Protein Synthesis: Steps, Labeled Diagram & Simulator

Protein synthesis is how a cell builds a protein from the information stored in DNA, in two steps: transcription (DNA to mRNA, in the nucleus) and translation (mRNA to protein, on ribosomes in the cytoplasm).

Each three-base mRNA codon is read by a tRNA that carries one amino acid. The ribosome joins the amino acids with peptide bonds until it reaches a stop codon (UAA, UAG or UGA). A 300 amino acid protein costs about 1,200 high-energy phosphate bonds and takes about a minute in a human cell.

Rule of thumb: the site of protein synthesis is the ribosome. The first step is transcription in the nucleus; the second step is translation in the cytoplasm. Ribosomes add about 6 amino acids per second in human cells and about 15 per second in E. coli.

Protein synthesis definition (biology): protein synthesis is the process in which a cell reads the genetic code in a gene and uses it to join amino acids, in the right order, into a protein. It follows the central dogma of molecular biology: DNA makes RNA, and RNA makes protein. In simple words, protein synthesis means "building proteins from instructions".

What it measures here: this tool follows one gene through the whole process. It tells you which mRNA is made, which codons are read, which tRNAs arrive, which protein comes out, how heavy it is, and what it costs the cell.

A worked one-liner: the coding strand ATG GCT AAT CCG GGA TTC TAA is transcribed to the mRNA AUG GCU AAU CCG GGA UUC UAA, which is translated to Met-Ala-Asn-Pro-Gly-Phe, a 6 amino acid peptide of 635.74 Da that costs 24 high-energy bonds.

1.1 Protein synthesis diagram, labeled

1.2 Protein synthesis steps in order

1. Transcription (first step). RNA polymerase opens the DNA in the nucleus and copies the template strand into a matching mRNA. U replaces T.
2. mRNA processing (eukaryotes). A 5′ cap and a poly-A tail are added, and introns are cut out by splicing. The mature mRNA leaves the nucleus through a nuclear pore.
3. Translation initiation (second step begins). The small ribosomal subunit binds the mRNA and finds the start codon AUG. The initiator tRNA carrying methionine pairs with it, and the large subunit joins.
4. Elongation. A charged tRNA enters the A site. The ribosome makes a peptide bond, then moves 3 bases along the mRNA. The empty tRNA leaves from the E site.
5. Termination. A stop codon (UAA, UAG or UGA) enters the A site. A release factor frees the finished chain.
6. Protein processing. The chain folds, and may be cut, glycosylated or sent to the right place in the cell.

1.2a Transcription close up

1.2b The ribosome and its three sites

1.2c What tRNA does

1.2d The three stages of translation

1.3 Where does protein synthesis take place?

The site of protein synthesis is the ribosome. Ribosomes float free in the cytoplasm or sit on the rough endoplasmic reticulum (rough ER). The nucleus is involved because transcription happens there and it holds the DNA. Mitochondria and chloroplasts also have their own small ribosomes. In bacteria there is no nucleus, so transcription and translation happen together in the cytoplasm.

Who uses this tool: biology students learning the protein synthesis process, teachers making worked examples, geneticists checking what a mutation does to a protein, and lab scientists planning protein expression who need the expected size and A280 coefficient before running a gel.

4.1 What the protein sequence tells you

The protein is the direct product of the genetic code. Every three mRNA bases become one amino acid, so the protein sequence is fixed once you know the reading frame and the start codon. If the first amino acid is not methionine, translation did not start at a real AUG, and the result is a fragment rather than a natural protein.

4.2 Why the start codon matters

Real ribosomes scan from the 5′ end of the mRNA and usually start at the first AUG in a good context (the Kozak sequence in eukaryotes, the Shine-Dalgarno site in bacteria). The tool uses the first AUG by default. A CHECK on the start codon means the first AUG was not at position 1, which is normal for an mRNA with a 5′ untranslated region but worth noticing if you pasted a coding sequence.

4.3 Reading the stop codon verdict

A PASS means the chain ends at UAA, UAG or UGA, as a real protein does. A FAIL means no in-frame stop was found. In a cell, a ribosome that runs off the end of an mRNA stalls, and the cell destroys both the mRNA and the incomplete chain. A stop codon far earlier than expected points to a nonsense mutation.

4.4 Molecular weight and the band on your gel

The molecular weight is the sum of the residue masses plus one water. On average one amino acid adds about 110 Da, so a quick check is length × 110. A protein on SDS-PAGE can run 5 to 10% away from this value because of charge, glycosylation or a signal peptide that is cut off. The value here is for the unmodified chain with the starting methionine kept.

4.5 The energy cost of protein synthesis

Making proteins is the most expensive job a growing cell does. Charging each tRNA costs 2 high-energy bonds (ATP to AMP), each elongation cycle costs 2 GTP (EF-Tu and EF-G), and initiation and termination cost 1 GTP each. That gives about 4 bonds per amino acid. Proofreading and mRNA synthesis add more, so treat the figure as a lower limit.

4.6 How long protein synthesis takes

Speed depends on the organism. A ribosome adds about 6 amino acids per second in mammalian cells and 12 to 20 in E. coli. RNA polymerase II moves about 2 to 4 kb per minute. The time shown is for one ribosome; real mRNAs carry many ribosomes at once (a polysome), so a cell makes many copies in parallel.

4.7 GRAVY and the extinction coefficient

The GRAVY score is the average Kyte-Doolittle hydropathy. Values above 0 suggest a hydrophobic or membrane protein; most soluble proteins sit between −1 and 0. The extinction coefficient at 280 nm comes from tryptophan and tyrosine. When it is zero, A280 cannot measure the protein, and you need a Bradford or BCA assay instead.

4.8 Reading the mutation check

A silent change alters the DNA but not the protein. A missense change swaps one amino acid, as in sickle-cell disease (Glu to Val). A nonsense change creates an early stop and a short protein, as in many thalassaemias. A frameshift adds or removes bases in a number not divisible by 3, so every codon after it changes. The tool reports positions with methionine as residue 1 (HGVS style) and also gives the classic numbering where needed.

4.9 What this tool cannot tell you

It cannot predict splicing, so paste the coding sequence (cDNA), not the genomic gene with introns. It does not predict folding, post-translational modification, protein half-life, or how much protein a cell makes. For those you need experiments or dedicated prediction tools.

4.10 Practical judgement

Check four things before you trust the protein: it starts with Met, it ends at a stop codon, the frame has no leftover bases, and the length matches what you expect for the gene. If all four pass, the predicted protein is the one the cell makes from that mRNA.

▶ Run the analysis above to auto-fill all five examples with your results.

This flow chart shows protein synthesis step by step, from a DNA sequence to a finished protein with a mass and an energy cost. Every box uses the same worked example as the Excel, R and Python sections: the teaching gene ATGGCTAATCCGGGATTCTAA in a human cell.

Check any box yourself: the Excel sheet in Section 9, the R script in Section 10 and the Python script in Section 11 all return MANPGF, 635.74 Da and 24 high-energy bonds for this gene.

1. Load a sample or paste your sequence. Pick one of the ten sample datasets, or paste a DNA or mRNA sequence. FASTA headers, numbers and spaces are removed automatically.
2. Or upload a file. On the Upload tab choose a FASTA, CSV or Excel file, then pick the record, sheet, column and row to load.
3. Or type codons by hand. On the Manual Codon Table tab type one codon per cell and press Use these codons.
4. Say which strand you pasted. Choose coding strand, template strand (3 prime to 5 prime or 5 prime to 3 prime) or mRNA.
5. Choose where translation starts. Leave it on the first AUG to copy a real ribosome, or pick reading frame 1, 2 or 3.
6. Pick the cell type. Eukaryote or bacterium sets the ribosome and RNA polymerase speeds. Choose Custom to type your own.
7. Add a reference for a mutation check. Optional. Paste the normal gene to have the change named as silent, missense, nonsense or frameshift.
8. Press Run Protein Synthesis. Nothing is calculated until you press the button, and any change to the inputs clears old results.
9. Read the QC table and step through the ribosome. Check the PASS, CHECK and FAIL verdicts, then use Play to watch translation codon by codon.
10. Copy the report or download it. Sections 4, 5 and 18 fill in with your numbers. Download Doc gives a text report and Download PDF a print-ready page.

Excel has no "translate" function, but it can do the whole protein synthesis process with text functions and one lookup table. The easy parts are transcription (one SUBSTITUTE) and cutting codons (MID). The parts that trip people up are absolute references, the 64-row codon table, and Excel treating * as a wildcard.

9.1 The functions you need

9.2 Step by step

9.3 The awkward cases

• Long genes. One Excel cell holds at most 32,767 characters. A large gene or a whole mRNA can be cut off silently. Check with =LEN(A2) against the true length.
• The stop codon wildcard. In SUMIF and COUNTIF, * means "any text". =COUNTIF(E2:E30,"*") counts every amino acid, not the stops. Use "~*" to mean a real asterisk.
• Finding the start codon. =FIND("AUG",B2) gives the position of the first AUG. Then use MID($B$2,$K$1+3*(ROW()-2),3) with the start position in K1.
• Template strand input. Complement it with a chain of SUBSTITUTE calls through placeholder letters, otherwise A becomes T and then back into A.
• Codons past the stop. MID keeps cutting after the stop codon. TEXTBEFORE on the joined string removes them.

9.4 Why your Excel answer might differ from R or Python

9.5 Charting the result in Excel

Count each amino acid with =COUNTIF($E$2:$E$30,"M") and so on, select the 20 counts and insert a Clustered Column chart. For a publication figure, delete the gridlines and the chart title, and add axis titles "Amino acid" and "Count".

9.6 Excel errors you will probably hit

In R, Biostrings from Bioconductor does transcription and translation in one line each, but a bare translate() keeps going past the stop codon and gives no mass or energy. The script below is complete: it transcribes, translates to the first stop, computes the mass, energy, time and GC, prints a plain-English verdict and saves one 300 dpi figure.

Install once with install.packages("BiocManager") then BiocManager::install("Biostrings"). Biostrings is on Bioconductor, so install.packages("Biostrings") fails.

10.1 The complete script

R with Biostrings, saves protein_synthesis.png

# ============================================================
# Protein synthesis: DNA -> mRNA -> protein, with one figure
# StatsUnlock - https://statsunlock.com/protein-synthesis/
# Needs Biostrings:  install.packages("BiocManager")
#                    BiocManager::install("Biostrings")
# ============================================================
library(Biostrings)

# ---- 1. Your data ------------------------------------------
# Paste the coding (sense) strand, 5' to 3'. Or read a FASTA file:
#   coding <- readDNAStringSet("gene.fasta")[[1]]
#   coding <- DNAString(gsub("N", "", as.character(coding)))  # drop unknown bases
coding   <- DNAString("ATGGCTAATCCGGGATTCTAA")
label    <- "Teaching gene"
aa_per_s <- 6     # human cell; E. coli about 15
nt_per_s <- 40    # human cell; E. coli about 50

# ---- 2. Transcription --------------------------------------
template <- complement(coding)          # template strand, 3' to 5'
mrna     <- RNAString(coding)           # T -> U
start    <- start(matchPattern("AUG", mrna))[1]
orf      <- subseq(coding, start = start)

# ---- 3. Translation ----------------------------------------
full    <- as.character(translate(orf, if.fuzzy.codon = "solve"))
protein <- sub("\\*.*$", "", full)      # cut at the first stop
L       <- nchar(protein)
has_stop <- grepl("\\*", full)

# ---- 4. Mass, energy, time, GC -----------------------------
res <- c(A=71.0788, R=156.1875, N=114.1038, D=115.0886, C=103.1388,
         E=129.1155, Q=128.1307, G=57.0519,  H=137.1411, I=113.1594,
         L=113.1594, K=128.1741, M=131.1926, F=147.1766, P=97.1167,
         S=87.0782,  T=101.1051, W=186.2132, Y=163.1760, V=99.1326)
aa     <- strsplit(protein, "")[[1]]
mw     <- sum(res[aa]) + 18.01528
energy <- c(charging = 2 * L, initiation = 1,
            elongation = 2 * (L - 1), termination = as.numeric(has_stop))
gc     <- 100 * letterFrequency(coding, "GC") / length(coding)

cat("Sample:         ", label, "\n")
cat("mRNA:           ", as.character(mrna), "\n")
cat("Template 3'-5': ", as.character(template), "\n")
cat("Protein:        ", protein, " (", L, " aa)\n", sep = "")
cat(sprintf("Molecular wt:    %.2f Da\n", mw))
cat(sprintf("Energy:          %d high-energy bonds\n", sum(energy)))
cat(sprintf("Time:            %.2f s translation, %.2f s transcription\n",
            L / aa_per_s, 3 * (L + has_stop) / nt_per_s))
cat(sprintf("GC content:      %.2f %%\n", gc))
cat("Verdict:        ",
    if (substr(protein, 1, 1) == "M" && has_stop)
      "complete protein: starts with Met and ends at a stop codon\n"
    else "CHECK: no start Met or no in-frame stop codon\n")

# ---- 5. One publication-ready figure -----------------------
counts <- table(factor(aa, levels = strsplit("ACDEFGHIKLMNPQRSTVWY", "")[[1]]))
png("protein_synthesis.png", width = 9, height = 3.6, units = "in", res = 300)
par(mfrow = c(1, 2), mar = c(4.5, 4.5, 3, 1))
barplot(counts, col = "#0d9488", border = NA, las = 1,
        xlab = "Amino acid", ylab = "Count",
        main = sprintf("%s: %d aa, %.2f Da", label, L, mw))
barplot(energy, col = c("#d97706", "#0d9488", "#2563eb", "#9333ea"),
        border = NA, las = 2, ylab = "High-energy bonds", main = "Energy budget")
dev.off()

10.2 What each part does

10.3 What the figure shows

The left panel shows how many of each amino acid the protein contains; for the teaching gene every bar is 1 except the 14 absent amino acids. The right panel shows the energy budget: half of the cost is charging tRNAs and almost half is elongation, while initiation and termination are tiny.

10.4 Common R problems and fixes

10.5 Useful one-liners

translate(DNAString("ATGGCTAATCCGGGATTCTAA"))            # all codons, stop as *
translate(reverseComplement(DNAString("TTAGAATCCCGGATTAGCCAT")))  # from the template 5'-3'
GENETIC_CODE["ATG"]                                         # "M": the code table uses T, not U
codons(DNAString("ATGGCTAATCCGGGATTCTAA"))                 # split into codons
translate(dna, genetic.code = getGeneticCode("2"))        # vertebrate mitochondrial code
alphabetFrequency(translate(dna))                          # amino acid counts

In Python, Biopython's Seq object has transcribe() and translate() built in. The script below does the full protein synthesis process, prints the mRNA, template strand, protein, mass, energy, time, GC and a verdict, and saves one 300 dpi figure. It returns exactly the same numbers as the calculator, Excel and R.

Install once with pip install biopython matplotlib numpy.

11.1 The complete script

Python with Biopython, saves protein_synthesis.png

# ============================================================
# Protein synthesis: DNA -> mRNA -> protein, with one figure
# StatsUnlock - https://statsunlock.com/protein-synthesis/
# pip install biopython matplotlib numpy
# ============================================================
from Bio.Seq import Seq
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np

# ---- 1. Your data ------------------------------------------
# Paste the coding (sense) strand, 5' to 3'. Or read a FASTA file:
#   from Bio import SeqIO
#   coding = next(SeqIO.parse("gene.fasta", "fasta")).seq
#   coding = Seq(str(coding).upper().replace("N", ""))   # drop unknown bases
coding = Seq("ATGGCTAATCCGGGATTCTAA")
label = "Teaching gene"
aa_per_s, nt_per_s = 6, 40        # human cell speeds; E. coli about 15 and 50

# ---- 2. Transcription --------------------------------------
template = coding.complement()            # template strand, 3' to 5'
mrna = coding.transcribe()                # T -> U
start = str(mrna).find("AUG")             # first start codon
orf = mrna[start:]

# ---- 3. Translation ----------------------------------------
protein = str(orf.translate(to_stop=True))     # stops at UAA, UAG or UGA
L = len(protein)
n_codons = L + 1                               # plus the stop codon
has_stop = len(orf) >= 3 * n_codons and str(orf[3*L:3*L+3]) in ("UAA", "UAG", "UGA")

# ---- 4. Mass, energy, time, GC -----------------------------
res = dict(A=71.0788, R=156.1875, N=114.1038, D=115.0886, C=103.1388,
           E=129.1155, Q=128.1307, G=57.0519, H=137.1411, I=113.1594,
           L=113.1594, K=128.1741, M=131.1926, F=147.1766, P=97.1167,
           S=87.0782, T=101.1051, W=186.2132, Y=163.1760, V=99.1326)
mw = sum(res[a] for a in protein) + 18.01528
energy = {"tRNA charging": 2 * L, "initiation": 1,
          "elongation": 2 * (L - 1), "termination": 1 if has_stop else 0}
gc = 100 * (str(coding).count("G") + str(coding).count("C")) / len(coding)

print(f"Sample:          {label}")
print(f"mRNA:            {mrna}")
print(f"Template 3'-5':  {template}")
print(f"Protein:         {protein}  ({L} aa)")
print(f"Molecular wt:    {mw:.2f} Da")
print(f"Energy:          {sum(energy.values())} high-energy bonds {energy}")
print(f"Time:            {L / aa_per_s:.2f} s translation, "
      f"{3 * n_codons / nt_per_s:.2f} s transcription")
print(f"GC content:      {gc:.2f} %")
verdict = ("complete protein: starts with Met and ends at a stop codon"
           if protein.startswith("M") and has_stop
           else "CHECK: no start Met or no in-frame stop codon")
print(f"Verdict:         {verdict}")

# ---- 5. One publication-ready figure -----------------------
aas = "ACDEFGHIKLMNPQRSTVWY"
counts = [protein.count(a) for a in aas]
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(9, 3.6))
ax1.bar(list(aas), counts, color="#0d9488")
ax1.set_xlabel("Amino acid"); ax1.set_ylabel("Count")
ax1.set_title(f"{label}: {L} aa, {mw:.2f} Da")
ax2.bar(list(energy), list(energy.values()),
        color=["#d97706", "#0d9488", "#2563eb", "#9333ea"])
ax2.set_ylabel("High-energy bonds"); ax2.set_title("Energy budget")
ax2.tick_params(axis="x", rotation=25)
fig.tight_layout()
fig.savefig("protein_synthesis.png", dpi=300, bbox_inches="tight")

11.2 What each part does

11.3 What the figure shows

The left panel is the amino acid composition of the protein. The right panel splits the 24 high-energy bonds into charging (12), initiation (1), elongation (10) and termination (1). For a long protein the two big bars grow and the two small ones stay at 1.

11.4 Common Python problems and fixes

11.5 Useful one-liners

Seq("ATGGCTAATCCGGGATTCTAA").translate()                 # 'MANPGF*'
Seq("ATGGCTAATCCGGGATTCTAA").translate(to_stop=True)     # 'MANPGF'
Seq("TTAGAATCCCGGATTAGCCAT").reverse_complement().translate()  # from template 5'-3'
Seq(dna).translate(table=2)                               # vertebrate mitochondrial code
from Bio.SeqUtils import gc_fraction; gc_fraction(dna) * 100   # returns a fraction, so x 100
from Bio.SeqUtils.ProtParam import ProteinAnalysis; ProteinAnalysis("MANPGF").molecular_weight()

Run it from a terminal with python script.py. In Jupyter, drop the savefig line and add plt.show().

12.1 The standard genetic code (mRNA codons)

What to conclude: 61 codons code for 20 amino acids and 3 are stops (UAA, UAG, UGA). AUG is both the start codon and methionine. Most amino acids have several codons, so the code is redundant. Source: Nirenberg and Matthaei (1961); Crick et al. (1961).

12.2 Amino acids: codes, residue masses and hydropathy

What to conclude: residue masses range from 57 Da (Gly) to 186 Da (Trp), averaging about 110 Da. Positive hydropathy means water-avoiding. Sources: Kyte and Doolittle (1982); Pace et al. (1995).

12.3 Energy cost of each stage of protein synthesis

What to conclude: about 4 bonds per amino acid, and translation uses most of the energy budget of a fast-growing cell. Source: Lynch and Marinov (2015).

12.4 Speed of transcription and translation

What to conclude: bacteria translate about three times faster than human cells. Sources: Ingolia et al. (2011); Jonkers and Lis (2015).

12.5 Sites of protein synthesis in the cell

What to conclude: the ribosome is the organelle responsible for protein synthesis; the nucleus supplies the instructions. Source: Palade (1975).

12.6 Prokaryotic versus eukaryotic protein synthesis

What to conclude: antibiotics such as streptomycin and tetracycline target the 70S ribosome, which is why they spare human cells. Sources: Shine and Dalgarno (1974); Kozak (1987); Jackson et al. (2010).

12.7 Stop codons and release factors

What to conclude: no tRNA reads a stop codon in the standard code; a protein release factor does. Source: Schmeing and Ramakrishnan (2009).

Eight worked examples of protein synthesis, from a clean textbook gene to real disease mutations and a lab expression construct. Load any of them from the sample menu in Section 2 to see the full output.

Study design: a cell-free transcription and translation reaction makes the protein predicted above from a plasmid or PCR product, so you can check its size on a gel. The steps below use the NEB PURExpress kit (reconstituted E. coli system); the Promega TnT T7 Quick kit (rabbit reticulocyte lysate) works the same way with the volumes in brackets.

Prepare

1. Check the protein synthesis prediction first. Run your sequence in the simulator. You need a T7 promoter, a ribosome binding site or Kozak sequence, an AUG start and an in-frame stop codon. Write down the expected mass.
2. Prepare clean template DNA. Use 250 ng of plasmid (1 µg for TnT) purified with a miniprep kit and eluted in water, not TE: EDTA chelates the magnesium that ribosomes need. RNase-free tubes and tips only.
3. Thaw the kit on ice. Solution A and B (or the TnT master mix) stay on ice at all times. Never vortex the ribosome solution; flick to mix.

Set up

4. Assemble the 25 µL reaction on ice: 10 µL Solution A, 7.5 µL Solution B, 1 µL RNase inhibitor (20 U), template DNA, nuclease-free water to 25 µL. (TnT: 40 µL master mix, 1 µL 1 mM methionine, DNA, water to 50 µL.)
5. Include a positive and a negative control. The kit's DHFR control plasmid gives an 18 kDa band. A no-DNA reaction shows background bands.
6. Mix gently and spin down for 5 seconds so the whole volume sits at the bottom of the tube.

Run

7. Incubate for protein synthesis at 37 °C for 2 hours (TnT: 30 °C for 60 to 90 minutes). Longer does not help: the energy system runs down.
8. Stop on ice and take 2.5 µL into SDS loading buffer. Heat at 95 °C for 5 minutes (70 °C for 10 minutes for membrane proteins, which aggregate when boiled).
9. Run SDS-PAGE on a 4 to 20% gradient gel at 200 V for about 35 minutes with a prestained ladder, then stain with Coomassie or transfer for a Western blot against a tag.

Record

10. Compare the band with the predicted protein synthesis product. A band within about 10% of the predicted mass confirms translation. A shorter band suggests an early stop codon or a frameshift.
11. Record everything: plasmid ID, DNA concentration, kit lot, temperature, time, gel image file name and the simulator output line from Section 5.

Replicates: run each construct in duplicate reactions on the same day; 2 reactions plus the 2 controls fit one 10-well gel with a ladder. Common mistakes: template eluted in TE buffer, no stop codon in the construct, a missing T7 promoter, RNase contamination from bare hands, and boiling a membrane protein.

15.1 Four real examples

1. A biology student pastes the textbook gene to see each step of protein synthesis in order.
2. A clinical genetics trainee compares a patient HBB variant with the reference and gets "missense, p.Glu7Val".
3. A protein lab checks that a GFP construct gives a 26.9 kDa product before running a gel.
4. A teacher builds a quiz from the codon and anticodon table.

15.2 Experimental design guidance

Always paste the strand you are sure of, and say which one it is. Use the coding sequence from RefSeq or Ensembl (the CDS), not the whole mRNA, when you want the protein; use the full mRNA when you want to see the 5′ and 3′ untranslated regions.

15.3 Decision tree

Assumptions

1. The standard genetic code applies. Requires: a nuclear gene of most organisms. Check: the source organism and compartment. If it fails (mitochondria, some ciliates), UGA is read as Trp and AUA as Met, so the tool underestimates protein length by stopping too early.
2. The first AUG is the real start. Requires: a normal 5′ UTR with no upstream AUG. Check: the Kozak context. If it fails, the protein is shifted, too long or in the wrong frame.
3. The sequence has no introns. Requires: cDNA or a CDS. Check: compare with RefSeq. If it fails, intron bases are translated and the protein is wrong after the first exon, usually cut short by an intron stop codon.
4. The mass is for the unmodified chain. Requires: no cleavage or modification. Check: UniProt features. If it fails, a signal peptide makes the gel band smaller and glycosylation makes it larger than predicted.
5. Speeds are averages. Requires: steady growth. Check: cite the rate you used. Rare codons and stress slow ribosomes, so the time is a lower limit.
6. Energy is the textbook 4 bonds per amino acid. Requires: no proofreading cost. Proofreading and mRNA turnover add energy, so the cost is underestimated.

Limitations

1. No splicing prediction. Use a gene annotation (Ensembl, RefSeq) to get the CDS first.
2. No folding or 3D structure. Use a structure predictor or the Protein Data Bank.
3. No protein amount or expression level. Use RNA-seq, ribosome profiling or mass spectrometry.
4. One frame at a time. Use a six-frame ORF finder for unknown sequences.
5. Selenocysteine (UGA with a SECIS element) and pyrrolysine are read as stop codons. Use a selenoprotein predictor for those genes.

Protein synthesis is the two-step process that turns the information stored in DNA into working proteins. Transcription in the nucleus copies a gene into mRNA. Translation on the ribosome reads that mRNA three bases at a time, while tRNAs bring the matching amino acids, until a stop codon releases the finished chain.

The simulator on this page makes each step visible with a real sequence. It shows the mRNA, every codon and anticodon, the protein, its mass and its cost, and it checks the start codon, the stop codon and the reading frame so that you can trust the result. The mutation check shows in one line why a single base change can cause sickle-cell disease or thalassaemia.

Use it to learn the protein synthesis steps, to check a construct before an experiment, or to explain a mutation. Then come back to this protein synthesis simulator whenever you need to go from DNA to protein quickly and correctly.

The following peer-reviewed references support the methods, values and explanations used in this protein synthesis simulator.

1. Ban, N., Nissen, P., Hansen, J., Moore, P. B., & Steitz, T. A. (2000). The complete atomic structure of the large ribosomal subunit at 2.4 Å resolution. Science, 289(5481), 905–920. https://doi.org/10.1126/science.289.5481.905
2. Chang, J. C., & Kan, Y. W. (1979). β⁰ thalassemia, a nonsense mutation in man. Proceedings of the National Academy of Sciences, 76(6), 2886–2889. https://doi.org/10.1073/pnas.76.6.2886
3. Cock, P. J. A., Antao, T., Chang, J. T., Chapman, B. A., Cox, C. J., Dalke, A., Friedberg, I., Hamelryck, T., Kauff, F., Wilczynski, B., & de Hoon, M. J. L. (2009). Biopython: Freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics, 25(11), 1422–1423. https://doi.org/10.1093/bioinformatics/btp163
4. Crick, F. (1970). Central dogma of molecular biology. Nature, 227(5258), 561–563. https://doi.org/10.1038/227561a0
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