Genetics & Molecular Biology — DNA, Mendelian Inheritance, Cell Division and CRISPR

Why Simulate Molecular Biology?

Molecular biology operates at scales invisible to any microscope you can point at a classroom slide. A single DNA replication fork moves at ~1 000 base pairs per second; a ribosome translates 10–20 amino acids per second; CRISPR-Cas9 finds its 20-nucleotide target in a genome of 3 billion base pairs. These numbers matter because they reveal the machinery of life — but they are hard to build intuition around from diagrams alone.

Animation bridges that gap. When you can watch the helicase unwind the double helix, see Okazaki fragments appear behind the lagging-strand polymerase, and then slow the animation to examine each enzyme in turn, the textbook diagram becomes a process you understand rather than a picture you memorise.

This spotlight walks through the six molecular biology simulations in the collection, grouped by scale: first the DNA molecule itself, then the cell as a whole, then inheritance across generations, then enzyme chemistry, and finally gene editing.

Layer 1: The DNA Molecule

DNA Replication

Every time a cell divides it must first make an exact copy of its entire genome. The DNA Replication simulation animates the replication fork: helicase unwinds and separates the double helix; primase lays short RNA primers; DNA Polymerase III follows the leading strand continuously and synthesises the lagging strand in discrete Okazaki fragments; and DNA ligase seals the nicks once each Okazaki fragment is complete.

Complementary base pairing:
  A ↔ T  (2 hydrogen bonds)
  G ↔ C  (3 hydrogen bonds)

Polymerisation direction: only 5′ → 3′
Leading strand: continuous synthesis in fork direction
Lagging strand: discontinuous — Okazaki fragments ~200 nt (eukaryotes)

Error rate of Pol III (before proofreading): ~10⁻⁵
Error rate after 3′→5′ exonuclease proofreading: ~10⁻⁷
Final genomic error rate (+ mismatch repair): ~10⁻¹⁰

The simulation lets you adjust playback speed and zoom into individual base pairs. Switch on "base pair mode" to see every A–T and G–C pair as the helicase passes. The progress tracker counts replicated base pairs in real time.

DNA Transcription

Once the DNA sequence exists, the cell reads selected genes and converts them into messenger RNA — a process called transcription. The DNA Transcription simulation shows RNA Polymerase progress along the template strand, assembling complementary mRNA nucleotides (A→U, T→A, G→C, C→G). As the polymerase moves, the DNA double helix re-forms behind it and the growing mRNA strand peels away.

DNA → mRNA base pairing (template strand read 3′→5′):
  A → U      T → A      G → C      C → G

Eukaryotic Pol II elongation rate: ~20–60 nt/s
Prokaryotic Pol elongation rate:   ~40–80 nt/s

Central dogma (simplified):
  DNA ──transcription──▶ mRNA ──translation──▶ Protein

Codon: triplet of mRNA bases; 4³ = 64 possible codons
       (encoding 20 amino acids + 3 stop codons)

Layer 2: The Cell

Mitosis and Meiosis

Reading the genome is only one requirement. Cells must also divide accurately, so each daughter cell receives a complete genome. The Mitosis & Meiosis simulation animates both division types across all phases: interphase → prophase → metaphase → anaphase → telophase → cytokinesis for mitosis; and the additional meiosis-specific stages that halve the chromosome number for sexual reproduction.

Mitosis (7 phases):
  Interphase → Prophase → Metaphase → Anaphase
  → Telophase → Cytokinesis
  Daughter cells: 2 × diploid (2n)  Purpose: growth, repair

Meiosis (10 phases, 2 divisions):
  Meiosis I (reductive): homologues separate → 2 × haploid(n)
  Meiosis II (equational): chromatids separate → 4 × haploid(n)
  Key event — crossing over: non-sister chromatid exchange
  during Prophase I → genetic recombination

Chromosome count example (human):
  2n = 46  →  Meiosis  →  n = 23 (gametes)

The simulation includes a phase-chip panel so you can jump to any stage, step through manually, or run the animation at adjustable speed. The spindle, nuclear envelope, chromosomes and cleavage furrow are all rendered on canvas with realistic proportions.

Layer 3: Inheritance Across Generations

Mendelian Genetics and Hardy-Weinberg Equilibrium

Mendel's pea-plant experiments in the 1860s established the rules of inheritance before anyone knew what DNA was. The Mendelian Genetics simulation implements both the monohybrid and dihybrid Punnett square, the Hardy-Weinberg equilibrium equations, and a Monte Carlo generator that draws 200 offspring from user-defined genotype frequencies.

Mendel's First Law (Segregation):
  Each organism carries two alleles; they segregate
  equally into gametes  →  p(A) + p(a) = 1

Mendel's Second Law (Independent Assortment):
  Alleles of different genes assort independently
  (when on non-homologous chromosomes)

Hardy-Weinberg equilibrium (no selection, mutation, drift):
  p² + 2pq + q² = 1      where p = freq(A), q = freq(a)
  → genotype frequencies: AA = p², Aa = 2pq, aa = q²

Condition for departure from H-W:
  ΔHet = 2pq(current) − 2pq(H-W) ≠ 0
  (inbreeding coefficient F measures excess homozygosity)

Five trait presets (petal colour, seed shape, blood type ABO, height co-dominance and sickle-cell anemia) cover both simple Mendelian and more complex co-dominance and incomplete dominance scenarios. The blood type preset correctly implements the three-allele IA/IB/i system.

Layer 4: Enzyme Chemistry

Enzyme Kinetics — Michaelis-Menten

Cells are not just copying information; they are constantly running chemical reactions, all catalysed by enzymes. The Enzyme Kinetics simulation visualises the Michaelis-Menten model of enzyme-substrate interaction, draws the Lineweaver-Burk double-reciprocal plot, and demonstrates three classes of inhibition: competitive, uncompetitive and non-competitive.

Reaction scheme:   E + S ⇌ ES → E + P
                        k₁     k₂
                        k₋₁

Michaelis-Menten equation:
  v = Vmax · [S] / (Km + [S])

  Vmax = k₂ · [E]total        (max velocity at substrate saturation)
  Km = (k₋₁ + k₂) / k₁      (substrate concentration at ½ Vmax)

Lineweaver-Burk (double reciprocal):
  1/v = (Km/Vmax) · (1/[S]) + 1/Vmax
  → y-intercept: 1/Vmax;  x-intercept: −1/Km

Inhibition types (competitive example):
  v = Vmax · [S] / (Km·α + [S])   where α = 1 + [I]/Ki
  → Km apparent increases; Vmax unchanged

The substrate-depletion curve view shows how product accumulates over time as substrate is consumed — a useful complement to the steady-state v-vs-[S] view that typically appears in textbooks.

Layer 5: Gene Editing

CRISPR-Cas9 Gene Editing

CRISPR-Cas9 is the most significant biotechnology development since PCR. The CRISPR simulation animates the molecular mechanism: the guide RNA (gRNA) searches the genome for a complementary 20-nucleotide protospacer sequence; Cas9 locks on, unwinds the local DNA, verifies the PAM site (NGG for SpCas9), and makes a double-strand break. The cell then repairs the break by either non-homologous end joining (NHEJ, error-prone) or homology-directed repair (HDR, precise).

Components:
  gRNA  = 20-nt spacer (matches target) + scaffold RNA
  Cas9  = endonuclease with RuvC and HNH nuclease domains
  PAM   = Protospacer Adjacent Motif (5′-NGG-3′ for SpCas9)

Target recognition:
  gRNA spacer pairs with non-template strand
  PAM must be immediately 3′ of target on non-template strand
  Cas9 unwinds ~20 bp and samples base-pair complementarity

Cleavage:
  HNH domain cuts non-template strand (+3 nt from PAM)
  RuvC domain cuts template strand
  → blunt-ended double-strand break (DSB)

Repair pathways:
  NHEJ:  error-prone ligation → indels → gene knockout
  HDR:   homology template provided → precise edit
         requires cell to be in S/G2 phase

The simulation includes an off-target scoring overlay: mismatches in the seed region (positions 1–10, counting from PAM) are weighted higher than proximal mismatches, reflecting empirical Cas9 fidelity data. Adjust the gRNA sequence and watch how the predicted off-target score changes in real time.

Complete Molecular Biology Collection

Cross-Collection Connections

Molecular biology does not exist in isolation. Several simulations in other categories connect directly to what this spotlight covers:

• Synapse Transmission — the proteins that form ion channels and vesicle-fusion machinery are translated from genes by the same machinery that the DNA Transcription sim shows.
• Pharmacokinetics — drug metabolism is primarily driven by cytochrome P450 enzymes; their kinetics follow Michaelis-Menten curves identical to those in the Enzyme Kinetics sim.
• Brownian Motion — thermal fluctuations at the scale of individual molecules drive the random walks that bring enzymes and substrates into contact; the same diffusion coefficient appears in both simulations.
• Prey-Predator Dynamics — the Lotka-Volterra equations that describe ecological population cycles are mathematically equivalent to the enzyme kinetics equations (both are mass-action rate laws).

Algorithms & Methods in This Collection