Glycosylation Profile Determination via Discrete Substrate Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for detecting and measuring glycosylated proteins are inefficient and prone to underestimation due to interference from protein glycosylation, leading to false results in diagnostic tests, and there is a need for improved methods to generate glycosylation profiles for disease screening, diagnosis, and treatment.
Innovation Solution
A method involving contacting a target biological molecule with a specific antibody and a glycan-binding agent on a reaction substrate, allowing for the determination of a glycosylation profile in a single step by comparing the binding levels of the target with and without glycosylation, using discrete test regions to differentiate between glycan types and assess under-detection caused by glycosylation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods are used to detect and measure glycosylated proteins, then the detection process is simple, but the results are inaccurate due to underestimation and false results caused by interference from protein glycosylation
Solution Approach 1:
The assay is divided into multiple discrete test regions on the substrate, each dedicated to detecting specific glycan types or protein forms. This segmentation allows simultaneous measurement of different aspects (glycosylated vs non-glycosylated proteins) without cross-interference, resolving the contradiction between accurate measurement and assay simplicity.
Solution Approach 2:
Glycan-binding agents are introduced as intermediaries that specifically bind to glycan moieties on proteins. These agents enable indirect detection of glycosylation status by measuring binding affinity, allowing accurate differentiation between glycosylated and non-glycosylated proteins without directly measuring the proteins themselves, thus improving detection accuracy while maintaining manageable complexity.
2Productivity
If a single step method is used to determine glycosylation profile, then the productivity is improved, but the measurement precision may be compromised due to the complexity of differentiating between glycan types
Solution Approach 1:
The substrate contains multiple discrete test regions, each optimized for detecting specific glycan types or protein-glycan complexes. This spatial segmentation enables simultaneous parallel detection of different glycan profiles in a single assay step, achieving both high productivity and precise glycan differentiation without requiring sequential testing.
Solution Approach 2:
Different regions of the substrate are designed with specific local properties - certain regions contain capture antibodies for specific proteins, others contain glycan-binding agents for specific glycan types. This local quality differentiation allows each region to specialize in detecting particular features, enabling accurate glycan type differentiation while processing multiple targets simultaneously in one step.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables efficient and cost-effective generation of glycosylation profiles, improving diagnostic accuracy by distinguishing between glycosylated and non-glycosylated protein levels, thereby enhancing the detection of biomarkers and disease diagnosis.
Implementation Method 1
contacting the sample with an immobilised capture antibody that binds specifically to the target
Implementation Method 2
contacting the target bound to the immobilised capture antibody with a detection antibody that specifically binds the target
Implementation Method 3
contacting the target bound to the immobilised capture antibody with a glycan-binding agent
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The present invention describes methods of determining the glycosylation signature and determining the level of a protein in a sample obtained from a patient. The present invention also describes use of a patient protein glycosylation profile to identify the presence or absence of a disease in subjects.