OVERVIEW
Precision biologics designed around your specific challenges
As solution architects, we recognise that there is no one-size-fits-all approach to biologics discovery. Each of our custom workflows draws on one or more of Etcembly’s validated structural and computational capabilities...
To address the specific challenges of co-complex prediction, small molecule design, functional immune discovery, and antibody expression.
Some of these validated capabilities also power EMLy Co-pilot, while others are currently delivered only through these custom workflows.
HAVE A SPECIALIZED PROJECT?
Connect with us to learn about custom solutions to meet your unique needs.
WORKFLOW 1
Co-complex prediction
The challenge
Current computational tools do not reliably predict binding and affinity across full immune receptor–target co-complexes, such as TCR-pMHC complexes.
What this workflow delivers
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High-precision affinity modelling via structure-aware protein docking
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Scoring of docked models to select near-native conformations
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Identification of similar binding poses across docked models
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Better early-stage decision-making around candidate viability
Approach
Binder prediction and affinity optimisation are performed using molecular dynamics-based protein docking designed for full TCR–pMHC co-complexes. Docked models are scored to identify near-native conformations and similar binding poses. Geometric descriptors capture the spatial organization of the complex, enabling the model to learn key biological constraints more effectively with substantially less data.
WORKFLOW 2
Small molecule design
The challenge
Standard structural biology computational approaches do not capture the full structural landscape of trimeric cytokines.
What this workflow delivers
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Analysis of complex and transitional cytokine conformations
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Identification of binding pockets and allosteric sites for biased ligand design
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Structural support for antibody discovery against cryptic epitopes
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Improved accuracy in early-stage hit discovery
WORKFLOW 3
Functional immune discovery
The challenge
Identification of representative immune sequences requires analysis across large datasets.
What this workflow delivers
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Sequencing and functional annotation across immune repertoires
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Discovery of functional motifs that represent promising leads and biomarkers
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Insights to support optimisation of hit antibodies
Approach
Our proprietary high-throughput microfluidics platform for paired immune sequencing powers this workflow. Combined with machine learning, diversity and clustering analyses, and integration with multi-omics datasets, this approach enables functional annotation of large immune datasets to inform biomarker and lead discovery.
WORKFLOW 4
Antibody expression enhancement
The challenge
Candidate developability can be limited by structural elements that contribute to misfolding, instability, and poor solubility.
What this workflow delivers
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Expression-boosting candidate mutations
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Structural and in-silico predictions associated with improved ability
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Assessment of aggregation risk while preserving structure and function
WORKFLOW 5
Affinity optimisation
The challenge
Conventional optimisation campaigns require large-scale, cost-heavy exploratory mutagenesis, synthesis, and testing of hundreds of variants.
What this workflow delivers
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Structure-guided affinity optimisation from sequence data
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In silico assessment of thousands of candidate variants before synthesis
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Ranked shortlists of mutations with improved binding potential
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Evaluation of TCR contact geometry, CDR loop positioning, and interface dynamics
Approach
Etcembly’s affinity optimisation workflow uses EMLy to model candidate binders in complex with their targets, assess productive binding poses, and prioritise mutations before synthesis. The workflow combines expert-guided mutagenesis, structural perturbation analysis, and high-throughput in silico variant assessment to identify candidates with improved binding potential.
