pyPolyBuilder
pyPolyBuilder generates molecular topologies and initial configurations for classical molecular dynamics of arbitrary supramolecules, including linear polymer chains and branched structures such as dendrimers.
Key Features:
- Versatility: Generates topologies for a wide range of supramolecular systems beyond traditional biomolecules, including large branched molecules and dendrimers.
- Automation: Automates creation of molecular topology files for complex molecular structures to streamline simulation setup.
- Starting Structure Generation: Produces reasonable initial configurations suitable for classical molecular dynamics simulations.
- Implementation and Compatibility: Implemented in Python and designed for compatibility with multiple molecular simulation engines.
Scientific Applications:
- Nonbiological supramolecular modeling: Preparation of topologies and starting structures for supramolecular systems that are not well served by biomolecular tools.
- Materials science: Enabling molecular dynamics studies of polymeric and supramolecular materials to investigate their properties.
- Nanotechnology: Modeling branched and dendritic nanostructures for simulation-based characterization.
- Polymer chemistry: Supporting simulations of linear polymer chains and complex branched polymers such as dendrimers.
Methodology:
Implemented in Python and automates generation of molecular topology files and reasonable starting configurations for classical molecular dynamics, with outputs compatible with multiple simulation engines.
Topics
Details
- License:
- MIT
- Tool Type:
- command-line tool
- Programming Languages:
- Python
- Added:
- 11/29/2021
- Last Updated:
- 11/29/2021
Operations
Publications
Ramos MC, Quoika PK, Horta VAC, Dias DM, Costa EG, do Amaral JLM, Ribeiro LM, Liedl KR, Horta BAC. pyPolyBuilder: Automated Preparation of Molecular Topologies and Initial Configurations for Molecular Dynamics Simulations of Arbitrary Supramolecules. Journal of Chemical Information and Modeling. 2021;61(4):1539-1544. doi:10.1021/acs.jcim.0c01438. PMID:33819017.