1. Genetic Code & Amino-Acid Similarity 🧬

• The genetic code consists of 64 codons:
  • 61 encode amino acids
  • 3 are stop codons
• Amino acids with similar chemical properties cluster together in the codon table:
  • Non-polar amino acids cluster together
  • Polar, basic, and acidic amino acids also cluster

Why this matters

• Single-nucleotide mutations often change an amino acid into another with similar chemistry
• This buffers proteins against catastrophic functional loss
• Example: a hydrophobic amino acid often mutates into another hydrophobic one

2. Canonical, Rare, and Non-Natural Amino Acids 🧪

• 20 standard amino acids are used in proteins
• Two rare natural amino acids:
  • Selenocysteine
  • Pyrrolysine
• These are not expected to be memorized, but they demonstrate that biology can expand the genetic code

Non-natural amino acids

• Can be engineered into proteins
• Retain amino + carboxyl groups but have novel side chains
• Require genetic engineering
• Used to introduce:
  • Fluorescent probes
  • Crosslinkers
  • Novel chemical reactivity

3. Naming Systems & Mass Spectrometry ⚖️

• Amino acids have:
  • Full name
  • 3-letter code
  • 1-letter code
• Ambiguous notation:
  • Asx = Asparagine or Aspartate
  • Glx = Glutamine or Glutamate

Mass spectrometry problem

• Leucine and isoleucine have:
  • Identical molecular weight
  • Indistinguishable by MS alone
• Result: ambiguity in protein sequencing unless supported by DNA data

4. Hydrophobicity & Transfer Free Energy 🌊

Hydrophobicity is quantified by:

ΔG of transferring an amino-acid side chain from a hydrophobic to a hydrophilic environment

Key points

• Absolute ΔG values depend on experimental setup
• Relative order is conserved

Hydrophobic extremes

• Very hydrophobic: Phenylalanine, Leucine, Isoleucine
• Borderline: Glycine (tiny side chain)
• Strongly hydrophilic: Charged amino acids

Does hydrophobicity depend on pH?

• Generally no
• Exception: amino acids with titratable side chains (e.g. Lys, Asp, Glu)
• Protonation state changes → charge changes → hydrophobicity changes

5. Ionization, pKa, and pI 🔋

Example: Glycine

• Two ionizable groups:
  • α-carboxyl (~pKa ≈ 2)
  • α-amino (~pKa ≈ 9.6)
• pI ≈ 6 (net charge = 0)

Key definitions

• pKa: pH where 50% protonated
• pI: pH where net charge = 0

Amino acids with side-chain pKa

• Basic: Lys, Arg, His
• Acidic: Asp, Glu
• Special: Cys (~8.3), Tyr (~10.9)

6. Why Cysteine Is Exceptionally Reactive ⚡

This is a core concept.

pKa of cysteine ≈ 8.3

• At physiological pH (~7):
  • ~10% exists as thiolate (S⁻)

Consequences

• Thiolate is a very strong nucleophile
• Protonated thiol (–SH) is weak
• Even partial deprotonation is enough for reactivity

Functional impact

• Cysteine participates in:
  • Catalysis
  • Redox chemistry
  • Disulfide bond formation

Why tyrosine does not behave similarly

• pKa ≈ 10.9
• Almost no deprotonation at pH 7
• Negligible nucleophilicity in biology

7. Why Serine (or Cysteine) Is Placed Near Histidine 🧠

This explains catalytic triads.

• Serine and cysteine alone are weak nucleophiles
• Histidine acts as a general base
• Histidine:
  • Accepts a proton
  • Activates Ser-O⁻ or Cys-S⁻

Result

• Formation of a powerful nucleophile
• Enables peptide bond cleavage
• Core principle of:
  • Serine proteases
  • Cysteine proteases

8. pKa Is NOT Fixed in Proteins 🌡️

• pKa values listed in tables are for free amino acids in water
• In proteins, pKa shifts due to:
  • Nearby charges
  • Hydrophobic environments
  • Hydrogen bonding

Examples

• Acidic residue near negative charges → higher pKa → prefers protonation
• Acidic residue near positive charges → lower pKa → prefers deprotonation
• Hydrophobic environment → neutral state favored

Implication

• Protein pI cannot be predicted perfectly
• Must be measured experimentally
• Critical for purification (e.g. ion-exchange chromatography)

9. UV Absorption & Protein Concentration 📈

280 nm absorption

• Dominated by tryptophan
• Tyrosine contributes weakly
• Phenylalanine contributes minimally

210–220 nm absorption

• All peptide bonds absorb
• Allows concentration measurement even without aromatics
• Problem: many contaminants also absorb

10. Amino-Acid Analysis (Composition, Not Sequence) 🧪

• Proteins hydrolyzed:
  • 110 °C
  • 6 M acid
  • ~16 h
• Peptide bonds fully broken
• Amino acids derivatized with fluorescent tags
• Separated by chromatography
• Output:
  • Which amino acids
  • Their relative amounts
• Does not give sequence information

11. Amino-Acid Frequencies in Proteins 📊

• If random: each amino acid ≈ 5%
• Observed deviations:
  • Lysine: high frequency → flexible, easy to accommodate
  • Cysteine: low frequency → reactive, disulfide risk
  • Tryptophan: low frequency → bulky, rigid

12. Levels of Protein Structure 🏗️

1. Primary: amino-acid sequence
2. Secondary: α-helices, β-sheets, turns
3. Tertiary: 3D fold of one chain
4. Quaternary: multi-subunit assemblies

13. Peptide Bond Chemistry 🔗

• Formed by:
  • Nucleophilic attack of amino group on carboxyl carbon
  • Release of water
• Peptide bond has:
  • Partial double-bond character
  • Planarity
  • Dipole moment
• No free rotation around peptide bond

14. Cis vs Trans Peptide Bonds ⚠️

• Trans favored due to sterics
• Exceptions:
  • Glycine (tiny)
  • Proline (ring locks geometry)
• Cis–trans isomerization of proline:
  • Slow
  • Requires peptidyl-prolyl isomerases

15. Backbone Angles & Ramachandran Plot 📐

• Two rotatable angles:
  • φ (phi): N–Cα
  • ψ (psi): Cα–C
• Steric hindrance restricts allowed combinations
• Ramachandran plot shows:
  • α-helix regions
  • β-sheet regions
  • Disallowed zones

16. Secondary Structure Elements 🌀

α-Helix

• 3.6 residues per turn
• Hydrogen bond: i → i+4
• Rise: 1.5 Å per residue
• One turn: 5.4 Å
• Can be amphipathic
  • One hydrophobic face
  • One hydrophilic face
• Crucial for membrane proteins

β-Sheets

• Parallel or antiparallel
• Hydrogen bonds between strands
• Longer rise per residue (~3.5 Å)
• Connected by turns and loops

17. Amino-Acid Preferences for Secondary Structure 🧩

• α-Helix lovers: Ala, Leu, Met
• β-Sheet lovers: Val, Ile, Phe
• Turn/coil: Gly, Pro
• Proline:
  • Breaks helices
  • Promotes turns
• Collagen:
  • Extremely proline-rich
  • Forms specialized triple helices

Final takeaway 🎯

This lecture builds the chemical foundation of proteins:

• Why amino acids behave differently
• How environment controls charge and reactivity
• Why cysteine is rare but powerful
• How structure emerges from chemistry
• Why enzymes position residues precisely