Frequently Asked Questions

Nucleora is a DNA and mRNA design studio — a local-first bioinformatics software application that provides researchers with a complete molecular biology software toolkit. It's designed for gene design, nucleotide sequence design, and genetic engineering workflows.

Unlike cloud-based tools, Nucleora runs entirely on your own computer. Your sequences never leave your machine unless you explicitly export them. The software includes over 530 tools for sequence analysis, codon optimization, RNA structure prediction, molecular cloning, and mRNA construct design.

Nucleora supports the design of:

• mRNA constructs for vaccines and therapeutics (with T7 promoter, UTRs, signal peptides, poly-A tails)
• Codon-optimized genes for expression in any host organism
• Plasmid vectors with restriction site mapping and assembly planning
• PCR primers for amplification, sequencing, and cloning
• Gibson and Golden Gate assemblies for modular cloning
• Guide RNAs for CRISPR applications
• Recombinant protein constructs with signal peptides and tags

Yes. Nucleora is free while in development. The full feature set — including codon optimization, RNA folding, primer design, cloning simulation, and mRNA vaccine design tools — is available at no cost.

There are no artificial feature limitations, watermarks, or sequence length caps during the free period.

Nucleora is being developed for macOS and Windows as a desktop application. It's built as cross-platform DNA software using Python with a local web interface.

Request early access to be notified when builds are available for your platform.

Yes. Nucleora is designed as local-first, offline-capable bioinformatics software. Core computational features work without any internet connection:

• Codon optimization using built-in codon usage tables
• RNA secondary structure folding via ViennaRNA
• Restriction enzyme analysis and mapping
• Primer design with Tm calculations
• Sequence annotation and feature detection
• Cloning simulation and assembly design

Database searches (NCBI, UniProt, Ensembl) require internet connectivity but results can be cached locally.

Yes. Nucleora is a privacy-first bioinformatics tool. All computations happen locally on your machine. Sequences are never uploaded to any server — not for analysis, not for storage, not for anything.

The only network requests are optional database lookups that you explicitly initiate (e.g., searching NCBI for a gene). Even then, only search queries are transmitted — your designed sequences stay local.

Yes. Nucleora includes a complete mRNA vaccine design workflow optimized for mRNA therapeutics development. The guided three-step process takes you from antigen selection to a fully-assembled vaccine construct:

• Step 1: Search for an antigen from real protein databases (UniProt, NCBI, Ensembl)
• Step 2: Codon-optimize the antigen for your target species and assemble the mRNA construct
• Step 3: Analyze RNA structure, simulate IVT manufacturing, and export

This makes Nucleora suitable for mRNA vaccine research, immunogen design, and early-stage mRNA drug design.

Nucleora's mRNA construct assembler supports all standard therapeutic-style elements:

• T7 promoter for in-vitro transcription
• 5' UTR with options for stability and translation efficiency
• Kozak sequence for ribosome recognition
• Signal peptide for secretion (MHC I/II targeting, DC targeting)
• Antigen ORF (codon-optimized)
• 3' UTR with stability elements
• Poly(A) tail with customizable length

Each part includes provenance citations so you know the source of every element.

Yes. Nucleora handles modified nucleotides used in modern mRNA therapeutics:

• N1-methylpseudouridine (m1Ψ) — the modification used in COVID-19 vaccines
• 5-methoxyuridine (5moU)
• Pseudouridine (Ψ)

The software correctly calculates molecular weight, extinction coefficients, and mass for transcripts containing modified bases, and tracks the modification through IVT simulation and order-form generation.

Nucleora includes a cap analog compatibility checker that validates your construct against:

• CleanCap AG — requires AG start
• CleanCap AU — requires AU start
• ARCA — anti-reverse cap analog
• Enzymatic capping — post-transcriptional

If your 5' UTR doesn't match the cap's start requirements, Nucleora shows the chemistry conflict and offers a one-click auto-fix.

Yes. Nucleora includes an LNP encapsulation predictor and lipid nanoparticle design guidance:

• Packaging index estimation based on mRNA length and structure
• Suggested N/P ratio for ionizable lipid formulation
• Four-lipid formulation guidance (ionizable lipid, helper lipid, cholesterol, PEG-lipid)
• RiboGreen encapsulation efficiency notes

Note: This is a heuristic estimator for research planning, not a substitute for wet-lab formulation optimization.

Yes. The immunogenicity analysis features include:

• dsRNA prediction — identifies regions that may form immunostimulatory double-stranded RNA
• Uridine content analysis — high U content triggers innate immune responses
• CpG motif detection — unmethylated CpG dinucleotides are immunostimulatory
• 5' UTR hairpin check — strong secondary structure near the cap can reduce translation

These checks are integrated into the IVT readiness report with severity grades and suggested fixes.

Codon optimization is the process of replacing codons in a gene sequence with synonymous codons that are more efficiently translated in a target host organism. This improves protein expression levels without changing the amino acid sequence.

It matters because different organisms use different codons at different frequencies. A codon that's common in E. coli might be rare in human cells or cattle, causing ribosome stalling and low expression.

Nucleora supports species-specific codon optimization for a wide range of organisms:

• Human (Homo sapiens)
• Mouse (Mus musculus)
• Cattle (Bos taurus) — and cattle proxies for related species
• Elephants (African and Asian) — real RefSeq-derived tables
• Companion animals — dogs, cats, horses
• Livestock — pigs, sheep, goats, chickens
• Zoo animals — primates, big cats, bears, rhinos
• Conservation species — with documented clade proxies where data is limited
• Model organisms — zebrafish, C. elegans, Drosophila
• E. coli, yeast, CHO cells — standard expression hosts

Each table cites its data source (NCBI RefSeq, Kazusa, or documented proxy).

Nucleora provides multiple codon optimization strategies:

• Most-frequent codon — replace every codon with the most common synonym
• Usage-weighted (stochastic) — probabilistic selection matching natural codon frequencies
• CAI-guided — optimize the Codon Adaptation Index toward the reference set
• tAI-guided — optimize the tRNA Adaptation Index based on tRNA availability
• MFE-aware — consider minimum free energy of local mRNA structure
• Multi-objective — balance CAI, tAI, and MFE with adjustable weights (Pareto optimization)

A live before/after comparison shows how each metric changes.

Yes. CpG depletion is a built-in constraint for codon optimization. Unmethylated CpG motifs trigger TLR9-mediated innate immune responses, which can reduce mRNA translation and increase reactogenicity.

Nucleora's optimizer can avoid CpG-containing codons where synonymous alternatives exist, with a configurable depletion strength setting.

Yes. Uridine depletion reduces innate immune recognition by RIG-I/MDA5 sensors. This is especially important for mRNA therapeutics using unmodified UTP.

The optimizer preferentially selects synonymous codons with fewer uridines while maintaining expression efficiency. The uridine fraction is reported in the QC panel.

Yes. The motif scrubber can avoid:

• Restriction enzyme sites that would interfere with cloning (specify any enzyme)
• Poly(A) signals (AAUAAA) that could cause premature termination
• Splice donor/acceptor sites
• T7 terminator motifs
• ARE (AU-rich elements) that destabilize mRNA
• miRNA seed sequences

Constraints are applied through guarded synonymous rewrites that don't change the protein sequence.

The Codon Adaptation Index (CAI) is a measure of how well-adapted a gene's codons are to a host organism, scored from 0 to 1. It's calculated relative to a reference set of highly-expressed genes.

Nucleora's CAI calculator computes this metric before and after optimization, showing the improvement. A CAI above 0.8 is generally considered well-optimized.

The tRNA Adaptation Index (tAI) measures how efficiently a sequence can be translated based on tRNA availability in the host cell. Unlike CAI, which uses codon frequencies, tAI is based on tRNA gene copy numbers.

Nucleora calculates tAI using GtRNAdb weights, with documented proxy fallbacks for species without direct tRNA data.

Yes. GC content optimization features include:

• Global GC% calculation (target: 40–60% for most hosts)
• Rolling-window GC plot showing local GC distribution
• GC cliff detection — flags regions with extreme local GC that may cause synthesis or expression issues
• GC smoothing constraint in the optimizer to avoid extremes

Nucleora uses the ViennaRNA package for RNA secondary structure prediction. This is the same engine used in academic research for mRNA folding prediction and RNA structure analysis.

The prediction is based on minimum free energy (MFE) thermodynamic calculations with the Turner 2004 energy parameters.

The RNA structure analysis includes:

• Minimum free energy (MFE) — the most thermodynamically stable structure
• Ensemble free energy — average energy across all possible structures
• Base-pairing probabilities (BPP) — partition function calculation
• Centroid structure — most representative structure of the ensemble
• Positional entropy — flexibility at each nucleotide position
• 5' UTR accessibility — ΔG in the cap-proximal and start-codon regions

Yes. Nucleora includes a 2D RNA structure viewer that renders:

• Arc diagrams showing base pairs along the linear sequence
• Forna-style interactive structure graphs
• Color-coding by base-pairing probability or positional entropy
• Feature overlays highlighting UTRs, start codon, and annotated elements

Strong RNA hairpins in the 5' UTR, especially near the cap and start codon, can block ribosome scanning and reduce translation efficiency. Nucleora's 5' UTR unwinding checker calculates ΔG in two windows:

• Cap-proximal (1–30 nt) — should be relatively unstructured for cap-dependent initiation
• Start-codon region (−15 to +15) — should be accessible for ribosome positioning

Results are graded with thresholds: too-stable structures get a "Critical" warning.

Yes. The dsRNA mapper identifies regions of the mRNA that may form double-stranded structures, which can trigger innate immune responses via pattern recognition receptors (RIG-I, MDA5, TLR3).

The analysis shows a positional risk map that you can use to identify and potentially redesign problematic regions.

Nucleora provides molecular cloning software features for:

• Restriction enzyme cloning — traditional cut-and-paste with compatible ends
• Gibson Assembly — seamless, multi-fragment assembly with overlapping ends
• Golden Gate assembly — Type IIS enzyme-based modular cloning
• TOPO cloning support

Each method includes simulation, fragment design, and primer generation.

Yes. Nucleora includes comprehensive restriction enzyme mapping with:

• Full REBASE enzyme database (via BioPython)
• Restriction site analysis showing all cut positions
• Unique-cutter identification for cloning
• Filter by enzyme properties (overhang type, methylation sensitivity)
• Virtual digest simulation with predicted fragment sizes

Gibson Assembly joins multiple DNA fragments with overlapping ends (typically 20–40 bp) using a mix of exonuclease, polymerase, and ligase.

Nucleora's Gibson assembly design tool:

• Calculates optimal overlap sequences
• Designs primers to amplify fragments with correct overlaps
• Checks for internal homology that could cause misassembly
• Predicts Tm of overlap regions

Golden Gate assembly uses Type IIS restriction enzymes (like BsaI, BsmBI) that cut outside their recognition sequence, creating custom overhangs for scarless, directional assembly.

Nucleora helps design:

• Compatible 4-bp overhangs for each junction
• Domestication primers to remove internal enzyme sites
• Entry vector and destination vector parts
• Assembly order verification

Yes. The plasmid map viewer renders:

• Circular plasmid maps (the default for vectors and IVT templates)
• Linear maps for fragments and constructs
• Feature annotations with labels and colors
• Restriction sites marked on the map
• ORFs and genes with reading frame indicators

Maps are rendered using dna_features_viewer in SnapGene-style format.

Nucleora uses the primer3 algorithm for PCR primer design. This is the same industry-standard tool used in NCBI Primer-BLAST, adapted for local use.

The primer design software handles:

• PCR amplification primers
• Sequencing primers
• Cloning primers (with overhangs for Gibson/Golden Gate)
• qPCR primer pairs
• IVT-template primers (T7 + AG start, reverse after poly-A)

Nucleora's primer analysis includes:

• Melting temperature (Tm) calculation with nearest-neighbor method
• GC content checking (target: 40–60%)
• Primer dimer prediction — self-dimers and cross-dimers
• Hairpin analysis — internal secondary structure
• 3' end stability — avoid 3' complementarity that causes mispriming
• Specificity check — off-target binding prediction

Yes. Multiplex primer design in Nucleora checks all primer pairs for cross-reactivity, ensuring compatible Tm values and avoiding inter-primer dimers that would cause problems in a single reaction.

The melting temperature calculator uses the nearest-neighbor thermodynamic method with configurable salt conditions:

• Primer concentration (default: 250 nM)
• Monovalent cation concentration (Na+, K+)
• Divalent cation concentration (Mg2+)
• dNTP concentration

This is more accurate than simple GC%-based formulas for primers >20 bp.

Nucleora provides comprehensive DNA sequence analysis and protein sequence analysis tools:

• Translation — all six reading frames
• Transcription — DNA to RNA
• Reverse complement
• ORF finder — detect all open reading frames
• GC content and composition statistics
• Molecular weight calculation (DNA, RNA, protein)
• Extinction coefficient for concentration determination

Yes. The ORF finder identifies all open reading frames in all six reading frames:

• Configurable minimum ORF length
• Alternative start codon support (ATG, CTG, GTG)
• Nested ORF detection
• Export ORFs as sequences or coordinates

Results are shown on the translation ribbon aligned to the DNA sequence.

Yes. Sequence alignment features include:

• Pairwise alignment — compare two sequences (local or global)
• Multiple sequence alignment — ClustalW-style
• Alignment to reference — compare an edited sequence to the original

Alignments show identity, gaps, and mismatches with color-coded visualization.

Nucleora's sequence parser handles:

• FASTA — single and multi-sequence
• GenBank (.gb, .gbk) — with full feature annotation
• Plain text — raw sequences (auto-detected)
• EMBL format

The GenBank parser extracts features, annotations, and metadata for display on plasmid maps.

Yes. Sequence annotation features detect:

• Common features — T7 promoter, CMV promoter, standard terminators
• Signal peptides — secretion leaders
• Antibiotic resistance genes
• Origins of replication
• Affinity tags — His-tag, FLAG, etc.
• Restriction sites — all enzymes in REBASE

Nucleora includes a suite of protein analysis tools:

• Molecular weight calculator — from sequence
• Isoelectric point (pI) calculator
• Extinction coefficient calculator — at 280 nm
• GRAVY score — grand average of hydropathicity
• Amino acid composition
• Peptide property calculator

Yes. The signal peptide prediction uses von Heijne 3-region scoring to:

• Identify N-terminal signal sequences
• Predict cleavage site position
• Score the n-region, h-region, and c-region

Nucleora also includes a curated library of secretion leaders for common applications (MHC I targeting, MHC II targeting, DC targeting).

Yes. Epitope analysis features include:

• Antigenicity prediction — identify immunogenic regions
• Hydrophilicity plots — surface-exposed regions
• Flexibility analysis

These help identify regions likely to elicit antibody responses for vaccine antigen design.

Yes. Nucleora includes a dedicated veterinary vaccine design workflow with:

• Species-specific codon optimization for livestock, companion animals, and wildlife
• Real codon usage tables from NCBI RefSeq for many species
• Documented clade proxies for species with limited genomic data
• Physiology-aware dosing estimates based on body weight

This makes Nucleora suitable for animal mRNA vaccine research in academic, zoo, and conservation settings.

Nucleora supports animal vaccine development for many species:

• Livestock: cattle, pigs, sheep, goats, chickens, horses
• Companion animals: dogs, cats, rabbits, ferrets
• Zoo animals: elephants (African & Asian), primates, big cats, bears, rhinos
• Conservation species: okapi, bongo, pangolins, and more (using documented proxies)
• Wildlife: deer, boar, bats

Species with very few sequenced genes are flagged with a "low data" warning.

For species with sufficient RefSeq data (typically 40,000+ mRNAs), Nucleora builds real codon usage tables from genomic data. This includes:

• Elephants — both African and Asian, ~100k+ RefSeq transcripts each
• Most primates — chimps, gorillas, macaques
• Common livestock — cattle, pigs, sheep, chickens

For species with limited data (e.g., okapi with ~1 RefSeq mRNA), Nucleora uses a documented clade proxy (cattle for okapi) and flags this explicitly.

Yes. The manufacturing simulator includes allometric scaling estimates:

• µg mRNA per dose by species weight class
• Number of doses from a given IVT reaction scale
• Adjustments for different administration routes

Note: These are research estimates based on published scaling factors, not regulatory guidance.

In vitro transcription (IVT) is the process of synthesizing mRNA from a DNA template using T7 RNA polymerase. Simulating it before wet-lab work helps:

• Identify sequence features that reduce yield (homopolymer runs, premature termination signals)
• Estimate reagent quantities and costs
• Predict yield at different reaction scales
• Plan manufacturing runs efficiently

The IVT readiness checker scans your construct for manufacturing issues:

• T7 promoter presence and correct positioning
• +1 initiation efficiency — G or A at the transcription start
• Premature termination risks — poly-U runs, T7 terminator-like motifs
• dsRNA/immunostimulation risk — U content, loopback structures
• ORF integrity — frame, start codon, stop codon, internal stops
• Homopolymer runs — long stretches that cause polymerase problems
• Cryptic poly(A) signals — AAUAAA upstream of the tail
• Cap compatibility — +1/+2 sequence vs. cap analog

Each issue is graded by severity with suggested fixes.

Yes. The IVT yield model estimates production based on:

• Reaction scale (µL, NTP concentration, template amount)
• T7 polymerase units and lot activity
• Temperature and incubation time
• Cap method (co-transcriptional vs. enzymatic)
• Transcript length and base composition
• Quality penalties from the readiness checker

Output: estimated µg and mg yield, plus vaccine doses at a configurable µg/dose.

Yes. The simulator produces an IVT kinetics time-course showing:

• T7 elongation rate (temperature-dependent: ~60 nt/s at 25°C to ~230 nt/s at 37°C)
• Time to synthesize one transcript
• Saturating yield curve: Y(t) = Ymax(1 − e^−t/τ)
• Approximate time to reach 80% maximum yield

Note: This is an empirical model, not a mechanistic kinetic simulation.

Yes. The bill of materials generator itemizes reagents for your reaction:

• Linearized DNA template (amount)
• T7 RNA polymerase (units)
• NTP mix (per-base masses, including modified nucleotides)
• Cap analog (if co-transcriptional)
• Poly(A) polymerase (if tail not encoded)
• Buffer, RNase inhibitor, pyrophosphatase, DNase
• Purification kit

Each line shows quantity and indicative cost (labeled as estimates). Export as CSV or plain text.

Nucleora connects to major biological databases:

• NCBI — nucleotide, protein, gene (via Entrez)
• UniProt — protein sequences with annotations
• Ensembl — genes, transcripts, sequences (multi-species)
• PDB/RCSB — protein structures

Search by gene name, protein name, accession number, or keyword.

Yes. The deep-sequence fetcher auto-detects ID types:

• UniProt IDs — P12345, Q9Y6K1
• NCBI accessions — NM_001234, NP_001234, NC_000001
• Ensembl IDs — ENSG00000139618, ENST00000275493
• PDB IDs — 1ABC

The correct database is queried automatically based on the ID format.

Yes. When fetching from UniProt, Nucleora extracts:

• Signal peptide positions
• Domain annotations
• Transmembrane regions
• Active sites
• Post-translational modifications

These are normalized into features that display on the sequence map.

Nucleora's lab bench simulation features include:

• Virtual agarose gel — visualize restriction digests, PCR products
• In-silico PCR — predict amplicons from primer pairs
• Peptide property calculator — MW, pI, extinction coefficient
• Pairwise alignment — compare optimized vs. original sequences

These help validate designs before ordering reagents.

The virtual gel electrophoresis simulates band migration:

• Configure agarose percentage (0.5% to 3%)
• Load multiple samples (digests, PCR products, ladders)
• See band positions based on fragment size
• Includes RNA denaturing gel mode for mRNA
• TapeStation electropherogram style available

Predicted band positions help identify unexpected fragments before running real gels.

Yes. In-silico PCR finds primer binding sites and predicts amplicons:

• Locate forward and reverse primer annealing positions
• Predict amplicon size
• Flag off-target binding sites
• Check for mispriming

Use this to verify primers will amplify the expected region.

Nucleora supports exporting constructs in standard formats:

• GenBank (.gb) — with annotations, SnapGene-compatible
• FASTA — plain sequence
• GFF3 — standard annotation format
• CSV — primer lists, order forms
• PDF — construct spec sheets with maps and properties

Yes. Nucleora's GenBank export is formatted to be SnapGene compatible:

• Standard .gb format that SnapGene can open
• /note and color qualifiers for feature display
• Round-trip import/export tested

You can design in Nucleora and view in SnapGene, or vice versa.

Yes. The synthesis order automator generates:

• Vendor-specific CSV templates (Twist, IDT, GenScript)
• Manufacturability pre-checks
• Automatic fragmentation for sequences over synthesis length limits
• Repeat-breaking suggestions

Yes. The construct spec-sheet PDF includes:

• Circular or linear map
• Peptide properties (MW, pI, extinction coefficient)
• IVT manufacturability report
• Lineage/provenance information
• SHA-256 hash and timestamp for documentation

Generated using reportlab for consistent formatting.

SnapGene is a commercial desktop application for molecular cloning and sequence visualization. Nucleora differs in several ways:

• mRNA focus: Nucleora is built around mRNA vaccine and therapeutics design, with IVT simulation, LNP guidance, and modified nucleotide support — features not in SnapGene
• Codon optimization: Nucleora includes built-in multi-algorithm codon optimization; SnapGene requires external tools
• Price: Nucleora is free; SnapGene licenses cost hundreds per year
• Cloning: SnapGene has more advanced cloning history and some cloning wizards not yet in Nucleora

Many users find them complementary — design mRNA in Nucleora, view plasmids in SnapGene.

Benchling is a cloud-based platform for molecular biology and lab management. Compared to Nucleora:

• Privacy: Nucleora is local-first (sequences never uploaded); Benchling is cloud-based
• Scope: Benchling is a full LIMS with inventory, notebooks, and team collaboration; Nucleora focuses on sequence design
• mRNA tools: Nucleora has deeper mRNA-specific features (IVT simulation, cap checking, LNP guidance)
• Cost: Nucleora is free; Benchling has free and paid tiers

ApE is a free, lightweight plasmid editor popular in academic labs. Compared to Nucleora:

• Features: Nucleora has more tools (530+ vs. ApE's core set)
• mRNA design: Nucleora has full mRNA construct design; ApE is plasmid-focused
• Codon optimization: Built into Nucleora; not in ApE
• Interface: Nucleora has a modern web interface; ApE has a traditional desktop UI

Geneious is a comprehensive bioinformatics platform. Compared to Nucleora:

• Scope: Geneious covers NGS analysis, phylogenetics, and more; Nucleora focuses on design
• Cost: Geneious costs $500–2000+/year; Nucleora is free
• mRNA tools: Nucleora has deeper mRNA-specific features
• Learning curve: Nucleora is simpler for vaccine design workflows

Nucleora is built with:

• Python backend — Flask server, BioPython, ViennaRNA bindings
• Browser frontend — vanilla JavaScript, no framework dependencies
• Local architecture — runs as a localhost web app
• Simple launcher — no command-line setup required

No technical expertise is required to use Nucleora.

Nucleora is currently in active development and not yet available for download. Request early access to be notified when builds become available.

When released, Nucleora will use a simple double-click launcher — no command-line setup required.

ViennaRNA provides Nucleora's RNA folding capabilities. It's included as a Python binding (via conda or pip). If ViennaRNA is unavailable on your system, Nucleora:

• Falls back to simpler folding estimates where possible
• Displays a warning that some features are limited
• Continues working for non-folding features

primer3 powers Nucleora's primer design. If the primer3-py wheel isn't available for your platform, Nucleora:

• Uses a built-in fallback for basic primer design
• Maintains Tm calculation and dimer checking
• Displays a note about the fallback

Yes. Nucleora includes gRNA design features for CRISPR applications:

• Cas9 guide design — find NGG PAM sites and design 20-nt spacers
• Cas12a guide design — TTTV PAM sites
• Off-target scoring — predict potential off-target sites
• Efficiency scoring — predict on-target activity

Yes. For gene knockin applications, Nucleora can design:

• Homology arm positions based on your cut site
• Configurable arm lengths (typically 500–1000 bp each)
• Insert positioning between arms
• Primers for amplifying donor constructs

Current support for base editing and prime editing is limited to sequence analysis — identifying potential target sites. Full pegRNA design with extension/PBS optimization is on the roadmap but not yet implemented.