Helix surface

After generating LIPS results for protein 1xqf chain A, we can make the most of them to annotate the protein at both surface and per-residue levels. In this tutorial, we show how we can use TMKit annotate each residue with helix surfaces of LIPS results that it belongs to.

Reminder of data

Please make sure that the build-in example dataset has been downloaded before you walk through the tutorial.

Example usage

We can first read the file of a helix surface ID id=1 using the following code. Please remember that we have put the results for protein 1xqf chain A in folder ./data/lips/ as in the last tutorial.

Code

import tmkit as tmk

df = tmk.feature.read_helix_surf(
    fp='./data/lips/',
    prot_name='1xqf',
    file_chain='A',
    id=1,
)
print(df)

Output

     aa_ids aa_names  lipos   ents  surf
0         2        V  0.026  1.158     1
1         5        K  0.804  6.798     1
2         6        A  0.573  4.896     1
3         9        A  0.697  4.852     1
4        12        M  0.973  3.694     1
..      ...      ...    ...    ...   ...
150     352        L  0.828  4.846     1
151     355        L  0.688  4.551     1
152     356        T  0.535  3.724     1
153     359        L  0.984  3.276     1
154     362        P  0.615  4.539     1

[155 rows x 5 columns]

The output is a dataframe containing 5 columns, as shown below.

Attribute	Description
aa_ids	amino acid ID
aa_names	amino acid name
lipos	the LIPOS score for an amino acid
ents	entropy
surf	the helix surface ID

If we want to annotate all amino acids with the helix surface IDs, we need to use all 7 surface data. In TMKit, we can do it this way.

Code

import tmkit as tmk

aa_surf_rank, _, _, _ = tmk.feature.read(
    fp='./data/lips/',
    prot_name='1xqf',
    file_chain='A',
)
print(aa_surf_rank)

Output

{1: 4, 4: 0, 5: 1, 8: 4, 11: 0, ..., 357: 2, 360: 5}

Actually, we can use TMKit to check the summary about all 7 surfaces, which shows the entropy, the LIPOS score, and the final LIPS score at the surface level.

Code

import tmkit as tmk

df = tmk.feature.read_helix_all_surf(
    fp='./data/lips/',
    prot_name='1xqf',
    file_chain='A',
)
print(df)

Output

   surfs  lipos   ents    lxe
0      5  1.834  4.846  8.889
1      0  1.770  4.912  8.694
2      3  1.729  4.852  8.389
3      1  1.815  4.885  8.865
4      2  1.791  4.749  8.507
5      6  1.777  4.746  8.435
6      4  1.767  4.948  8.741

Attributes

Attribute	Description
prot_name	name of a protein in the prefix of a PDB file name (e.g., 1xqf in 1xqfA.pdb)
file_chain	chain of a protein in the prefix of a PDB file name (e.g., A in 1xqfA.pdb)
fp	path where the LIPS results for a protein are placed
id	surface id, 0-6

See also

Please see here for better understanding the file-naming system.

Output

Please check the output in each vignette above.