Fragment Module Libraries for Faster Lead Optimization
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Solution Overview
Problem
Existing drug discovery processes are time-consuming and expensive, and the generation of large fragment libraries often fails to produce derivative molecules with high biological activity and synthesis accessibility.
Innovation Solution
A fully automated approach to create biologically active derivative libraries through systematic fragmentation, mutation, and combination of parent drug molecules using predefined rules, resulting in a searchable fragment module library.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large fragment libraries are generated from known drug molecules, then the quantity of derivative molecules is increased, but the quality (biological activity and synthesis accessibility) may be compromised
Solution Approach 1:
The patent divides parent drug molecules into smaller fragment modules through systematic cleavage at defined positions. This segmentation allows the creation of combinatorial libraries where fragments are reassembled in multiple configurations, generating diverse derivative molecules while maintaining structural relationships to the parent compounds that preserve biological activity and synthesis accessibility.
Solution Approach 2:
The patent applies systematic mutations to fragment modules by changing chemical parameters such as atom substitution (e.g., carbon to nitrogen), functional group modifications, and stereochemical variations. These controlled parameter changes generate diverse derivatives while maintaining the core structural features necessary for biological activity and reasonable synthesis accessibility.
2Loss of time
If computer-aided drug discovery is used to accelerate lead optimization, then the time and cost are reduced, but the complexity of the computational process increases
Solution Approach 1:
The computational process is segmented into discrete, automated steps: parent molecule selection, systematic cleavage at defined positions, fragment sorting into backbone and peripheral categories, mutation generation, and combinatorial assembly. This segmentation of the computational workflow reduces complexity by breaking down the lead optimization process into manageable, programmable operations that can be executed automatically.
Solution Approach 2:
The system performs self-service through automated computational workflows that systematically generate fragment libraries without requiring manual intervention at each step. The computer automatically executes cleavage, sorting, mutation, and combination operations based on predefined rules, reducing both time and operational complexity compared to traditional manual drug discovery methods.
3Adaptability or versatility
If systematic mutation of parent molecules is performed, then the diversity of derivative molecules is increased, but the synthesis accessibility may be reduced
Solution Approach 1:
By segmenting parent molecules into modular fragments and systematically reassembling them through defined combination rules, the patent generates diverse derivatives that maintain structural relationships to the original parent compounds. This modular approach ensures that mutations are introduced in a controlled manner that preserves synthesis accessibility while achieving the desired diversity.
Solution Approach 2:
The patent applies mutations locally to specific fragment modules rather than throughout the entire molecule. This localized approach allows diversity to be introduced at specific positions while maintaining the overall structural framework that ensures synthesis accessibility. The systematic combination of mutated fragments with unmutated portions balances diversity with manufacturability.
Data Source
AI summary
A fully automated approach to systematic creation of mega libraries of biologically active derivatives of a specified structural parent drug compound with high potentiality. The libraries may be generated using a variety of discrete steps: creation of backbone libraries and peripheral libraries, introduction of chemical mutations, systematic combination of mutated backbone constituents and peripheral constituents, and systematic attachment of formulated modules to the parent compound to create a mega library of potential lead compounds.