Ref B2
Computational Service
Confidence Reported
Scoped After Feasibility Review
Service Overview
Docking answers a narrower and more useful question than screening: given this compound and this pocket, how is it most plausibly bound, and which interactions hold it there. We run rigid, flexible-receptor (induced fit) and covalent docking according to what the target requires, validate the protocol by reproducing a known binding mode wherever one exists, and deliver poses annotated with the specific contacts that medicinal chemistry can act on.
Key Features & Advantages
Protocol Validated Before Use
Where a co-crystal ligand exists, we redock it and report the RMSD. A protocol that cannot reproduce a known pose is corrected before your compounds are docked.
Receptor Flexibility When Needed
Induced-fit docking is used for pockets with mobile side chains or loops, where rigid docking systematically misplaces or rejects otherwise viable ligands.
Covalent Docking Supported
For targeted covalent inhibitors, warhead chemistry and the reactive residue are modelled explicitly rather than approximated with non-covalent scoring.
Interaction Maps, Not Just Coordinates
Each pose is delivered with an interaction diagram identifying hydrogen bonds, hydrophobic contacts, pi-stacking, halogen bonds and any strained or unsatisfied groups.
Where This Service Is Used
1Determining the likely binding mode of a hit from a biochemical or phenotypic screen
2Rationalising a structure–activity relationship that the chemistry team cannot explain
3Guiding analogue design by showing which vectors point into unoccupied sub-pockets
4Assessing whether a compound can bind a mutant form that has lost activity
5Supporting covalent inhibitor design by checking warhead geometry against the target residue
Methods and Techniques Applied
1Receptor preparation with attention to protonation, histidine tautomers, metal coordination and structural waters
2Ligand preparation covering ionisation, tautomers, stereochemistry and ring conformations
3Protocol validation by redocking a reference ligand and, where available, cross-docking across structures
4Rigid, flexible side-chain and full induced-fit docking depending on pocket behaviour
5Covalent docking with explicit warhead–residue bond formation for targeted covalent series
6Pose selection by score, interaction quality, ligand strain and consistency with known SAR
What We Need From You
1Target structure and the binding site of interest
2Compounds as SMILES or SDF, with stereochemistry and salt form specified
3Any measured activity data, which is used to sanity-check whether the poses explain the SAR
4Known co-crystal structures of the target or close homologues, if your team holds unpublished ones
What You Receive
1Docked poses in SDF/PDB with scores, including alternative poses where the result is genuinely ambiguous
2Two-dimensional interaction diagrams and annotated three-dimensional figures per compound
3Protocol validation results, including redocking RMSD against the reference ligand
4Structure–activity interpretation relating poses to your measured data where data exists
5Design suggestions: which vectors are open, which contacts are missing, which modifications are indicated
What We Compute and Report
1Ranked poses per compound with scores and, where binding is ambiguous, alternative modes
2Redocking accuracy against a reference ligand, reported as coordinate deviation in ångströms
3Per-pose interaction diagram with distances and angles for each contact
4Ligand internal strain energy relative to the low-energy conformer
5Consistency check between predicted poses and your measured structure–activity data
Questions We Are Asked Before Scoping
How reliable is a predicted binding mode?
▸For well-defined pockets with a validated protocol, top poses are frequently close to the crystallographic mode. Reliability falls for shallow sites, large flexible ligands and induced-fit systems, and we state which regime your target is in.
Can docking rank my compounds by potency?
▸Not dependably. Docking scores separate plausible from implausible binders far better than they separate a 10 nM compound from a 100 nM one. For ranking within a series, MM/GBSA or FEP is the appropriate tool.
What if the pose contradicts our SAR?
▸That is informative and we report it rather than adjust until it agrees. It usually means a different binding mode, a different protonation state, or receptor flexibility that requires induced-fit treatment.
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
Compounds already exist and the binding mode is needed to guide analogue design
A structure–activity relationship is not explainable and a structural hypothesis is required
Covalent warhead geometry must be checked against a specific residue
Consider another service when
You need to rank compounds by potency rather than plausibility
MM/GBSA & MM/PBSA Binding Free Energy No compounds exist yet and starting points are needed
High-Throughput Virtual Screening 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.
A plausible pose that contradicts the measured SAR
Poses are checked against your activity data, and a contradiction is reported and diagnosed rather than adjusted away.
Rigid docking failing on a pocket with mobile side chains
Pocket flexibility is assessed first and induced-fit protocols are used where the site requires them.
Protonation or tautomer state chosen by default and quietly wrong
Ionisation states at assay pH are assigned explicitly and recorded with the result.
A Worked Example
Explaining a ten-fold activity cliff between two close analogues
The situation
Two compounds differing by a single methyl group differed tenfold in potency, and the chemistry team could not account for it.
What the work involved
The protocol was validated by redocking the co-crystal ligand, both analogues were docked with flexible side chains, and ligand strain and water displacement were analysed for each pose.
What came back
The methyl displaced a conserved water with a favourable geometry in one analogue and clashed with a rotamer in the other. Three further substitutions were proposed on that basis.
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.
A 22% confirmed hit rate from docking 138 million compounds
In a landmark 2019 study, ~138 million make-on-demand compounds were docked against the dopamine D4 receptor. Of 549 compounds selected and tested, 122 were confirmed active — a 22% hit rate — including ligands in the sub-nanomolar range. The same work screened ~99 million compounds against AmpC β-lactamase, where 5 of 44 tested compounds were confirmed (11%), one of which was among the most potent non-covalent AmpC inhibitors reported at the time.
Lyu et al., Nature, 2019 ↗Hit rate rises with rank, which is why library scale matters
The same body of work showed that the probability of a compound being confirmed active increases as its docking rank improves, and that larger libraries push better-scoring molecules into the selected set. This is the practical argument for screening make-on-demand space rather than a physical catalogue — and also the reason scoring accuracy, not library size alone, remains the limiting factor.
Lyu et al., Nature, 2019 ↗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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Service Contract
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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