Week 5 HW

Part A. SOD1 Binder Peptide Design

Superoxide dismutase 1 (SOD1) is a cytosolic antioxidant enzyme that converts superoxide radicals into hydrogen peroxide and oxygen. In its native state, it forms a stable homodimer and binds copper and zinc.

Mutations in SOD1 cause familial Amyotrophic Lateral Sclerosis (ALS). Among them, the A4V mutation (Alanine → Valine at residue 4) leads to one of the most aggressive forms of the disease. The mutation subtly destabilizes the N-terminus, perturbs folding energetics, and promotes toxic aggregation.

Challenge: Design short peptides that bind mutant SOD1, then decide which ones are worth advancing toward therapy.

Models used:

• PepMLM: target sequence-conditioned peptide generation via masked language modeling
• PeptiVerse: therapeutic property prediction
• moPPIt: motif-specific multi-objective peptide design using Multi-Objective Guided Discrete Flow Matching (MOG-DFM)

Part 1: Generate Binders with PepMLM

Retrieve the human SOD1 sequence from UniProt (P00441), introduce the A4V mutation, and use the PepMLM Colab to generate four peptides of length 12 amino acids conditioned on the mutant sequence. Add the known binder FLYRWLPSRRGG for comparison. Record perplexity scores.

A4V mutant SOD1 sequence (deleted M at position 1, changed A→V at position 4):

ATKVVCVLKGDGPVQGIINFEQKESNGPVKVWGSIKGLTEGLHGFHVHEFGDNTAGCTSAGPHFNPLSRKHGGPKDEERHVGDLGNVTADKDGVADVSIEDSVISLSGDHCIIGRTLVVHEKADDLGKGGNEESTKTGNAGSRLACGVIGIAQ

Generated peptides:

A note on perplexity: A lower perplexity score means higher model confidence that the peptide satisfies the criteria for binding the target.

Part 2: Evaluate Binders with AlphaFold3

Submit each peptide + mutant SOD1 as separate chains to the AlphaFold Server. Record the ipTM score and describe where each peptide appears to bind — does it localize near the N-terminus (A4V site), the β-barrel, or the dimer interface? Is it surface-bound or partially buried? In a short paragraph, describe the ipTM values and whether any PepMLM-generated peptide matches or exceeds the known binder.

Part 3: Evaluate Properties in the PeptiVerse

Using PeptiVerse, evaluate the therapeutic properties of each peptide against the A4V mutant SOD1 sequence. Check: predicted binding affinity, solubility, hemolysis probability, net charge (pH 7), and molecular weight.

The best peptide to advance for wet lab validation would be WRVGWVGVELKE due to its relatively high binding affinity (7.089, Medium).

Part 4: Generate Optimized Peptides with moPPIt

Using the moPPIt Colab: paste your A4V mutant SOD1 sequence, choose specific residue indices to target (e.g. near position 4, the dimer interface, or another surface patch), set peptide length to 12 aa, and enable motif + affinity guidance. Briefly describe how the moPPIt peptides differ from your PepMLM peptides. How would you evaluate these before advancing to clinical studies?

For the long execution time and computational resources required, the main advantage of moPPIt over PepMLM (in this context) is the motif score — there was no option to check motif specificity in PeptiVerse. All other properties of the PepMLM-generated sequences were comparable to the moPPIt peptides.

Part B. BRD4 Drug Discovery Platform Tutorial

(Optional — skipped)

Part C. Final Project: L-Protein Mutants

High level summary: The objective of this assignment is to improve the stability and auto-folding of the lysis protein of a MS2-phage. This mechanism is key to the understanding of how phages can potentially solve antibiotic-resistance.

Full instructions: Google Doc

Chose option 3: generating random mutations in the lysis protein while avoiding loss-of-function or nonsense codons. A Python script (Colab) was used to load active mutations from experimental data and apply them randomly to unique positions.

Generated sequences:

0. METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYVLIFLAIFLSKFTNQLLLSLLEAVIRTVTTLQQLLT (Original)
1. METRFPQQSQQTPASTNRRRPFKHEDYPCQRQQRSSTLYVLIFLAFFLSKFTNQLLLSLLEAVIRTVTTLQQLLT
2. METRFPQQSQQTLAATNRRRPFKHEDYPCRRQQRSSTLYVLIFLAIFLSKFTNQLLLSLLEAVIRTVTTLQQLLT
3. METRFPQQSQQTPASTNRRRPFKHGGYPCRRQQRSSTLYVLIFLAIFLSKFTNQLLLSLLEAVIRTVTTLQQLLT

AF2 Multimer was used to co-fold mutant sequence 1 with DnaJ. The plDDT score indicates low model confidence in the folding of the mutant L protein. Overall, the random mutation approach is very time-consuming for obtaining leads.