Protein Chemistry

Lecture 7 Paper 4

🧪 Chapter 1.V – Gel Permeation Chromatography (GPC)


🔹 1. What is Gel Permeation Chromatography?

💡 Core Idea

GPC (also called size exclusion chromatography) separates molecules based on their hydrodynamic size — not charge, not binding, just size in solution.

👉 Think of it like a molecular maze:

  • Big molecules → can’t enter pores → take shortcut → elute first 🚀
  • Small molecules → enter pores → take longer path → elute later 🐢

📌 From the file: small molecules can access ~90% of column volume, while large ones only access 25–35%


🧱 Matrix Structure (Page 1)

  • Column packed with porous beads
  • Made of:
    • Cross-linked agarose
    • Dextran (for strength)
    • Other polymers

📊 Key concept from Figure 1.40:

  • Molecules take different paths depending on size
  • Pores are irregular but controlled in distribution

🔹 2. Chromatography Matrix Requirements

To work properly, the matrix must be:

✔ Porous with defined pore size ✔ Insoluble in water ✔ Mechanically stable ✔ No nonspecific protein binding

📌 Common materials (Page 2):

  • Agarose (Sepharose)
  • Dextran (Sephadex)
  • Polyacrylamide
  • Silica-based matrices

💡 Important insight:

The matrix must not interact with proteins — otherwise separation is no longer purely size-based.


🔹 3. Separation Parameters ⚙️

🧪 Key Volumes (Page 4)

  • Vo (void volume) → outside pores
  • Vi (included volume) → inside pores
  • Vm (total volume) = Vo + Vi

📐 Distribution Coefficient

K_D = rac{V_e - V_o}{V_M - V_o}

Where:

  • Ve = elution volume (peak position)

Interpretation:

  • KD = 0 → completely excluded (large molecules)
  • KD = 1 → fully included (small molecules)

💡 Important:

KD is NOT a dissociation constant — it's a distribution constant


📊 Key Relationship:

V_e = V_o + K_D V_i

This is the fundamental equation of GPC


🧠 Conceptual Understanding

  • Larger Vi → better separation range
  • Typical limits:
    • Vi ≈ 3Vo (carbohydrate gels)
    • Vo ≈ 25% of Vm

🔹 4. What Does a Chromatogram Show?

📈 From Figure 1.43 (Page 3):

  • Peaks correspond to molecules of different sizes
  • Larger molecules → lower Ve → appear first
  • Smaller molecules → higher Ve → appear later

💡 Example: Glucose oligomers:

  • More units → larger → elute earlier

🔹 5. Calibration Curves 📏

🧪 How it works (Page 5)

  • Plot log(MW) vs Ve or KD
  • Use standard proteins

📌 Example proteins:

  • Catalase (300 kDa)
  • Albumin (68 kDa)
  • RNase (14 kDa)

🧠 Key Insight:

  • Globular proteins follow a smooth curve
  • Used to estimate unknown protein size

🔹 6. Shape Matters (VERY IMPORTANT) ⚠️

📌 From Page 6:

Not all proteins behave the same!

🔵 Globular proteins:

  • Compact → behave “normally”

🔴 Elongated proteins:

  • Appear larger than they are
  • Elute earlier than expected

👉 Why? They sweep a larger volume due to shape


🔥 Key takeaway:

GPC measures hydrodynamic size, not true molecular weight


🧪 Denatured proteins:

  • Unfold → become random coils
  • Appear much larger → elute earlier

🔹 7. Effect of Pore Size 🧱

From Figures 1.48–1.49:

Small pores:

  • Good for separating small proteins
  • Large proteins all elute together

Large pores:

  • Good for large proteins
  • Small proteins poorly resolved

💡 Rule:

Choose pore size based on target protein size range


🔹 8. Solvent Conditions 🧴

🧪 Standard conditions:

  • pH: 5–8
  • Salt: 50–200 mM NaCl

⚠️ Important effects:

Low salt:

  • Proteins aggregate → bad separation

Extreme pH or denaturants:

  • Proteins unfold

Chaotropic agents (urea, GuHCl):

  • Break structure → random coil

🔹 9. Ideal vs Non-Ideal Behavior

✅ Ideal behavior:

  • Separation depends ONLY on size

❌ Non-ideal behavior (Page 7):

Hydrophobic interactions:

  • Some molecules stick to matrix

👉 Example:

  • Aromatic peptides (Trp-containing)
  • Show KD > 1 (unexpected!)

🧠 Why?

Matrix is not purely hydrophilic:

  • Contains CH, CH2 → hydrophobic regions

🔥 Key Concept:

GPC can become bimodal separation:

  1. Size exclusion
  2. Hydrophobic interaction

🔹 10. Denaturation and Its Effects

🧪 What causes denaturation?

pH changes:

  • Low pH → lose negative charges
  • High pH → lose positive charges
  • Tyr can become negatively charged

👉 Result:

  • Disruption of:
    • Ionic interactions
    • H-bonds
    • Hydrophobic core

Chaotropic agents:

  • Urea, guanidinium chloride
  • Stabilize unfolded state

🧠 Structural consequence:

  • Native protein → compact sphere
  • Denatured protein → random coil

🔹 11. Hydrodynamic Volume Changes 📦

📊 Key finding (Page 11):

👉 Denatured proteins behave like:

  • ~3× larger molecular weight
  • ~1.5× larger radius

Example:

  • Small protein (native) → behaves like much larger protein when unfolded

🧠 Important insight:

GPC detects effective size in solution, not actual mass


🔹 12. Size of Denatured Proteins

Even though denatured proteins are flexible:

  • They still have a defined average size
  • So they elute reproducibly

📌 Calibration curves for denatured proteins are very smooth → behave like random coils


🔹 13. Practical Use of GPC

🧪 Main applications:

  • Protein purification
  • Molecular weight estimation
  • Checking aggregation
  • Studying folding/unfolding

🔁 Typical purification workflow (Page 11):

  1. Ion exchange
  2. Affinity chromatography
  3. Hydrophobic interaction
  4. Gel filtration (final polishing step)

🧠 BIG PICTURE SUMMARY

🔑 What GPC actually measures:

➡️ Hydrodynamic size (not mass)


🔑 What controls separation:

  • Pore size
  • Protein shape
  • Solvent conditions
  • Interactions (ideal vs non-ideal)

🔑 Key equations:

  • ( V_M = V_o + V_i )
  • ( K_D = rac{V_e - V_o}{V_M - V_o} )
  • ( V_e = V_o + K_D V_i )

🔑 Key pitfalls:

  • Shape effects
  • Aggregation
  • Hydrophobic interactions
  • Denaturation artifacts

🧩 Intuition to Remember

👉 Imagine:

  • Column = sponge 🧽
  • Big proteins = bounce off → fast
  • Small proteins = explore pores → slow

Quiz

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