Protein Folding Intermediate Targeting for Druggable Pocket Discovery
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Solution Overview
Problem
Existing methods are inadequate for identifying protein folding intermediates that can serve as therapeutic targets for drug discovery, as they do not effectively account for the druggability and stability of these intermediates.
Innovation Solution
A computational method is employed to model protein folding pathways, identify candidate intermediates based on energy and physical-chemical properties, and select target intermediates with druggable pockets using scoring parameters, followed by in silico drug discovery to find ligands that stabilize or inhibit these intermediates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing methods are used to identify protein folding intermediates, then the identification process is simple, but the ability to identify druggable targets with adequate stability is insufficient
Solution Approach 1:
The method segments the protein folding process into distinct intermediate states along the folding pathway, allowing individual identification and evaluation of each intermediate's druggability and stability characteristics separately
Solution Approach 2:
The patent introduces computational modeling and scoring parameters as intermediary tools that bridge the gap between raw protein structure data and druggability assessment, enabling systematic identification of therapeutic targets without direct experimental intervention at each step
2Measurement precision
If computational modeling of folding pathways is performed to identify stable intermediates, then the identification accuracy improves, but the computational time and resources increase
Solution Approach 1:
The method performs preliminary computational modeling to generate the folding pathway and identify candidate intermediates before applying detailed stability assessments and druggability scoring, filtering out non-promising candidates early to reduce overall computational burden
Solution Approach 2:
The patent employs multiple scoring parameters that can be adjusted and optimized to balance computational cost against identification accuracy, allowing flexible tuning of the method based on available resources and specific research needs
Data Source
AI summary
A method for identifying target protein folding intermediates, suitable to be tested as targets for drug discovery procedures. The method is carried out by means of electronic computing. The method provides a step of modelling a sequence in time of events defining a folding pathway of a protein, which includes modelling and/or calculating structural and/or energy and/or physical-chemical properties of one or more protein folding intermediate states along the folding pathway. Then, the method includes identifying at least one candidate protein folding intermediate, along the modelled folding pathway, based on identification properties, and selecting one or more target protein folding intermediates, among the at least one candidate protein folding intermediate, based on selection properties. The selection properties are related to the druggability of the protein folding intermediate. A related method for in silico drug discovery based on folding intermediate targeting is also provided.