Protein Surface Feature Analysis for Degron Identification
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Solution Overview
Problem
Current methods lack efficiency and accuracy in identifying target proteins capable of being targeted by E3 ligase machinery, particularly through the recognition of degrons on protein surfaces.
Innovation Solution
The development of methods that utilize protein surface features, specifically molecular surface representations, to identify degrons independently of primary and secondary structures, allowing for the identification of degrons in unrelated proteins with no structural similarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional methods based on primary and secondary structures are used to identify degrons, then identification is limited to proteins with known structural similarities, but the target space remains restricted and cannot identify degrons in unrelated proteins
Solution Approach 1:
The patent transitions from analyzing protein primary sequences and secondary structures to analyzing quaternary structure and molecular surface properties. This dimensional shift enables the identification of degrons in proteins with no sequence or structural similarity to known degron-containing proteins, thereby expanding the target space while maintaining identification accuracy through surface feature comparison
Solution Approach 2:
The patent changes the parameters used for degron identification from amino acid sequence composition and secondary structure elements to molecular surface properties including shape, electrostatic potential, hydrophobicity, and solvent accessibility. This parameter transformation allows the method to detect degrons in completely unrelated proteins by comparing surface feature patterns rather than sequence patterns
2Adaptability or versatility
If molecular glue degraders are used to expand target space to undruggable proteins, then more proteins can be targeted, but the challenge of identifying neosubstrates and matching targets to E3 ligases increases
Solution Approach 1:
The patent creates a computational model that copies the binding interface features of known degrons and uses this copy to screen for neosubstrates. By generating a degron profile from known substrate-receptor interactions, the method can identify new substrates that present similar surface features, even when the proteins themselves are unrelated, thus facilitating neosubstrate identification in the expanded target space
Solution Approach 2:
The patent develops a universal degron identification method based on molecular surface properties that can be applied across different protein families and E3 ligase systems. This universal approach, rather than being limited to specific protein families, enables the identification of neosubstrates for molecular glue degraders across the entire proteome, including previously undruggable targets
Data Source
AI summary
Described herein are methods and systems useful, for example, for degron identification, and also, for example, for predicting, identifying, classifying, and selecting neosubstrates of E3 ligases.