ArShift

ArShift predicts side-chain aromatic (^1H) chemical shifts from protein structural data to provide insights into the local environment of aromatic residues for assessing protein structure and dynamics.

Key Features:

• Structure-Based Prediction: Uses protein structural information to predict chemical shifts of aromatic side-chain hydrogen atoms (^1H).
• Model Validation: Distinguishes correct versus incorrect structural models by analyzing predicted chemical shifts and comparing them with experimental data.
• Detection of Structural Changes: Identifies structural changes caused by cofactor or ligand binding and by sequence alterations via shifts in predicted aromatic ^1H chemical shifts.

Scientific Applications:

• Protein Structure Validation: Enables assessment of structural model accuracy by comparing predicted aromatic ^1H chemical shifts with experimental measurements.
• Study of Protein Interactions: Reveals how ligand or cofactor binding affects the local chemical environment of aromatic residues at the atomic level.
• Analysis of Sequence Variants: Examines the impact of sequence changes on the chemical environment and function of aromatic side chains through predicted shift differences.

Methodology:

Predicts side-chain aromatic (^1H) chemical shifts from protein structural information and compares predicted shifts to experimental chemical-shift data to evaluate model accuracy and detect structural changes.