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.
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.
Leveraging the properties of known active molecules to rapidly generate and optimize new compounds. When structural data is limited, smarter compound design is enabled through ligand-driven insights, AI-powered tools, and collaborative expertise. This approach uncovers new chemical space and accelerates discovery, while seamless integration with medicinal chemistry teams drives drug discovery programs toward the clinic.
Sygnature Discovery’s ligand-based drug design (LBDD) capabilities offer a powerful alternative when protein structures are unavailable.
Our computational chemists use ligand-derived insights, such as pharmacophore features, shape, and electrostatics, to guide compound design and optimization across the discovery pipeline.
Expert knowledge is combined with advanced tools, including generative AI, matched molecular pair analysis, and predictive modeling, to explore novel scaffolds, improve ADME properties, and prioritize the most promising ideas. Close collaboration with medicinal chemistry teams ensures that every design decision is data-driven and aligned with program objectives.
Our Ligand Based Drug Design Solutions
Discover smarter drug design with our AI-powered ligand-based solutions to generate novel compounds, optimize ADME profiles, and accelerate your DMTA cycle.
Scaffold Hopping and Fragment Replacement Tools
Scaffold hopping and isostere replacement techniques are used to generate novel IP, explore backup series, or address ADME concerns. With access to OpenEye’s BROOD tool and proprietary databases, we can rapidly screen over 50 million 3D replacements to identify viable alternatives in a timely fashion.
AI Enabled LBDD
Iktos Makya’s generative AI platform enables exploration of chemical space to generate novel 2D and 3D ideas from small molecule starting points. Combined with QSAR models, this approach supports potency enhancement, novel IP development, and ADMET optimization. Matched Molecular Pair Analysis (MMPA) tools from MedChemica assist in refining design ideas and prioritizing compounds within the DMTA cycle.
Local QSAR Models, Free-Wilson Models, Matched Molecular Pair Analysis
2D and 3D QSAR models, Free-Wilson analyses, and machine learning protocols are used to predict potency and ADMET properties for new compounds. These tools support multi-objective optimization and guide compound selection.
Conformational Analysis and QM Geometry Optimization
Ligand conformational analysis and restriction, including FreeForm Analysis and QM capabilities, are used to assess compound flexibility and its predisposition for optimal bioactive conformations, supporting refined compound design and improved binding potential.
Pharmacophore Alignment and Shape-Based Screening
Pharmacophoric techniques and alignment methods based on ligand shape and electrostatic similarity are used to compare different compound series, analyze structure-activity relationship (SAR) data, and identify novel active compounds through virtual screening.
Key Benefits
Our experienced teams have proven success in generating several novel lead series through ligand-driven strategies. We bring our heightened experience to every project we partake in.
A knowledge-based approach to lead identification
This enables novel scaffold and fragment design as an efficient way of developing novel chemical matter using Ligand-based computational tools to design new scaffolds or molecular fragments.
Seamless collaboration with medicinal chemistry teams
We don’t sit in silos, our collaborative approach facilitates idea generation and early prioritization.
Access to industry-leading leading literature and patent exploration tools
This including Reaxys and LBDD tools from MedChemica and OpenEye desktop + Orion platform tools to enable our ligand driven approaches.
As CNS drug discovery grows more complex, so does the need for smarter,…
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FAQs
LBDD is a computational approach in drug discovery that relies on known ligand information rather than protein structural data. It is especially valuable when protein structures are unavailable, enabling design through pharmacophore modelling, shape, and electrostatic similarity.
We use scaffold hopping, fragment replacement, pharmacophoric alignment, QSAR modeling (2D/3D), Free-Wilson analysis, and machine learning. Generative AI tools including Iktos Makya and MedChemica help explore virtual chemical space and optimize compound profiles.
Our knowledge-based design accelerates lead identification, supports multi-objective optimization, and fosters close collaboration with medicinal chemistry teams. This results in novel scaffolds, improved ADME properties, and efficient prioritization of ideas for integrated drug discovery projects.
Related Solutions
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