{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/5"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/14"},{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"},{"label":"Chemistry","url":"https://skillfed.io/packages/category/scientific-engineering-chemistry"}],"enrichment":{"capability":"MDAnalysis reads and analyzes molecular dynamics simulation trajectories from many popular simulation packages, providing atom selection, structural analysis, and trajectory iteration through a Python API.","skillfed_tags":["molecular-dynamics","computational-chemistry","trajectory-analysis"],"use_cases":["Load and iterate through molecular dynamics trajectories from GROMACS, Amber, or NAMD simulations to extract atomic positions and velocities.","Select subsets of atoms (e.g., 'name OH' or 'protein and backbone') and compute structural properties like center of mass or distances.","Perform RMSD calculations and structural alignment to compare protein conformations across trajectory frames.","Extract time-series data (positions, forces, velocities) as NumPy arrays for downstream statistical or machine-learning analysis.","Analyze drug\u2013protein interactions or material properties by computing contact distances and structural metrics over simulation time."],"what_it_does":"MDAnalysis is a Python library for reading, manipulating, and analyzing molecular dynamics simulation trajectories. It abstracts away the complexity of different trajectory file formats\u2014supporting GROMACS, Amber, NAMD, CHARMM, DL_POLY, HOOMD, LAMMPS, and others\u2014and provides a unified interface to select atoms, extract structural data as NumPy arrays, and iterate through frames. The library is written by and for computational scientists and includes a growing collection of analysis algorithms for tasks like RMSD calculations, structural alignment, and distance analysis.\n\nThe package is mature (first released in 2012), actively maintained, and fiscally sponsored by NumFOCUS. It has a large dependency footprint (11 runtime packages including numpy, scipy, and matplotlib) and is designed for interactive exploration and scripting of simulation data. Prebuilt wheels cover recent Python versions and major platforms, making installation straightforward for most users.","worth_installing":"Yes. MDAnalysis is a mature, actively maintained library with broad support for simulation formats and a large user base in computational chemistry and biophysics. Install friction is moderate but manageable; the LGPLv3+ license is permissive for most use cases. No known security vulnerabilities. Install it if you work with molecular dynamics simulations and need a standard, well-documented toolkit for trajectory analysis."},"id":"mdanalysis","links":{"html":"https://skillfed.io/packages/mdanalysis","md":"https://skillfed.io/packages/mdanalysis.md","pypi":"https://pypi.org/project/mdanalysis/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-10-17","license_spdx":null,"license_treatment":"copyleft","name":"MDAnalysis","python_support":"supports_current","summary":"An object-oriented toolkit to analyze molecular dynamics trajectories."},"popularity":{"monthly_downloads":256728,"position":8459,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.10.0"}