chiLife

chiLife performs in silico site-directed spin label (SDSL) modeling for electron paramagnetic resonance (EPR) spectroscopy, including double electron-electron resonance (DEER), to predict spin-label conformations and interspin distances on protein structures.


Key Features:

  • In Silico Spin Labeling: Attaches rotamer ensemble representations of spin labels to protein structures to model spin-label conformations.
  • Customizable Pipelines: Enables construction of custom analysis and modeling pipelines that use SDSL EPR experimental data.
  • Extensibility with Custom Components: Supports addition of user-defined spin labels, scoring functions, and modeling methods.
  • Integration Capabilities: Integrates with third-party molecular modeling software via Python interfaces.

Scientific Applications:

  • DEER distance prediction: Predicts and aids interpretation of DEER-derived interspin distances by modeling spin-label conformations.
  • Protein dynamics and interactions: Investigates protein conformational dynamics and intra- or inter-protein interactions through simulated spin-label behavior.
  • Complementing experimental EPR: Generates simulated spin-label data to complement and validate experimental EPR measurements.

Methodology:

Computationally attaches spin-label rotamer ensembles to protein models and evaluates configurations using scoring functions to simulate spin-label interactions and produce data that complement EPR/DEER experiments.

Topics

Details

License:
GPL-2.0
Cost:
Free of charge
Tool Type:
library
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Python
Added:
4/20/2023
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

Backbone modelling

Publications

Tessmer MH, Stoll S. chiLife: An open-source Python package for in silico spin labeling and integrative protein modeling. PLOS Computational Biology. 2023;19(3):e1010834. doi:10.1371/journal.pcbi.1010834. PMID:37000838. PMCID:PMC10096462.

PMID: 37000838
Funding: - National Institute of General Medical Sciences: GM125753 - NIH Office of the Director: OD021557