It’s important to lay strong foundations for successful drug discovery at this first stage of the process. Our integrated target identification and validation platform combines AI with expert insights, and rigorous lab validation to guide targets through robust evaluation, ready for hit discovery.
Validated, high-quality hits, delivered through integrated technologies and expert collaboration, give you a confident starting point for faster drug discovery.
Turning promising leads into clinical candidates with speed, precision, and the scientific expertise to generate high-quality data and deliver real patient impact.
Discover precise insights into brain neurochemistry with Sygnature Discovery's in vivo microdialysis and cOFM services. With over 20 years of expertise, we design bespoke studies that reveal how compounds modulate neurotransmitter systems in health and disease. Using UHPLC/HPLC with electrochemical detection or mass spectrometry, we deliver robust PK/PD data to support confident CNS decision making.
Delivering integrated, modality-agnostic drug discovery to tackle complex biology, accelerate development, and advance innovative therapies with confidence.
Advancing next-generation ADCs through payload-focused design, integrated expertise, and collaborative innovation to deliver safer, more selective therapies.
Driving biologics innovation through integrated design, structural biology, and multidisciplinary expertise to accelerate next-generation therapies from concept to clinic.
Combining deep therapeutic expertise with translational insight to design strategies, reduce risk, and accelerate discovery programs toward clinical success.
Accelerating oncology drug discovery through integrated expertise, innovative modalities, and translational insight to deliver candidates with real clinical impact.
Driving immunology and inflammation drug discovery through tailored assays, translational models, and integrated expertise for faster clinical success.
Advancing CNS drug discovery through integrated models, translational biomarkers, and multidisciplinary expertise to overcome complexity and accelerate therapeutic innovation.
Designing and advancing differentiated small-molecule therapies for obesity and diabetes through integrated expertise, mechanistic insight, and translational strategies.
Inobrodib, an exciting, first-in-class oral anti-cancer drug in clinical development by CellCentric, was collaboratively designed, synthesised and supported on its pre-clinical journey by an integrated project team at Sygnature Discovery. Inobrodib is now showing promising results in Phase I and II trials for multiple myeloma and other cancer types.
AI Meets Expertise: A hybrid Workflow For Modern Target ID | QIAGEN & Sygnature
In drug discovery, generating targets is no longer the challenge.
The real question is how to identify the few worth investing months of research and significant resources to pursue.
Hear expert perspectives on how AI, pathway analysis and scientific expertise are shaping modern target identification.
It’s important to lay strong foundations for successful drug discovery at this first stage of the process. Our integrated target identification and validation platform combines AI with expert insights, and rigorous lab validation to guide targets through robust evaluation, ready for hit discovery.
Validated, high-quality hits, delivered through integrated technologies and expert collaboration, give you a confident starting point for faster drug discovery.
Turning promising leads into clinical candidates with speed, precision, and the scientific expertise to generate high-quality data and deliver real patient impact.
Delivering integrated, modality-agnostic drug discovery to tackle complex biology, accelerate development, and advance innovative therapies with confidence.
Advancing next-generation ADCs through payload-focused design, integrated expertise, and collaborative innovation to deliver safer, more selective therapies.
Driving biologics innovation through integrated design, structural biology, and multidisciplinary expertise to accelerate next-generation therapies from concept to clinic.
Combining deep therapeutic expertise with translational insight to design strategies, reduce risk, and accelerate discovery programs toward clinical success.
Accelerating oncology drug discovery through integrated expertise, innovative modalities, and translational insight to deliver candidates with real clinical impact.
Driving immunology and inflammation drug discovery through tailored assays, translational models, and integrated expertise for faster clinical success.
Advancing CNS drug discovery through integrated models, translational biomarkers, and multidisciplinary expertise to overcome complexity and accelerate therapeutic innovation.
Designing and advancing differentiated small-molecule therapies for obesity and diabetes through integrated expertise, mechanistic insight, and translational strategies.
Inobrodib, an exciting, first-in-class oral anti-cancer drug in clinical development by CellCentric, was collaboratively designed, synthesised and supported on its pre-clinical journey by an integrated project team at Sygnature Discovery. Inobrodib is now showing promising results in Phase I and II trials for multiple myeloma and other cancer types.
Helping you design and optimize ternary complexes with precision, combining advanced modeling and collaborative expertise, making previously “undruggable” targets tractable.
At Sygnature, we integrate advanced computational modelling with extensive drug discovery expertise to accurately predict ternary structures and assess their stability, turning complex structural data into actionable design decisions. By leveraging structural biology, molecular simulations, and AI-driven insights, we assess target tractability, analyze predict ternary complex formation, and guide degrader optimization, helping our partners unlock new therapeutic opportunities across diverse disease areas.
This capability addresses one of the hardest challenges in drug discovery, modulating disease-relevant proteins that lack conventional binding pockets or enzymatic activity. Through Targeted Protein Degradation (TPD) strategies, we can make previously “undruggable” targets tractable. Our TPD capabilities span both PROTACs and Molecular Glue degraders.
With over 14 years of experience in computational drug design, Sygnature leads in modelling and simulation for bifunctional degraders. Our scientists are committed to advancing and refining computational workflows that enable precise construction, simulation, and evaluation of both established and novel multicomponent assemblies. Our workflows cover everything from concept generation and ternary complex modelling to structural refinement, energetics evaluation, and degrader ranking, guided by detailed knowledge of binding epitopes and interaction interfaces.
Our Approach
We harness a suite of advanced technologies and proprietary platforms to drive molecular glue discovery and optimization:
• Molecular dynamics (MD) simulations
• Protein-protein docking
• Ligand-based virtual screening
• Industry leading tools: Orion, MolSoft ICM, MOE, Gamess
• AI-guided generative design and multi-parametric QSPR modelling to refine chemical matter and predict degradation efficiency.
These tools enable precise modelling of ternary complexes, prediction of binding cooperativity, residue-level interactions, and electrostatic complementarity mapping.
By combining structural biology, cheminformatics, and machine learning, we help clients overcome challenges in selectivity, potency, and mechanistic validation, bridging in silico design with in vitro success.
Unlocking the “undruggable” with PROTACs and Molecular Glues
To enable the precise design of bifunctional and monovalent degraders, our capabilities include:
• Fast follower linker and glue optimization
• Virtual screening for derisking and diversification of chemotypes of known glues
• Advanced ternary complex modelling and post-processing
• AI-driven glue design
• Predictive degradation profiling using Sygnature’s Fragmented Molecular Orbital at Protein-Protein Interface (FMO-PPI platform and Molecular Dynamics (MD)
While PROTACs and Molecular Glues (MGs) introduce complex design and data interpretation challenges, Sygnature’s integrated approach combines structure-based modeling, quantum-mechanical (QM) level interaction analysis, and AI-guided optimization to deliver predictive insights and validated strategies that accelerate discovery and reduce risk.
Our proprietary CHARMED platform and advanced modeling workflows enable rational design of PROTACs and Molecular Glues (MGs), tackling challenges such as selectivity, cooperativity, and degradation efficiency. These approaches extend the reach of therapeutic development into previously undruggable target classes, representing a major advancement in precision medicine.
Why Choose Sygnature
We blend extensive scientific expertise with cutting-edge technology to accelerate your drug discovery goals. Our strength lies in cross-functional collaboration from fully integrated and collocated support across medicinal chemistry, bioscience, DMPK, and computational modelling. Utilizing data- driven insights, we guide every stage of discovery while working closely with our partners to tailor solutions to their specific targets.
Using our proprietary CHARMED platform, we enhance early-stage TPD programs with high-throughput synthesis and screening. This approach is tightly coupled with advanced computational workflows to streamline degrader design and validation.
In drug discovery, generating targets is no longer the challenge.
The real question is how to identify the few worth investing months of research and significant resources to pursue.
Hear expert perspectives on how AI, pathway analysis and scientific expertise are shaping modern target identification.
Molecular glues are transforming targeted protein degradation but optimization remains complex and resource-intensive. This poster presents an integrated computational chemistry workflow combining generative AI and physics-based modelling to enable faster, more rational molecular glue design and prioritization.
Tatiana Rosado Rosenstock, Hiromitsu Ohzeki, Shohei Kumagai, Natsuno Suda, Colin Sambrook Smith Abstract Target identification (Target ID) is a foundational, multi-disciplinary…
Journal Papers
Related Capabilities
We help you design smarter compounds and make faster decisions by combining AI- powered modeling, extensive scientific expertise, and secure, collaborative data access to solve complex challenges and accelerate your drug discovery journey.
Using advanced AI and proven modelling techniques to predict protein structures with confidence, accelerating structure-based drug design and discovering novel therapeutic possibilities.
Providing Relative Binding-Free Energy Calculation using Non-Equilibrium Switching (NES) powered by OpenEye’s Orion® platform. Delivering precise binding affinity predictions to help you rank compounds with confidence and prioritize synthesis decisions for the most promising candidates early in the discovery process.
Utilizing cutting-edge technologies and proprietary software to uncover hidden interactions, predict ligand stability, and make confident design choices that accelerate your drug discovery program.
Combining AI-driven design, bespoke ML models and LLM-powered bioinformatics with hands-on collaboration to help you discover Optimized drug candidates faster.
From binding sites to druggability, our computational chemistry and protein science teams help you find the right starting points faster, combining structural insight with cutting-edge tools to design compounds that move your project forward with confidence.
Leveraging the properties of known active molecules to rapidly generate and optimize new compounds through ligand-driven insights, AI-powered tools, and collaborative expertise to uncover new chemical space and accelerate discovery.
Helping you design better compounds with greater confidence. Utilizing quantum-level insights and dynamic simulations we predict affinity, guide optimization, and help you prioritize the right candidates faster.
We apply advanced computational modelling to a wide range of targets, including kinases, transcription factors, scaffold proteins, epigenetic regulators, nuclear receptors, neurodegenerative disease targets, and E3 ligases. Our expertise spans both well-characterized and traditionally “undruggable” proteins.
Our modelling supports PROTACs, Molecular Glues, peptide-based degraders, and other heterobifunctional degraders. These approaches enable selective degradation of disease-relevant proteins using diverse mechanisms. Our modelling workflows are designed to support each modality by predicting ternary complex formation with known binding epitopes, guiding linker and glue design, and evaluating degradation potential.
We provide tailored workflows including structure-based virtual screening, conformational analysis with clustering, post-processing of ternary assemblies, and residue level energetics-based ranking using Sygnature’s FMO-PPI platform and MD pipelines to prioritise degrader candidates. These workflows are integrated with experimental platforms including CHARMED for rapid iteration and data-driven decisions.
We provide comprehensive scientific reports that include modelled ternary complex structures in preferred formats, ranked degrader poses with clustering analysis, and detailed interaction maps with residue-level insights such as FMO-PPI-SP. Reports are typically delivered in CSV or other accessible formats and include expert design recommendations, validation metrics, and full computational rationales.
Also included are clear visual summaries such as interaction diagrams and boundary surface representations to ensure transparency, traceability, and actionable insights throughout the degrader development process.
To accurately model ternary complexes for novel PROTACs and molecular glues, we require a well -defined set of inputs that enable precise computational analysis. These typically include structural and mechanistic information on the protein of interest (POI) and the recruiter protein or E3 ligase, known or hypothetical binding epitopes and key interface residues.
Preliminary degradation assay data or experimental results, if available, are highly valuable for validating modelling outcomes. We also request details on linker chemistry, binding motifs, and any known mutations that may influence complex formation and stability. Structural data such as crystallographic models, cryo-EM maps, or homology models are essential for refining simulations and tailoring our computational workflows to the specific biological system under investigation.
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Peak Proteins, NuChem Sciences, and SB Drug Discovery have now fully integrated with Sygnature Discovery.
