SSP

SSP computes residue-specific Secondary Structure Propensity (SSP) scores by integrating NMR chemical shifts from multiple nuclei to quantify α-helical and β-sheet propensities in intrinsically disordered proteins, including alpha- and gamma-synuclein.

Key Features:

• Chemical Shift Integration: Integrates chemical shifts from multiple nuclei into a single residue-specific SSP score that reports fractional α-helical or β-sheet propensity.
• SSP score: Provides a quantitative per-residue measure of expected α-helical versus β-sheet population in disordered regions.
• Re-referencing Technique: Applies a re-referencing procedure for chemical shifts to improve accuracy and comparability across disordered and folded proteins.
• Comparative Analysis: Enables direct comparison of SSP profiles between protein sequences to identify regions with differing secondary structure tendencies.
• Inference of Stability and Aggregation: Uses SSP profiles to infer local structural stability and aggregation propensity from transient secondary structure signals.

Scientific Applications:

• Disease Research: Compares alpha-synuclein (Parkinson's disease) and gamma-synuclein (overexpressed in late-stage breast cancers) to identify disease-related differences in secondary structure propensity.
• Structural Insights: Probes how sequence variations modulate transient α-helical and β-sheet propensities, informing hypotheses about evolutionary modulation of protein structure and function.
• Amyloid and Aggregation Studies: Has revealed increased α-helical propensity in gamma-synuclein in regions critical for alpha-synuclein amyloid fibril formation, suggesting a potential protective mechanism against aggregation.

Methodology:

Measure chemical shifts for target proteins, compare them to reference data, apply a re-referencing technique to ensure consistency, integrate nucleus-specific shifts into residue-specific SSP scores, and analyze SSP profiles to infer structural stability and aggregation tendencies.