kianho / pconpy Goto Github PK

For other users:

1. DSSP executable is not available in the provided ftp server. But I can get it using conda install -c salilab dssp, and the command is mkdssp instead of dssp.
2. from Bio._py3k import StringIO should be removed in python3. Without StringIO, the output can be read as str instead of file.
3. without chain_ids defined residues = get_residues(opts["--pdb"], chain_ids=chain_ids) will throw an error. Just add chain_ids=None.

modify/refactor the necessary code to make it python3 compatible.

Note that opts["--measure"] is set to None by default at runtime, it should be "CA" instead.

$ ./pconpy.py cmap 8.0 -p ../tests/pdb_files/1ubq.pdb -o ./cmap.txt --plaintext -D
{'--dpi': '80',
 '--font-family': 'sans',
 '--font-size': '10',
 '--greyscale': False,
 '--height-inches': '6.0',
 '--mask-thresh': None,
 '--measure': None,
 '--no-colorbar': False,
 '--output': './cmap.txt',
 '--pdb': '../tests/pdb_files/1ubq.pdb',
 '--plaintext': True,
 '--show-frame': False,
 '--symmetric': False,
 '--title': None,
 '--transparent': False,
 '--width-inches': '6.0',
 '--xlabel': 'Residue index',
 '--ylabel': 'Residue index',
 '-D': True,
 '-c': None,
 '<dist>': 8.0,
 'cmap': True,
 'dmap': False,
 'hbmap': False}
Traceback (most recent call last):
  File "./pconpy.py", line 553, in <module>
    symmetric=opts["--symmetric"])
  File "./pconpy.py", line 467, in calc_dist_matrix
    dist = calc_distance(res_a, res_b, measure)
  File "./pconpy.py", line 433, in calc_distance
    raise NotImplementedError
NotImplementedError

The current --plaintext outputs the matrices as dense adjacency vectors. This format is needlessly verbose. Change the output format to graph-style edge tuples, such that tuples of non-contacts are not shown -- (res index 1, res index 2, distance)

see http://google-styleguide.googlecode.com/svn/trunk/pyguide.html?showone=Comments#Comments

users currently need to specify the --symmetric option at the command line to mirror the upper-triangle plot to the lower-triangle.

solution

• change the --symmetric option to --asymmetric so that plots are symmetric by default.

tests reveal that their computation is incorrect, the weighted sum needs to be computed over axis=0 e.g.

weighted_sum = numpy.array(sidechain_atom_coords).sum(axis=0)

Hello, i have two questions hope i get the answers from you

1- first the rule of the sequence alignment is that to extract a chunks of subsequences represents the first sequence

2- and then those alignments are fed to the covariance matrix to extract a matrix called covariance matrix the measures the correlations between each of these alignments with each other

3-from what i understand it that proteins contact map describe the distance matrix as a label , like for example the distance between the first amino acid in the first chain and the first amino acid in the second chain is equal to 200 A, we set a threshold with 8 A so the proteins contact map description for this distance number will be "not in contact" "False" or in binary world "0" is im right with that understanding

My Questions
First
1-what is the rule of the covariance matrix
2- what is the rule of proteins contact map are those the labels of the matrix distances if so what is the rule of the covariance matrix
3- what is the input to the neural network model
A- what is the feature, are those the distance matrix if yes what is the rule of covariance matrix
B- what is the label of these features are Proteins contact map is the labels in (0's and 1's )

Second
1- i want from you kindly to give me a hint or steps which is the first script to use and second and so on cuz i want to cite your paper so i started to inspired from your great work

thanks in advance

A standalone pconpy web-server would allow lab members to use pconpy without the need for the command-line.

Possible solution

This could be implemented in Flask.

Rendering PDF plots of large proteins takes a long time.
E.g. rendering 1mtp.

possible solutions

• is there matplotlib trick to make this more efficient?
• issue a warning to the user

ftp://ftp.cmbi.ru.nl/pub/software/dssp/ not find!!!

Add hydrogen-bond map (or HB-plot, http://en.wikipedia.org/wiki/Protein_contact_map#HB_Plot) functionality.

This requires parsing of the inter-residue hydrogen-bond interaction columns from DSSP output, a feature which isn't currently supported by biopython.

I have implemented this feature and made a pull-request to the official biopython repository (biopython/biopython#464). The feature has been informally accepted but not yet merged.

possible solution

Copy the required code from my biopython contribution into pconpy.py. Then remove it once the pull-request has been formally merged.