SESCA

SESCA computes empirical circular dichroism (CD) spectra from protein structural models to estimate secondary structure (SS) composition and validate structural models.

Key Features:

• Empirical Spectrum Calculation: Employs an empirical approach to calculate CD spectra from protein structures for SS estimation and spectrum prediction.
• Model Validation and Prediction: Compares measured CD spectra against high-quality reference data and predicts CD spectra from synthetic datasets derived from known structures.
• Error Analysis and Correction: Identifies sources of inaccuracy such as intensity scaling errors and non-SS contributions and implements re-scaling techniques to mitigate scaling errors.
• Enhanced Accuracy: Accounts for typical non-SS contributions to reduce overestimated model errors during validation.
• Comprehensive Reference Set: Utilizes a large reference protein set with high-quality CD spectra to quantify deviations from ideal spectra and reference structures due to experimental limitations.

Scientific Applications:

• Secondary Structure Estimation: Determines protein SS composition from measured CD spectra and from spectra predicted from structural models.
• Structural Model Validation: Validates computational and experimental structural models by quantifying agreement between predicted and measured CD spectra.
• Assessment of Experimental Artifacts: Quantifies and corrects for intensity scaling errors and non-SS contributions that affect CD-based SS estimation and validation.

Methodology:

Empirical calculation of CD spectra from protein structures, analysis and quantification of deviations between measured and ideal/reference spectra, and implementation of re-scaling techniques and corrections for intensity scaling errors and non-SS contributions to improve SS estimation, CD prediction, and model validation.