PROMPT

PROMPT predicts protein conformational motions and models structural transitions to analyze dynamic regulatory mechanisms of proteins.

Key Features:

• Conformational Motion Prediction: Predicts large-scale conformational changes within proteins relevant to biological activity.
• Geometry-based Coarse-Grained Modeling: Employs a geometry-based coarse-grained mathematical model to simulate long-range protein motions while preserving essential spatial relationships.
• Monge-Kantorovich Optimization: Uses an optimization algorithm inspired by the Monge-Kantorovich mass transportation problem to model transformations between protein conformations.
• Crystallographic Structural Input: Utilizes distinct crystallographic data to identify and compare protein conformations.
• Validation by Morphing Methods: Validates predicted transitions using alternative morphing methods.

Scientific Applications:

• SSADH redox-switch analysis: Models the transformation between two crystal structures of succinic semialdehyde dehydrogenase (SSADH) to investigate redox-switch modulation involving disulfide bonding in the catalytic loop.
• Enzyme regulation: Elucidates dynamic regulatory mechanisms of enzymes through conformational analysis.
• Drug design: Informs drug design by providing structural transition data relevant to therapeutic development.
• Metabolic pathway analysis: Assists interpretation of protein roles within metabolic pathways, exemplified by application to GABA metabolism.

Methodology:

Uses distinct crystallographic structures as input; applies a geometry-based coarse-grained mathematical model to simulate transitions; solves an optimization problem inspired by the Monge-Kantorovich mass transportation framework; and validates predictions with alternative morphing methods.