AlphaKnot

AlphaKnot analyzes and quantifies entanglement (knotting) in protein structures predicted by AlphaFold, integrating pLDDT confidence values to assess the reliability of detected knots.

Key Features:

• Entanglement Analysis: Evaluates the presence and complexity of knots within protein structures using a probabilistic definition of knotting that considers entire chains and subchains.
• Matrix Diagram Visualization: Presents matrix diagrams that map knot types across polypeptide chains and subchains and pinpoint knot cores as minimal backbone segments forming specific knots.
• Classification System: Classifies entanglements into Knots, Unsure, and Artifacts based on pLDDT confidence values.
• Database Access: Provides a database of knotting information derived from AlphaFold predictions for 21 proteomes published prior to 2022 to support analyses of protein geometry, model validation, and evolutionary comparisons.

Scientific Applications:

• Protein Geometry Analysis: Examines relationships between knotting and protein structural features to infer potential impacts on function or stability.
• Modeling Reference: Serves as a reference set for validating new AlphaFold models against known entanglement patterns.
• Evolutionary Studies: Enables comparison of knotting across proteomes to investigate evolutionary trends and functional implications of structural complexity.

Methodology:

Analyzes AlphaFold-predicted structures using a probabilistic definition of knots that incorporates pLDDT confidence values, computes knot types across chains and subchains, and identifies knot cores.