Python bindings around the TM-align code for structural alignment of proteins
Project description
TM-Tools
Python bindings for the TM-align algorithm and code developed by Zhang et al for protein structure comparison.
Installation
From the console, simply run
pip install git+https://github.com/jvkersch/tmtools.git#egg=tmtools
The package supports Python 3.6 and up. You will need a fairly recent version of pip, as well as a C++ compiler that supports C++ 14.
This package supports Linux, macOS, and Windows.
Usage
The function tmtools.tm_align
takes two NumPy arrays with coordinates for the
residues (with shape (N, 3)
) and two sequences of peptide codes, performs the
alignment, and returns the optimal rotation matrix and translation, along with
the TM score:
>>> import numpy as np
>>> from tmtools import tm_align
>>>
>>> coords1 = np.array(
... [[1.2, 3.4, 1.5],
... [4.0, 2.8, 3.7],
... [1.2, 4.2, 4.3],
... [0.0, 1.0, 2.0]])
>>> coords2 = np.array(
... [[2.3, 7.4, 1.5],
... [4.0, 2.9, -1.7],
... [1.2, 4.2, 4.3]])
>>>
>>> seq1 = "AYLP"
>>> seq2 = "ARN"
>>>
>>> res = tm_align(coords1, coords2, seq1, seq2)
>>> res.t
array([ 2.94676159, 5.55265245, -1.75151383])
>>> res.u
array([[ 0.40393231, 0.04161396, -0.91384187],
[-0.59535733, 0.77040999, -0.22807475],
[ 0.69454181, 0.63618922, 0.33596866]])
>>> res.tm_norm_chain1
0.3105833326322145
>>> res.tm_norm_chain2
0.414111110176286
If you already have some PDB files, you can use the functions from tmalign.io
to retrieve the coordinate and sequence data:
>>> from tmtools.io import get_structure, get_residue_data
>>> from tmtools.testing import get_pdb_path
>>> s = get_structure(get_pdb_path("2gtl"))
>>> s
<Structure id=2gtl>
>>> chain = next(s.get_chains())
>>> coords, seq = get_residue_data(chain)
>>> seq
'DCCSYEDRREIRHIWDDVWSSSFTDRRVAIVRAVFDDLFKHYPTSKALFERVKIDEPESGEFKSHLVRVANGLKLLINLLDDTLVLQSHLGHLADQHIQRKGVTKEYFRGIGEAFARVLPQVLSCFNVDAWNRCFHRLVARIAKDLP'
>>> coords.shape
(147, 3)
These functions are light-weight wrappers around BioPython.
Credits
This package arose out of a personal desire to better understand both the TM-score algorithm and the pybind11 library to interface with C++ code. At this point in time it contains no original research code.
If you use the package for research, you should cite the original TM-score papers:
- Y. Zhang, J. Skolnick, Scoring function for automated assessment of protein structure template quality, Proteins, 57: 702-710 (2004).
- J. Xu, Y. Zhang, How significant is a protein structure similarity with TM-score=0.5? Bioinformatics, 26, 889-895 (2010).
License
The original TM-align software (version 20210224, released under the MIT
license) is bundled with this repository (src/extern/TMalign.cpp
). Some small
tweaks had to be made to compile the code on macOS and to embed it as a
library. This modifications are also released under the MIT license.
The rest of the codebase is released under the GPL v3 license.
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