Antibody and protein engineering, with the evidence trail built in
De novo binder design, antibody and nanobody engineering, bispecific design, epitope mapping, structure prediction, docking, and variant stability — designed, expressed, and purified by Excellgen scientists, and delivered with the complete record: inputs, model versions, parameters, ranked structures, and the candidates we rejected and why.
Excellgen, Inc. has developed and manufactured recombinant proteins and enzymes since 2008. Every computational campaign runs on NextELN, our own platform — so the audit trail is produced by the system doing the work, not written up afterwards. See the services →
Computational designs are hypotheses. See what we have validated, and what we have not →
Protein and antibody engineering, with the evidence trail built in
Excellgen scientists run scoped computational campaigns while NextELN keeps the exact inputs, methods, versions, candidate decisions, deliverables, and validation plan together.
Protein engineering
Structure-guided campaigns for solubility, expression, stability, or function, delivered as a ranked variant panel with rationale and an experimental plan.
View service →Antibody engineering
A clear entry point for Fv structure prediction, CDR-aware review, nanobody design, and bispecific-format engineering around your target and constraints.
View service →Nanobody design
VHH scaffold and antigen inputs move through structure, complex, sequence-design, and developability review on an operator-run GPU workbench.
View service →Bispecific antibody design
Format and topology selection, exact chain assembly, interface-aware complex modeling, and developability review for multispecific concepts.
View service →De novo binder design
Target-conditioned backbone and sequence generation with method-specific structural checks and a complete record of inputs, versions, and limitations.
View service →Epitope mapping
B-cell epitope maps, MHC-I/II binder prediction, and recommended antibody peptides from a target sequence, with structure-based contact analysis where a co-structure or model is available.
View service →Structure prediction
Batch protein structure prediction with PDB deliverables and per-residue confidence, suitable for downstream review and experimental planning.
View service →Computational designs and scores are research hypotheses; binding, activity, expression, stability, and safety require fit-for-purpose experiments.
Discuss a project →Every engagement comes with a workspace of its own
Submit requirements, put questions to the scientists doing the work, follow progress, hold the project data, read the results, and settle the invoice — in one place, for the length of the project. Included with the work, not sold on its own.
Requirements and questions
Set the target, the constraints, and what a useful answer looks like in a structured intake — then put questions to the scientists doing the work, against the actual data rather than an email thread.
Progress, data, and results
See what stage a campaign is in and what is waiting on you. Sequences, structures, parameters, model versions, and measurements stay together; ranked candidates are explorable in the browser with their metrics.
Quotes and invoicing
Scope, approve, and pay for work in the same place the work is recorded — so what was ordered, what was delivered, and what it cost never drift apart.
Your data stays yours — AI runs per-workspace and is never used to train models.
The instruments our scientists use on your project
These are the working surfaces behind an engagement — structure prediction, sequence and epitope analysis, literature monitoring, and the reporting that turns a campaign into something you can hand to a colleague. Your workspace shows the outputs; the scientists drive the tools.
Automatic literature search
Name your topics once. Every day NextELN scans PubMed and bioRxiv/medRxiv and files new papers & preprints in your workspace — deduplicated, with DOIs, abstracts, and PDF links.
Experimental-result summary
One click turns a page of raw procedure and data into a clear, editable summary at the top of your entry — the write-up is done in seconds.
Figures from your data
Point the assistant at a data table and it picks the right chart and draws a publication-ready figure delivered with the campaign report.
Manuscript writing
Give it a title and project details for a structured first draft; as results come in, pull data from your tables and pages and it grows the manuscript with you.
Data → PowerPoint
Turn a data table into a results deck — the AI writes the narrative and builds charts from your real numbers, exported as an editable .pptx.
Lab-meeting deck
Auto-summarize your recent results into a lab-meeting presentation — agenda, what's new, key charts, and next steps, ready to present.
Business-development deck
Draft an investor or partner pitch deck from your product and project details — problem, solution, technology, market, and the ask.
Scientific-meeting abstract
Write a structured conference abstract (Background · Methods · Results · Conclusion) grounded in your project and data — edit and submit.
Molecular-biology bench tools
Sequence viewer for DNA/RNA/plasmid maps, plus PCR primer design, restriction-site mapping, and find-a-matching-sequence across your own clones and oligos.
3D protein structure
Paste a protein sequence to fold it with ESMFold, or pull any PDB/AlphaFold structure — explore it interactively in 3D with pLDDT confidence coloring, right in the project workspace.
Antibody antigen design
Rank the best immunogenic peptides for raising antibodies in mice or rabbits from a protein sequence — antigenicity, surface accessibility, and flexibility scored together, with KLH/BSA conjugation guidance.
mRNA vaccine candidate design · Research preview
From a viral genome: assemble a computational candidate package for expert review, experimental planning, and preclinical validation. Predictions are not evidence of efficacy or safety.
Production, beta, research-preview, and roadmap capabilities are labelled separately. See the tool catalog and maturity status →
Connect prediction to measurement — and learn from the difference
NextELN keeps the computational proposal, scientist approval, experimental plan, samples, measured result, and next design round in one auditable lineage. The value is not another model output; it is evidence showing which predictions worked in your laboratory.
Design
Record inputs, versions, parameters, confidence, and rejected candidates.
Review
A scientist selects candidates and defines acceptance criteria.
Measure
Link expression, stability, binding, function, and failures to each design.
Redesign
Compare prediction with measurement and improve the next round.
How we engage
Scoped to the question you need answered. Workspace access, provenance, and the full record are included with every engagement.
Scoped study
Per project
A defined target, a defined question
- ✓Single campaign from the service catalog
- ✓Acceptance criteria agreed before work starts
- ✓Full provenance record delivered with results
- ✓Expression and purification available
Discovery program
Multi-round
Design → measure → redesign
- ✓Everything in a scoped study
- ✓Iterative rounds against your assay data
- ✓Dedicated workspace for your team
- ✓Named scientific lead
Embedded partner
Custom
Large biotech & pharma
- ✓Everything in a discovery program
- ✓Private data residency and your preferred model
- ✓SSO / SAML · API · SLA
- ✓Confidentiality and IP terms to your template