Polysaccharide characterisation is a data integration problem: no single technique establishes structure, and the answer emerges from reconciling chromatography, mass spectrometry, methylation analysis, monosaccharide composition and NMR. We interpret these datasets together to determine molecular weight distribution, monosaccharide composition, glycosidic linkage patterns, branching and anomeric configuration, and we state clearly which structural features the data actually supports and which remain undetermined.
Linkage, composition, mass and NMR evidence are assessed against one another, and contradictions between techniques are surfaced rather than resolved by assumption.
One- and two-dimensional spectra are assigned systematically to determine anomeric configuration, linkage position and sequence as far as the data permits.
Chromatographic results are interpreted with attention to calibration standards and column behaviour, which determine whether a reported average is meaningful.
Structural features supported by the data are separated from those that are inferred, which matters for publication and for regulatory documentation.
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.
| Item | Specification | Notes |
|---|---|---|
| Data types | NMR, MS, GC-MS, GPC/SEC | Plus composition and methylation analysis |
| Typical turnaround | 2–5 weeks | Depending on data completeness and complexity |
| Scope | Interpretation and integration | Analytical measurement is performed by your laboratory or a partner |
| Output | Report, tables, figures | Written for publication or technical dossiers |
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.
We check that the data, target class and available structural evidence can support the proposed approach, and say plainly where they cannot.
Scope, methods, deliverables, timeline and price are confirmed in writing, together with the limitations we expect to report.
The analysis runs on pinned tool versions in a containerised environment, with quality checkpoints and method comparison where that is informative.
You receive the ranked results, the documented methods, the limitations and a proposed validation plan, plus support in interpreting them.
The failure modes that produce confident-looking results which do not survive the next experiment. Each one is designed against rather than discovered afterwards.
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.
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.
Tell us about the target, the data you hold and the decision the result needs to support. A scientist reviews every enquiry and replies within one business day.
