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:
- Size exclusion
- 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):
- Ion exchange
- Affinity chromatography
- Hydrophobic interaction
- 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