PINE-SPARKY.2

PINE-SPARKY.2 integrates automated NMR chemical shift assignment, secondary-structure detection, flexibility and hydrophobic core prediction, and three-dimensional model calculation to support NMR-based structural biology of biological macromolecules.


Key Features:

  • Chemical Shift Assignment and Verification: Automated assignment and verification of NMR chemical shifts to identify atomic environments within macromolecules.
  • Automated Detection of Secondary Structural Elements: Automated detection of alpha-helices and beta-sheets from NMR data.
  • Predictions of Flexibility and Hydrophobic Cores: Algorithms to predict regions of flexibility and to identify hydrophobic cores relevant to protein stability and function.
  • Calculation of Three-Dimensional Structural Models: Calculation and refinement of three-dimensional structural models from NMR data to determine spatial atomic arrangements.

Scientific Applications:

  • Atomic-level Structure Determination: Determination of atomic-level structures of proteins and other biological macromolecules using NMR data.
  • Conformational Dynamics in Solution: Investigation of conformational changes and internal dynamics of macromolecules in solution.
  • Protein–Ligand Interaction Characterization: Characterization of protein–ligand interactions detectable by NMR.

Methodology:

Performs automated chemical shift assignment and verification, automated secondary-structure detection, flexibility and hydrophobic core prediction algorithms, and calculation and refinement of three-dimensional structural models from NMR data.

Topics

Details

Tool Type:
desktop application
Operating Systems:
Linux
Added:
6/27/2018
Last Updated:
11/25/2024

Operations

Publications

Lee W, Markley JL. PINE-SPARKY.2 for automated NMR-based protein structure research. Bioinformatics. 2017;34(9):1586-1588. doi:10.1093/bioinformatics/btx785. PMID:29281006. PMCID:PMC5925765.

PMID: 29281006
PMCID: PMC5925765
Funding: - National Institutes of Health: P41GM103399

Documentation