AI-Driven Agonist Design Service
AI-Driven Agonist Design Service, Accelerate Your GPCR Therapeutics Pipeline! Are you currently facing challenges with low peptide design efficacy, lengthy lead-optimization cycles, and difficulty creating molecules with extended half-lives? Our AI-Driven Agonist Design Service helps you accelerate drug discovery and obtain potent, stable agonists by leveraging advanced deep learning models and proprietary high-throughput virtual screening platforms.
Introduction of AI-Driven Agonist Design
The development of effective agonists is central to treating metabolic, cardiovascular, and neurological diseases. However, traditional drug discovery is slow and costly, often failing to create functional molecules that bind and activate the receptor in the precise manner required for therapeutic efficacy. The breakthrough in utilizing AI to address this fundamental "function-over-binding" challenge marks a new era in drug design.
What Are Services?
Our AI-Driven Agonist Design Service provides a rational, accelerated pathway for discovering novel therapeutic peptides, focusing on the challenging requirements of receptor activation. We use advanced computational biology and deep learning models to generate and virtually screen millions of novel peptide sequences designed to function as highly potent and selective receptor agonists. Various application scenarios, including:
- Ultra Long-Acting Therapeutics: Design novel peptide agonists engineered with enhanced stability and resistance to enzymatic degradation, significantly extending the in vivo half-life to enable less frequent patient dosing.
- Novel Dual- or Multi-Agonists: Rapidly discover "single shot" molecules that can simultaneously activate two or more metabolically relevant GPCRs, addressing complex polygenic diseases like obesity and type 2 diabetes with a single agent.
Why Choose Us?
| Pain Points | Benefit Created by Creative Biolabs |
|---|---|
| Low Design Efficacy | High Success Rate: Our models accurately predict function before synthesis, increasing the success rate in wet lab validation. |
| Long Development Cycles | Single-Cycle Acceleration: Reduce the traditional multi-step Design-Make-Test-Analyze cycle to a single, high-throughput computational-experimental cycle (validated in as little as ≈ two weeks). |
| Poor In Vivo Stability | Extended Half-Life: Computational screening for enzymatic degradation sites results in leads with significantly prolonged plasma half-lives. |
Fig.1 Workflow for deep learning-driven peptide design, functional screening, and experimental validation.1
How Creative Biolabs' AI-Driven Agonist Design Can Assist Your Project
Our service provides clear, scientifically-grounded solutions delivered through a meticulously managed, transparent workflow designed for maximum efficiency.
Workflow
- Target Receptor/GPCR Structure
- Target Functionality Criteria
- Reference Molecule Data
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Key Benefits
Our AI-Driven Agonist Design Service provides a critical advantage in the highly competitive peptide therapeutics market by focusing on extended stability and accelerated timelines.
- Extended Half-Life Guarantee: Our computational filter specifically targets and removes sequences prone to degradation by key enzymes, resulting in leads with a demonstrated three-fold increase in half-life compared to benchmarks.
- Rational Chemical Space Expansion: We move beyond the limitations of natural evolution, which can effectively design functional peptides across an expanded chemical space, delivering novel, stable, and highly potent drug candidates.
- Validated Functional Success: Our pipeline is built on the core principle of functional accuracy. Through rigorous virtual and in vitro screening, we have achieved a high functional validation rate.
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Deliverables
- Final Project Report: A comprehensive document detailing methodology, computational results, and final conclusions.
- Synthesized Lead Candidates: Delivery of purified peptide samples corresponding to the top-ranked, validated sequences.
- Full In Vitro Data Set: Complete raw and analyzed data from all functional assays.
- PK/PD Data Report (Optional): Full summary of in vivo pharmacokinetic and pharmacodynamic experimental results, including comparative analysis against reference drugs.
Frequently Asked Questions
Q1: Can your service design dual- or multi-agonists, and how is the risk of off-target activity managed?
A: Yes, our platform is optimized for multi-agonist, demonstrated by the published data on designing single-molecule dual agonists. The risk is managed by generating sequences that are structurally novel and distinct from any known natural sequences, and by running extensive in silico and in vitro binding and functional screens against closely related receptor family members early in the process.
Q2: How long does the entire design and in vitro validation process typically take compared to traditional methods?
A: Traditional iterative methods can take six months to a year just for lead optimization. Our AI-driven single-cycle approach, from initial design to the delivery of in vitro validated leads, typically ranges from 8 to 14 weeks. This acceleration is one of the most critical benefits we offer our clients.
Q3: What intellectual property safeguards are built into your design process?
A: Our de novo sequence generation process is engineered to create molecules that are completely novel and structurally divergent from existing natural and patent-protected sequences. We incorporate diversity filtering and structure-based comparisons early on to inherently create sequences with a strong, de-risking your ultimate commercial launch.
Contact Us
Creative Biolabs is the specialized partner for companies seeking to leverage the power of AI-Driven Agonist Design for next-generation peptide therapeutics. We provide validated lead candidates with superior characteristics—enhanced potency, prolonged half-life, and novel chemical structures—accelerating your discovery timeline from years to months. Contact our expert team today to discuss your specific target requirements and receive a detailed project proposal.
Reference
- Wei, Ting, et al. "AI-Driven De Novo Design of Ultra Long-Acting GLP-1 Receptor Agonists." Advanced Science (2025): e07044. Distributed under Open Access license CC BY 4.0, without modification. DOI: https://doi.org/10.1002/advs.202507044