PyShifts

PyShifts performs chemical shift-based analysis of biomolecular ensembles within PyMOL to compare and visualize discrepancies between experimentally measured and computationally predicted chemical shifts.

Key Features:

• Integration with PyMOL: Implemented as a PyMOL plugin to operate directly on biomolecular ensembles and associated chemical shift data.
• Comparison and Visualization: Compares experimentally measured chemical shifts with computational predictions and visualizes discrepancies between them.
• Conformational Analysis: Sorts and ranks multiple conformations based on chemical shift discrepancies to identify conformers with the closest agreement to experimental data.
• Compatibility with Predictors: Accepts predicted chemical shifts from specific predictors such as LARMOR^D and LARMOR^Cα and supports input from other prediction sources.

Scientific Applications:

• Structure–shift correlation: Exploring relationships between chemical shifts and biomolecular structures.
• Protein dynamics: Analyzing conformational changes and dynamics through differences between measured and predicted shifts.
• Ensemble validation and selection: Identifying and prioritizing conformers that best match experimental chemical shift data for ensemble refinement or validation.
• Drug design and molecular modeling: Informing molecular modeling and drug-design hypotheses by highlighting structural variations reflected in shift discrepancies.
• Characterization of interactions: Comparing chemical shifts to study biomolecular interactions and their structural consequences.

Methodology:

Within PyMOL, PyShifts compares measured and predicted chemical shifts (including inputs from LARMOR^D and LARMOR^Cα) and sorts conformations by their shift discrepancies.