b22 = p38_groups[5]
    # Load representative structure (most ordered residues) for each group into PyMol
    p38_b1_rep = p38.get_representative_structure([p38_b1])
    p38_b2_rep = p38.get_representative_structure([p38_b2])
    p38_b11_rep = p38.get_representative_structure([p38_b11])
    p38_b12_rep = p38.get_representative_structure([p38_b12])
    p38_b21_rep = p38.get_representative_structure([p38_b21])
    p38_b22_rep = p38.get_representative_structure([p38_b22])
    # load representative structure aligned to residues 127-144 for consistency with cdk2 example
    p38.load_structures([p38_b1_rep,p38_b2_rep,p38_b11_rep,p38_b12_rep,p38_b21_rep,p38_b22_rep], segment=(127,144))
    # Colour residues by amplified changes between subgroups b21 and b22
    p38.colour_by_amplification(property="backbone",groups=[p38_b21,p38_b22],chain_id=p38_b22_rep)
    p38.colour_by_amplification(property="backbone",groups=[p38_b21,p38_b22],chain_id=p38_b21_rep)
    p38.colour_by_amplification(property="sidechain",groups=[p38_b21,p38_b22],chain_id=p38_b21_rep)
    p38.colour_by_amplification(property="sidechain",groups=[p38_b21,p38_b22],chain_id=p38_b22_rep)


.. image:: images/p38_b21_b22.png
    :scale: 40 %
    :align: center