Ref C6
Computational Service
Confidence Reported
Scoped After Feasibility Review
Service Overview
Degrader design has more moving parts than inhibitor design: two proteins must be brought into a productive, cooperative ternary complex by a linker whose length and rigidity determine whether degradation happens at all, and the resulting molecule must still cross a membrane. We model that system end to end — E3 ligase selection, ternary complex prediction, linker enumeration and scoring, cooperativity assessment and permeability prediction — and deliver a ranked set of degrader designs with the structural reasoning behind each choice.
Key Features & Advantages
Ternary Complex Modelled Explicitly
Complexes are predicted and simulated rather than assumed, because degradation depends on a productive ternary arrangement and surface compatibility, not on binary affinity to either protein.
Systematic Linker Exploration
Attachment points, lengths, rigidity and chemistry are enumerated and scored together, since the linker is usually what separates a degrader that works from one that does not.
E3 Ligase Choice Reasoned
Ligase selection considers tissue expression, surface complementarity with your target, resistance liabilities and existing chemistry, rather than defaulting to CRBN or VHL by habit.
Permeability Treated As A Design Constraint
Beyond-rule-of-five properties are predicted through the design cycle, so cell-permeability risk is surfaced while the molecule can still be changed.
Where This Service Is Used
1Converting a known binder into a degrader when occupancy-based inhibition is insufficient
2Targeting scaffolding functions that inhibition cannot address
3Overcoming resistance mutations that impair inhibitor binding but leave degradation viable
4Selecting and prioritising linker chemistry for an existing degrader series with weak activity
5Assessing molecular glue feasibility where no ternary-capable linker approach is available
Methods and Techniques Applied
1E3 ligase shortlisting from expression, surface compatibility and available ligand chemistry
2Protein–protein docking and multimer prediction of target–E3 arrangements to identify productive geometries
3Linker enumeration across attachment vectors, lengths and rigidity classes with conformational sampling
4Ternary complex refinement and molecular dynamics to test stability of the modelled arrangement
5Cooperativity assessment from interface contact analysis and binding energy decomposition
6Permeability, solubility and property prediction adapted to the beyond-rule-of-five space
What We Need From You
1Target structure and the warhead or binder you intend to use, with its binding pose if known
2Preferred or excluded E3 ligases and any degrader chemistry already available in-house
3Existing degrader data: analogues tested, degradation results, hook effect observations
4Cell system and tissue of interest, which bear on ligase selection and expression assumptions
What You Receive
1Ranked degrader designs with full structures, linker specification and attachment rationale
2Ternary complex models with interface analysis and simulation-based stability assessment
3Cooperativity and surface-complementarity assessment per design
4Predicted physicochemical and permeability profiles with the associated risk flagged
5Recommended synthesis and testing sequence, including which designs test which hypothesis
What We Compute and Report
1Ternary complex models with target–ligase interface area and contact composition
2Cooperativity assessment derived from interface analysis and binding energy decomposition
3Linker conformational ensembles with the span and flexibility each design permits
4Predicted permeability and solubility for beyond-rule-of-five chemistry, with domain caveats stated
5Simulation-based stability metrics for the modelled ternary arrangement
Questions We Are Asked Before Scoping
Can you predict whether a degrader will work?
▸No. Ternary complex modelling identifies designs that are geometrically and energetically plausible and removes those that are not. Degradation depends on ubiquitination efficiency, cellular context and proteasome processing, which computation does not resolve.
How many compounds should we make?
▸Degrader campaigns are empirical. Most teams synthesise fifteen to thirty linker variants in a first round. Our ranking is designed to make that round systematic rather than to replace it.
Do you design molecular glues as well?
▸We assess and model glue-type interfaces, but de novo glue design remains substantially harder than PROTAC design, and we say so at scoping rather than in the final report.
Interpretation and Limitations
Computational predictions prioritise hypotheses; they do not independently establish binding, biological activity, therapeutic efficacy, safety or clinical validity. Performance depends on input quality, target class, the structural evidence available and the applicability domain of the selected methods. Scores used for ranking are comparative devices and should not be read as measured quantities. All deliverables are for research use only and are not intended for diagnostic or therapeutic use.
Is This the Right Service for You?
Choose this when
Occupancy-based inhibition is insufficient and degradation is the intended mechanism
A validated binder exists with an exit vector that can carry a linker
Resistance mutations have weakened inhibitor binding but leave degradation plausible
Consider another service when
The target has no usable binder yet
De Novo Small Molecule Design A degrader series exists and the question is why it behaves as it does
Degrader Assessment & Validation What Goes Wrong, and How We Handle It
These are the failure modes that produce confident-looking results which do not survive the next experiment. Each one is designed against rather than discovered afterwards.
Two strong binders joined by a linker that cannot form a productive complex
Ternary geometry is modelled and simulated across the linker space before any design is recommended.
Degrader-sized molecules assessed with rule-of-five property models
Permeability and solubility are predicted with models built for beyond-rule-of-five space, with domain caveats stated.
Defaulting to the most common E3 ligase without checking fit
Ligase selection weighs tissue expression, surface complementarity and resistance liabilities, and the reasoning is documented.
A Worked Example
Linker exploration for a kinase degrader
The situation
The warhead and ligase ligand were both established, but the first six linkers made had produced no measurable degradation.
What the work involved
Attachment vectors were re-analysed on both ends, ternary complexes were predicted and simulated across lengths and rigidity classes, and interface contacts were used to estimate cooperativity.
What came back
The original attachment point was shown to orient the ligase away from the target surface. Twenty-four redesigned linkers were delivered, ranked by modelled complex stability and predicted permeability.
Illustrative of the shape this work takes. Details are generalised, no client or target is identified, and scope and outcome vary with the system in question.
What Published Work Reports
The results below were published by independent groups and are cited to show what these computational approaches have achieved in the literature. They are not ICDMO project results, and outcomes vary substantially between targets, datasets and programmes. We do not promise comparable results for any particular project.
AI-designed molecules have now produced clinical-stage compounds
A compound designed by generative methods against an AI-nominated target completed a randomised Phase 2a trial in idiopathic pulmonary fibrosis, reporting a mean forced vital capacity change of +98.4 mL in the 60 mg once-daily arm against −20.3 mL for placebo over 12 weeks in 71 patients. The result shows that generative design can produce molecules that survive to clinical testing; it does not show that any individual generated series will.
Nature Medicine, 2025 ↗Service Workflow
1
Scientific Consultation
We discuss the objective, the decision it supports and the data you hold. Nothing is quoted before we understand what the result has to answer.
2
Feasibility Review
We check that the data, target class and available structural evidence can support the proposed approach, and say plainly where they cannot.
3
Technical Proposal
Scope, methods, deliverables, timeline and price are confirmed in writing, together with the limitations we expect to report.
4
Computation and QC
The analysis runs on pinned tool versions in a containerised environment, with quality checkpoints and method comparison where that is informative.
5
Report and Follow-Up
You receive the ranked results, the documented methods, the limitations and a proposed validation plan, plus support in interpreting them.
Service Process
1
Online Consultation
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2
Solution Matching
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3
Service Contract
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4
Project Execution
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Data Delivery
Specifications & Turnaround
Note: ICDMO delivers computational (in silico) services. Results prioritise hypotheses for testing; they do not by themselves establish binding, biological activity, efficacy or safety. All deliverables are for research use only and are not intended for diagnostic or therapeutic use. Downstream experimental work is scoped separately and executed through qualified partners.
Get a Custom Quote
Our scientific team responds within 24 hours with a detailed technical proposal and pricing tailored to your project.
Contact Us Online ConsultationStandard Deliverables
✓Sequence-verified final product
✓Full QC documentation
✓Certificate of Analysis (CoA)
✓Electronic data files
✓Project completion report
Why ICDMO?
Computational CDMO Focus
Reproducible, Versioned Pipelines
Confidence & Limitations Reported
Experiment-Aware Recommendations
Response Within One Business Day