Skip to main content

Python bindings around the TM-align code for structural alignment of proteins

Project description


Python bindings for the TM-align algorithm and code developed by Zhang et al for protein structure comparison.


From the console, simply run

    pip install git+

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.


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
>>> res.tm_norm_chain2

If you already have some PDB files, you can use the functions from to retrieve the coordinate and sequence data:

>>> from 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
>>> coords.shape
(147, 3)

These functions are light-weight wrappers around BioPython.


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).


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.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Built Distributions

tmtools-0.0.2-cp310-cp310-win_amd64.whl (1.5 MB view hashes)

Uploaded cp310

tmtools-0.0.2-cp310-cp310-win32.whl (1.5 MB view hashes)

Uploaded cp310

tmtools-0.0.2-cp39-cp39-win_amd64.whl (1.5 MB view hashes)

Uploaded cp39

tmtools-0.0.2-cp39-cp39-win32.whl (1.5 MB view hashes)

Uploaded cp39

tmtools-0.0.2-cp38-cp38-win_amd64.whl (1.5 MB view hashes)

Uploaded cp38

tmtools-0.0.2-cp38-cp38-win32.whl (1.5 MB view hashes)

Uploaded cp38

tmtools-0.0.2-cp37-cp37m-win_amd64.whl (1.5 MB view hashes)

Uploaded cp37

tmtools-0.0.2-cp37-cp37m-win32.whl (1.5 MB view hashes)

Uploaded cp37

tmtools-0.0.2-cp36-cp36m-win_amd64.whl (1.5 MB view hashes)

Uploaded cp36

tmtools-0.0.2-cp36-cp36m-win32.whl (1.5 MB view hashes)

Uploaded cp36

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page