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.

Diagram illustrating goals and scenarios for ternary complex prediction in targeted protein degradation (TPD) strategies, including fast follower and hit-based approaches for recruiter proteins and glue molecules.

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

• Proprietary FMO Protein-Protein Interface FMO-PPI Sygnature Platform

• 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.

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Related Capabilities

Protein Structure Prediction
Free Energy Methods
Molecular Dynamic Simulations
Generative AI and Machine Learning
Virtual Screening
Target Analysis
Ligand Based Drug Discovery
Structure-Based Drug Design

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