Intrachain interaction topology can identify functionally similar intrinsically disordered proteins

Area of Science:

• Computational Biology and Bioinformatics
• Protein Science
• Biophysics

Background:

• Intrinsically disordered proteins (IDPs) present a classification challenge due to low sequence homology and lack of stable structures, hindering traditional sequence and structural alignment methods.
• Functional similarity in IDPs often does not correlate with sequence similarity, necessitating alternative approaches for classification.

Purpose of the Study:

• To introduce and validate a novel classification scheme for intrinsically disordered proteins (IDPs) using sequence-patterning metrics derived from charge distribution.
• To demonstrate the utility of Sequence Charge Decoration Matrices (SCDMs) as 'molecular blueprints' for functional annotation of IDPs, particularly those with low sequence homology.

Main Methods:

• Application of heteropolymer theory to derive sequence-patterning metrics, focusing on charge patterning to generate Sequence Charge Decoration Matrices (SCDMs).
• Utilizing SCDMs to classify proteins within three specific families: Ste50, PSC, and the disordered RAM region of the Notch receptor.
• Comparison of SCDM-based classification with experimental data, including functional grouping and binding constants.

Main Results:

• SCDM-based metrics successfully classified proteins in the Ste50 and PSC families into functional and non-functional groups, aligning with experimental observations.
• The algorithm accurately grouped synthetic variants of the RAM region based on SCDMs, showing reasonable agreement with classifications derived from experimental binding constants.
• The study highlights the importance of high-dimensional metrics, such as self-interaction maps and topology, encoded in SCDMs for functional annotation of IDPs.

Conclusions:

• Sequence Charge Decoration Matrices (SCDMs) provide a powerful, structure-independent method for functional classification of intrinsically disordered proteins (IDPs).
• This novel approach effectively addresses the limitations of sequence alignment for functionally similar IDPs with low sequence homology.
• The findings underscore the critical role of electrostatic charge patterning in determining IDP function and offer a valuable alternative tool for protein annotation.