MDTraj: a modern, open library for the analysis of molecular dynamics trajectories

By R. McGibbon, Kyle A. Beauchamp, Christian Schwantes, Lee‐Ping Wang, Carlos Xavier Hernández, Matthew P. Herrigan, T. J. Lane, Jason M. Swails, Vijay S. Pande. 2014

2,233 citations recorded by the source corpus.

Summary: MDTraj is a modern, lightweight and efficient software package for analyzing molecular dynamics simulations. MDTraj reads trajectory data from a wide variety of commonly used formats. It provides a large number of trajectory analysis capabilities including RMSD, DSSP secondary structure assignment and the extraction of common order parameters. The package has a strong focus on interoperability with the wider scientific Python ecosystem, bridging the gap between molecular dynamics data and the rapidly-growing collection of industry-standard statistical analysis and visualization tools in Python. Availability: Package downloads, detailed examples and full documentation are available at http://mdtraj.org. The source code is distributed under the GNU Lesser General Public License at https://github.com/simtk/mdtraj.

Subfields: Atomic and Molecular Physics, and Optics, Molecular Biology, Spectroscopy

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

1. Brooke E. Husic
2. Vijay S. Pande
3. Sergey Ovchinnikov
4. Frank No'e
5. Lucy J. Colwell
6. Dorothee Kern
7. Hao Wu

In Molecular Biology

1. Frank No'e
2. Brooke E. Husic
3. Hannah K. Wayment-Steele
4. Vijay S. Pande
5. Lucy J. Colwell
6. Mohammad M. Sultan
7. Carlos Xavier Hernández
8. Sergey Ovchinnikov

In Spectroscopy

1. Frank No'e
2. Brooke E. Husic
3. Sergey Ovchinnikov
4. Vijay S. Pande
5. Lucy J. Colwell
6. Dorothee Kern
7. Hao Wu
8. Cecilia Clementi

Citations in the corpus

• Predicting multiple conformations via sequence clustering and AlphaFold2 (2023, neutral): “The r.m.s.d. for structure models was calculated in MDtraj 88 .”
• Generating valid Euclidean distance matrices (2019, methodology): “After we have found an assignment between the atoms, we superpose the structures using functionality from the software package MDTraj ([49]) and evaluate the maximal atomic distance between all heavy atoms (i.e., carbons and oxygens) after alignment.”
• Variational Encoding of Complex Dynamics (2017, methodology): “C α contacts were used for featurization 35,46 .”