Computer-Assisted Drug Design Using Hinge Region Mutation
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Solution Overview
Problem
Current computer-assisted treatment design processes face challenges in efficiently designing effective drugs due to the complexity of the treatment design process and the vast chemical space of potential new drugs.
Innovation Solution
The implementation of a computer-implemented treatment design system that utilizes a hinge region database to identify and modify hinge regions in functional compounds, allowing for the activation of functional regions without the need for activation agents, thereby optimizing therapeutic efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional trial-and-error methods are used for drug discovery, then the process is simple to implement, but the time and resources required are excessively large
Solution Approach 1:
The patent applies preliminary action by pre-identifying and storing hinge region structures and their associated mutations in a database before actual drug discovery begins. This allows the computer system to quickly retrieve and apply pre-analyzed hinge region information during the drug design process, eliminating the need for time-consuming real-time analysis of protein structures and potential mutations.
Solution Approach 2:
The patent uses copying by creating a computational model (copy) of the hinge region database that can be repeatedly queried and applied to different drug discovery projects. Instead of analyzing protein structures from scratch for each new drug candidate, the system copies and applies pre-stored hinge region knowledge to multiple different targets, significantly accelerating the discovery process.
2Reliability
If the chemical space of potential new drugs is extensively explored, then the likelihood of finding effective drugs increases, but the complexity of the treatment design process becomes unmanageable
Solution Approach 1:
The patent applies local quality by focusing the drug design process on specific, critical regions of the protein (hinge regions) rather than attempting to optimize the entire protein structure or explore all possible chemical modifications. By concentrating computational resources on analyzing and mutating only the hinge region, the system achieves reliable drug design results with manageable complexity.
Solution Approach 2:
The patent segments the complex protein structure into distinct functional regions, specifically isolating the hinge region as the critical target for modification. This segmentation allows the system to treat the hinge region as a separate, manageable unit with its own database of known structures and mutations, simplifying the overall drug design process while maintaining effectiveness.
3Reliability
If activation agents are used to activate functional regions, then the functional compound can interact with biological targets, but the therapeutic efficacy is reduced due to the need for additional compounds
Solution Approach 1:
The patent extracts the activation function from a separate activation agent and integrates it directly into the functional compound by modifying the hinge region. Instead of requiring a distinct activation agent to be administered separately, the hinge region mutation itself provides the activation capability, eliminating the need for additional compounds and improving therapeutic efficacy.
Solution Approach 2:
The patent merges the activation function with the functional compound by incorporating hinge region modifications directly into the compound's structure. This combining of the activation capability with the therapeutic agent reduces the total number of compounds needed and ensures that the functional compound is already in its active form upon administration.
Data Source
AI summary
Some embodiments include a computer-assisted method of biomedical treatment design. For example, a computer system can select a compound model associated with a candidate compound that is structured to bind to a biological target to modulate the biological target into achieving a therapeutic effect. The computer system can then identify a structural feature in the compound model as a hinge region that connects domains in the candidate compound. The computer system then determines a mutation process to introduce a mutation at the hinge region such that the mutation activates the candidate compound. The computer system then generates an updated compound model based on the mutation added to the candidate compound to present in a treatment design interface.