SCAMPI2

SCAMPI2 predicts the topology of alpha-helical membrane proteins from amino acid sequences to identify transmembrane (TM) helices and their orientation based on hydrophobicity patterns.

Key Features:

• Hydrophobicity-Based Recognition: Distinguishes N-terminal and C-terminal TM helices by recognizing their enhanced hydrophobicity relative to central TM helices, enabling discrimination of marginally hydrophobic transmembrane segments from similarly hydrophobic regions in soluble protein domains.
• Direct Membrane vs. Non-Membrane Separation: Separates membrane proteins from non-membrane proteins without requiring an additional prefilter step.
• Improved Topology Prediction for Complex Proteins: Enhances prediction accuracy for proteins with large non-membrane domains by leveraging differential terminal helix hydrophobicity.

Scientific Applications:

• Protein Structure Prediction: Supports modeling of membrane protein topology and arrangement of TM segments within the membrane.
• Functional Annotation: Aids inference of protein function by predicting membrane topology for newly discovered proteins.
• Drug Discovery and Design: Provides topology-derived structural information relevant to identifying and evaluating membrane protein targets.

Methodology:

SCAMPI2 applies a first-principle-based approach that exploits intrinsic hydrophobic properties of TM helices and the enhanced hydrophobicity at N- and C-terminal helices to identify transmembrane regions and their orientation relative to the membrane.