Allosteric drugs: New principles and design approaches
Wei-Ven Tee1, Igor N Berezovsky2
1Bioinformatics Institute (BII), Agency for Science, Technology and Research (A∗STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671.
Current Opinion in Structural Biology
|January 3, 2024
Summary
Designing allosteric drugs requires new strategies. This study emphasizes simultaneous optimization of allosteric sites and effectors for effective drug discovery.
Area of Science:
- Biochemistry
- Pharmacology
- Drug Design
Background:
- Allosteric drugs offer unique therapeutic potential distinct from orthosteric drugs.
- Current drug design principles may not fully capture the complexities of allosteric modulation.
Purpose of the Study:
- To outline novel principles and protocols for the rational design of allosteric drugs.
- To highlight the importance of considering both binding affinity and allosteric signaling in structure-activity relationships (SARs).
Main Methods:
- Introduction of the 'directed design protocol' for simultaneous generation and adjustment of allosteric site-effector pairs.
- Discussion of key approaches including reverse perturbation, targeted analysis, and agnostic analysis.
- Highlighting promising computational methods and generative models for allosteric drug discovery.
Main Results:
- Demonstration of the necessity to consider both binding affinity and allosteric signaling for effective allosteric effector design.
- Proposal of a simultaneous optimization framework for allosteric site-effector pairs.
- Identification of computational strategies, including generative models, to accelerate the discovery of allosteric drugs.
Conclusions:
- The design of allosteric drugs necessitates a departure from traditional approaches, integrating binding and signaling properties.
- A simultaneous, directed design protocol for site-effector pairs is crucial for optimizing allosteric drug candidates.
- Advanced computational techniques, particularly generative models, hold significant promise for advancing allosteric drug discovery.
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