Compound-Protein Interaction Mixture Systems for High-Throughput Screening
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Solution Overview
Problem
Existing compound-protein interaction experiments face high time-and-economic costs and low detection throughput due to complex procedures and lengthy sample preparation and measurement times.
Innovation Solution
A method that composes multiple compounds into mixture systems based on an optimized permutation matrix, allowing for high-throughput analysis by establishing corresponding relationships between compound interactions and mixture systems, thereby reducing experimental costs and time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If affinity-based or activity-based proteomic approaches are used to identify binding targets, then identification accuracy is improved, but experimental complexity and time cost increase
Solution Approach 1:
The patent combines multiple compounds into mixture systems and tests them together in a single experiment. Instead of testing each compound separately through complex derivatization procedures, the method merges multiple compounds into mixtures that are screened in parallel, reducing experimental complexity while maintaining identification accuracy through subsequent data analysis
Solution Approach 2:
The patent creates a universal testing framework where mixture systems can screen multiple compounds simultaneously using a single experimental protocol. The method develops universal data analysis algorithms that can deconvolute results from any mixture composition, making the approach broadly applicable without requiring compound-specific optimization
2Adaptability or versatility
If non-derivatization mass spectrometry methods are used, then applicability to more compounds is improved, but sample preparation time and measurement time increase
Solution Approach 1:
The patent merges multiple compound samples into mixture systems that are processed and analyzed together in a single mass spectrometry run. This combining approach eliminates the need for separate sample preparation for each compound, reducing total preparation time while maintaining broad applicability to diverse compound types through the non-derivatization MS methodology
Solution Approach 2:
The patent transitions from testing compounds in one dimension (individual samples) to testing them in a new dimension (combinatorial mixture systems). By organizing compounds into structured mixtures and using computational deconvolution, the method achieves high-throughput screening that reduces time investment while expanding compound applicability
3Measurement precision
If traditional compound-protein interaction experiments are conducted, then interaction detection accuracy is improved, but detection throughput decreases
Solution Approach 1:
The patent merges multiple compound-protein interaction experiments into a single assay by combining compounds into mixture systems. Multiple interactions are detected simultaneously in one experiment, dramatically increasing throughput while maintaining accuracy through computational algorithms that deconvolute the mixed signals to identify specific interacting compounds
Solution Approach 2:
The patent creates virtual copies of individual compound tests through computational modeling. By analyzing mixture data and using algorithms to reconstruct which individual compounds in the mixture caused the observed protein interactions, the method effectively generates accurate interaction data for multiple compounds without performing separate physical experiments for each
Data Source
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AI summary
The present application provides a method for improving a throughput of compound-protein interaction experiments. In the method of this application, multiple compounds to be tested are composed into multiple mixture systems according to a certain mixing rule, and corresponding relationships between abilities of the compounds to be tested to interact with the protein target and the mixture systems are established, and then the target protein corresponding to the compound to be tested is analyzed in a high-throughput manner. The analysis method of the present application can increase a detection throughput of the existing compound to be tested-target protein experiments by more than 10 times, while saving more than 90% of the experimental cost and time, significantly reducing the cost of manpower, time and experimental consumables, which has significant economic significance.