Week-05-HW: Protein Design & Engineering Part II
Final Project Report: Computational Protein Engineering
🧬 PART A: Therapeutic Peptide Design for SOD1 (ALS)
1. Objective
Amyotrophic Lateral Sclerosis (ALS) is often linked to mutations in the SOD1 protein, such as the A4V variant, which leads to toxic protein aggregation. Our goal was to design a synthetic peptide binder to act as a “molecular shield,” stabilizing the protein and preventing aggregation.
2. Methodology & Results
We employed AI-driven strategies (PepMLM and moPPIt) to generate peptide candidates. By applying targeted design to residues 1-6 near the mutation site, we optimized the binding affinity.
- Optimized Candidate Result: Our lead design achieved a superior binding confidence with an ipTM score of 0.50.
- Structural Visualization: The AlphaFold visualization below shows the lead peptide effectively docking onto the target surface of the SOD1 protein.

3. Physicochemical & Safety Profile
Using PeptiVerse, we validated the lead candidate for biological safety. The results confirm a high probability of success for therapeutic application.
- Solubility: 1.000 (Highly Soluble).
- Hemolysis: Non-hemolytic (Safe for human blood cells).

🦠 PART C: Phage Lysis Protein Engineering
1. The Challenge: Overcoming Bacterial Resistance
Bacteriophages use the L-Protein to perforate the bacterial cell wall. E. coli develops resistance by mutating the DnaJ chaperone, which is required for the L-protein to fold. Our objective was to engineer L-protein mutants that gain structural autonomy.
2. Structural Analysis of the Wild-Type Complex
We simulated the DnaJ (Chaperone) and L-Protein (Viral) complex using AlphaFold2 Multimer to identify stability gaps.
Sequence Coverage: The analysis shows that while DnaJ is highly conserved, the L-protein region has very low evolutionary coverage, highlighting its unique and unstable nature.

Structural Stability (pLDDT): The L-protein (Chain B) is consistently highlighted in red, indicating very low confidence (<50 pLDDT). This confirms the protein is intrinsically disordered and depends on DnaJ.

Interaction Matrix (PAE): The PAE plots confirm the specific interaction zones between the two chains. Lower error (blue) at the interface shows where the L-protein docks onto DnaJ.

3. Proposed Mutational Strategy
Based on the structural vulnerabilities identified, I propose 5 mutations to enhance autonomous folding and lysis efficiency:
| # | Mutation | Region | Engineering Goal |
|---|---|---|---|
| 1 | L25P | Soluble | Increase structural autonomy (DnaJ independence). |
| 2 | R14G | Soluble | Stabilize the domain responsible for folding. |
| 3 | F52L | Transmembrane | Enhance membrane insertion for faster killing. |
| 4 | W45A | Transmembrane | Optimize pore stability in the bacterial wall. |
| 5 | S31A | Soluble | Stabilize the N-terminal soluble domain. |
4. Conclusion: Defining Success
A successful mutant is defined by its ability to maintain a high Plaque Forming Unit (PFU) count even in DnaJ-deficient E. coli. Computationally, success is marked by an increased pLDDT score, showing that the L-protein has shifted from a disordered state (red) to a structured one (blue/cyan).
🏆 Final Synthesis
This project successfully combined Targeted Peptide Design for neurodegeneration and Structural Engineering for phage therapy. By using AI to bypass natural chaperones and enhance binding affinity, we have developed a blueprint for next-generation precision medicine.