Using temperature coefficients to support resonance assignment of intrinsically disordered proteins.

Area of Science:

• Biochemistry
• Structural Biology
• Computational Biology

Background:

• Resonance assignment of large intrinsically disordered proteins (IDPs) is challenging due to low chemical shift (CS) dispersion.
• CSs are residue-specific, offering a basis for spin-system classification.
• Previous work demonstrated the utility of linear discriminant analysis (LDA) for CS-based classification.

Purpose of the Study:

• To improve spin-system classification for IDPs by incorporating temperature coefficients (TCs) into the analysis.
• To develop a novel approach using experimental CS and TC data for residue classification.
• To enhance the accuracy of resonance assignment in large IDPs.

Main Methods:

• Extended classification parameters by adding temperature coefficients (TCs) to chemical shifts (CSs).
• Utilized linear discriminant analysis (LDA) with experimentally derived CS and TC values as a training set.
• Applied the method to a large fragment (1-239) of the Tau protein.

Main Results:

• Incorporating TCs into CS analysis significantly improved recognition efficiency for residue classification.
• The method successfully distinguished between lysine and glutamic acid, and valine and isoleucine residues.
• The combination of TCs with Cα, Cβ, N, and Hα CSs proved more beneficial than using Cα CSs alone.

Conclusions:

• The proposed method effectively enhances the accuracy of resonance assignment in large IDPs.
• Temperature coefficients provide valuable supplementary information for classifying amino acid residues.
• The developed computational tool is available for broader scientific application.