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AI & Bioinformatics Platform

Computational Biology
Services, End to End

ICDMO applies current structure prediction, molecular simulation and screening methods to protein interactions, antibody assessment, virtual screening and multi-omics analysis. Each method is used within its documented applicability domain, and every prediction is delivered as an atomic-level hypothesis with its confidence assessment, not as a settled fact.

Molecular SimulationAI ScreeningAntibody EngineeringBioinformatics

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Scoped

Feasibility Reviewed First

Versioned

Tools and Parameters

Specialist Areas

Reported

Confidence and Limits

Ranked

Candidate Output

What We Offer

End-to-End Computational Biology Platform Across Four Specialist Areas

Computational methods have changed what can be triaged before an experiment is run. Interaction hypotheses that once needed months of biochemistry can now be generated in hours, and compound sets that would be expensive to test can be narrowed in silico first. What has not changed is that these are hypotheses: they set priorities for experiments, they do not replace them.

ICDMO covers four complementary areas — molecular simulation, AI screening, antibody and protein design, and bioinformatics — as a computational CDMO. We deliver the in silico work and the validation plan that follows from it; the laboratory work itself is run by your team or by qualified partners.

Suitable For

Drug target identification and protein interaction mapping

Virtual screening of multi-million compound libraries

Antibody / nanobody discovery and affinity maturation

Enzyme engineering and directed evolution guided by ML

CRISPR guide RNA design with off-target risk scoring

Bulk and single-cell RNA-seq analysis (DEG, cell annotation)

Genome variant calling (WES/WGS) and functional annotation

Multi-omics integration and biomarker panel identification

Complex prediction · Confidence scoring · Interface analysis

AI Prediction

Versioned

Structure Libraries

Structural libraries are built per project rather than sold as a fixed catalogue. Source databases, build date, species coverage and per-entry model confidence are documented, so you can judge what the library does and does not cover.

GPU cluster · HPC · Rapid delivery

Rapid Delivery

day

Initial Response, Then Scoping

We acknowledge every enquiry within one business day. Turnaround is then confirmed per project, because it depends on system size, data quality and how much preparation the inputs need — not on a headline number.

SPR · Y2H · EMSA · Co-IP · MST

Wet-Lab Validated

Stated

Performance and Its Limits

Performance is reported with task-appropriate metrics on relevant validation data, and we name the metric rather than quoting a single accuracy figure. Experimental confirmation — SPR, Y2H, EMSA, Co-IP, MST — is designed with you and coordinated through partner laboratories.

Our Services

Four Specialist Computational Areas

Physics-Based Modeling

Molecular Simulation

All-atom simulation in explicit solvent with validated biomolecular force fields. System size, simulation length and replicate count are fixed during scoping and reported with the results. Feasibility is assessed per system: large or poorly resolved complexes are flagged before a project is accepted rather than after.

Molecular Dynamics Simulation

100–400 ns MD simulations for protein–protein, protein–ligand, and protein–membrane systems. RMSD, RMSF, hydrogen-bond occupancy, and MM/GBSA binding free energy analysis included.

Explicit-Solvent MD100–400 nsMM/GBSAHPC Cluster

Protein Interaction & Binding Site Prediction

AI-powered prediction of PPI interfaces, allosteric pockets, enzyme active sites, and protein–antibody epitopes. Confidence-ranked results with publication-quality 3D visualisation.

Complex PredictionInterface ScoringCryptic PocketsConfidence-Ranked

Protein / Nucleic Acid Interaction Model

Complex structure prediction for protein–DNA, protein–RNA and intrinsically disordered regions, delivered with per-interface confidence and predicted contact maps.

Complex PredictionInterface ConfidenceIDR ModelingProtein–RNA

How It Works

From Consultation to Validated Results

Scientific Consultation

Discuss research objectives and data availability with AI science team

Define target/question, expected outputs, and timeline

Feasibility assessment before scope and price are fixed

Recommendation of optimal AI platform and analysis strategy

Customized Solution Design

Bespoke pipeline designed for your biological question and data type

Selection of AI algorithms, force fields, and validation benchmarks

Detailed technical proposal with milestones and deliverable list

Timeline and pricing confirmed after scoping, not before

Data Preparation & QC

Client data upload via secure FTP or cloud portal

Sequence/structure format validation and quality control

Protein construct optimization for computational tractability

Reference dataset curation and benchmark parameter setting

AI Computation

Execution on GPU-accelerated HPC with pinned tool versions

Quality checkpoints and, where useful, comparison across methods

Real-time project status updates via client portal

Intermediate result review and direction adjustment if needed

Results, Report & Support

Written report with annotated figures, methods and parameters

3D structure files, ranked hit lists, confidence scores and limitations

Biological interpretation and experimental follow-up recommendations

Ongoing support for manuscript preparation and data queries

Technology Stack

Established Methods, Used Within Their Limits

These frameworks are open to everyone, so running them is not the differentiator. Framing the question correctly, choosing the method for a stated reason, checking consistency across methods, recognising when a run has failed, and interpreting the biology — that is the work. Deliverables are research-use, with methods and parameters documented.

✓

Protein complex structure prediction with per-interface confidence reported

✓

RoseTTAFold & RoseTTAFoldNA for protein–nucleic acid modeling

✓

Rapid large-scale structure prediction for screening across sequence variants

✓

All-atom molecular dynamics in explicit solvent, with replicates and convergence assessment reported

✓

Molecular docking from fast triage to precision scoring, with consensus across methods

✓

DeepPurpose & MolBERT for ADMET and drug–target interaction prediction

Validation We Help You Plan

Yeast Two-Hybrid (Y2H)PPI & binding interface validation

EMSA & DNase FootprintingProtein–DNA interaction confirmation

RIP-seq / CLIP-seqProtein–RNA interaction mapping

SPR & Bio-Layer InterferometryBinding kinetics (kon, koff, KD)

MST & ITCThermodynamic binding characterization

AlphaScreen & TR-FRETHigh-throughput PPI screening

Co-IP & GST Pull-downComplex formation confirmation

Applications

Where Computation Changes the Decision

Drug Target Identification

Genome-wide PPI network screening to reveal novel druggable targets and functional interaction partners for your therapeutic area.

Hit Identification & Triage

Virtual screening of multi-million compound libraries against AI-predicted binding sites — delivering ranked hits with predicted ADMET profiles.

Lead Prioritisation

MM/GBSA and related approaches used as relative ranking tools within an SAR cycle — useful for ordering analogues, not for quoting absolute binding free energies.

Antibody Design & Triage

Model-guided nanobody and IgG assessment, humanisation scoring and variant ranking — from antigen sequence to a prioritised list of binders worth expressing and testing.

Biomarker Hypotheses

Multi-omics integration to generate candidate biomarker panels. Where sample size cannot support a validated classifier we say so and scope what would be needed instead.

Translational Research

Integrative bioinformatics analyses connecting genomic variants, expression changes, and protein function for mechanism-of-disease studies.

Platform Comparison & Turnaround

Platform	Key Capability	Turnaround	Validation Method
Molecular Simulation	MD trajectories, binding free energy	3–10 days	SPR, ITC, MST
AI Protein Interaction	PPI, binding site, protein–nucleic acid	3–5 days	Y2H, Co-IP, EMSA
Virtual Screening	Compound prioritization, ADMET prediction	5–10 days	AlphaScreen, FP
Antibody Engineering	VHH discovery, humanization, CDR maturation	2–4 weeks	Yeast display, SPR
Enzyme Engineering	ML fitness landscape, variant design	1–3 weeks	Activity assay, Tm
Bioinformatics	NGS, multi-omics, biomarker discovery	5–15 days	qPCR, IHC, western

Note: 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, available structural evidence and the applicability domain of the chosen methods. All services are research use only and not intended for diagnostic or therapeutic purposes; turnaround times are indicative and confirmed after scoping.

Technical Consultation

Share your research question and we will recommend an approach, say what it can and cannot resolve, and follow up with a no-obligation technical proposal. Initial response within one business day.

service@icdmo.com +1-631-626-9181

Standard Deliverables

✓Full written analysis report (PDF)

✓3D structure files (PDB/CIF format)

✓Ranked hit lists with confidence scores

✓Method, parameter and version summary

✓Publication-quality figures & tables

✓Limitations and validation recommendations

Bring Us the Question, Not a Service Code

We reply within one business day, review feasibility against your data and target, and then send a scoped proposal with deliverables, timeline and validation options.

Computational BiologyServices, End to End