Part A. Conceptual Questions

• Answer any of the following questions by Shuguang Zhang:
  • How many molecules of amino acids do you take with a piece of 500 grams of meat? (on average an amino acid is ~100 Daltons)
  • Why humans eat beef but do not become a cow, eat fish but do not become fish?
  • Why there are only 20 natural amino acids?
  • Can you make other non-natural amino acids? Design some new amino acids.
  • Where did amino acids come from before enzymes that make them, and before life started?
    • There are 20 amino acids used in proteins by all living beings. Before they were discovered by breaking down and separating constituents of proteins, it is believed that amino acids were created from a mixture of molecules like ammonia, water, hydrogen, methane and electrical sparks. It is believed that this combination (primordial soup) also resulted in the evolution of single-cell organisms.
    • In addition, there is a belief that the left-handed chirality often found in amino acids found in life on earth could be from a certain meteorite (carbonaceous chondrites) which has an excess of left-handed isomers, although it is not known for certain.
    • Sources: https://www.nature.com/scitable/topicpage/an-evolutionary-perspective-on-amino-acids-14568445/#:~:text=In 1953%2C Miller and Urey,emerge from biosynthetic enzymatic reactions., https://astrobiology.com/2023/04/how-were-amino-acids-formed-before-the-origin-of-life-on-earth.html#:~:text=Currently%2C only a certain class,have originated from these meteorites.
  • If you make an alpha-helix using D-amino acids, what handedness (right or left) would you expect?
  • Can you discover additional helices in proteins?
  • Why most molecular helices are right-handed?
  • Why do beta-sheets tend to aggregate?
    • What is the driving force for b-sheet aggregation?
  • Why many amyloid diseases form b-sheet?
    • Can you use amyloid b-sheets as materials?
  • Design a b-sheet motif that forms a well-ordered structure.

Part B: Protein Analysis and Visualization

In this part of the homework, you will be using online resources and 3D visualization software to answer questions about proteins.

1. Pick any protein (from any organism) of your interest that has a 3D structure and answer the following questions.

pilA protein nanowire from geobacter sulfurreducens [https://www.uniprot.org/uniprotkb/Q74D23/entry#structure]

3D Structure of pilA from Uniprot:

• Briefly describe the protein you selected and why you selected it.

  • This protein nanowire comes from geobacter sulfurreducens and is can generate electricity from acetate and water, and is therefore used in biological energy generating applications, which I’m thinking to explore in my final project.

• Identify the amino acid sequence of your protein.

  • How long is it? What is the most frequent amino acid? You can use this notebook to count most frequent amino acid - https://colab.research.google.com/drive/1vlAU_Y84lb04e4Nnaf1axU8nQA6_QBP1?usp=sharing

    • Its length is 90AA.
    • Using the code from Colab and inserting the protein sequence:

    from collections import Counter
    
    # Protein sequence provided by the user
    protein_sequence = "MANYPHTPTQAAKRRKETLMLQKLRNRKGFTLIELLIVVAIIGILAAIAIPQFSAYRVKAYNSAASSDLRNLKTALESAFADDQTYPPES"
    # Removing spaces for proper analysis
    cleaned_sequence = protein_sequence.replace(" ", "")
    
    # Count the frequency of each amino acid
    amino_acid_count = Counter(cleaned_sequence)
    
    # Find the most common amino acid
    most_common_amino_acid = amino_acid_count.most_common(1)
    print(f"The most common amino acid is: {most_common_amino_acid[0][0]}, which appears {most_common_amino_acid[0][1]} times.")
    

    • The most common amino acid is: A, which appears 14 times.

    ---

  • How many protein sequence homologs are there for your protein?Hint: Use the pBLAST tool to search for homologs and ClustalOmega to align and visualize them. Tutorial Here

    • I followed the instructions to find the sequence homologs. There were 100 sequences found.

    seqdump.txt

    • Alignment by color coding:

    

  • Does your protein belong to any protein family?

    • Family: Glycoprotein, Type 4 Pilin 1

• Identify the structure page of your protein in RCSB

  • When was the structure solved? Is it a good quality structure? Good quality structure is the one with good resolution. Smaller the better (Resolution: 2.70 Å)
    • https://www.rcsb.org/structure/7TGG#entity-1
    • It was solved in 2022, and the resolution is 4.10 Å which is not good.
  • Are there any other molecules in the solved structure apart from protein?
    • There are no other molecules in the solved structure.
  • Does your protein belong to any structure classification family?
    • When searching in the above website, there were no results for the protein using the Uniprot ID (Q74D23)

• Open the structure of your protein in any 3D molecule visualization software:

  • PyMol Tutorial Here (hint: ChatGPT is good at PyMol commands)

  fetch 7TGG
  

  

  • Visualize the protein as "cartoon", "ribbon" and "ball and stick".
  • Cartoon:

  

  • Ribbon:

  

  • Ball and Stick:

  PyMOL>cmd.show("spheres"   ,"All")
  PyMOL>cmd.show("sticks"    ,"All")
  PyMOL>cmd.set("sphere_scale", 0.3, "All")
  PyMOL>cmd.set("stick_radius", 0.2, "All")
  

  

  • Color the protein by secondary structure. Does it have more helices or sheets?
  • More helices (blue) than sheets (red)

  

  • Color the protein by residue type. What can you tell about the distribution of hydrophobic vs hydrophilic residues?
  • The extended ‘arm’ has mostly hydrophobic residues, while the main folded structure is a mix of uncharged and hydrophobic residues.

  

  cmd.color("yellow", "resn ALA+VAL+LEU+ILE+MET+PHE+TRP+PRO")  # Hydrophobic residues
  cmd.color("blue", "resn ARG+LYS+HIS")  # Positively charged (basic) residues
  cmd.color("red", "resn ASP+GLU")  # Negatively charged (acidic) residues
  cmd.color("green", "resn ASN+GLN+SER+THR+TYR")  # Polar, uncharged residues
  cmd.color("cyan", "resn GLY")  # Glycine (special case)
  cmd.color("magenta", "resn CYS")  # Cysteine (sulfur-containing)
  

  • Visualize the surface of the protein. Does it have any "holes" (aka binding pockets)?
  • The surface is quite bumpy with many pockets, and has several potential binding sites.

  

Part C. Using ML-Based Protein Tools

<aside> <img src="/icons/snippet_lightgray.svg" alt="/icons/snippet_lightgray.svg" width="40px" /> Resources: https://colab.research.google.com/drive/1hXStRY9VCyw52n17uWdWQBj__IcR2ztK?usp=sharing#scrollTo=38gFJBazNdzJ

</aside>

• Fold your protein with AlphaFold or ESMFold or Boltz and compare it to the real structure.
• Comment on:
  • Any predicted vs. experimental differences.
  • Low-confidence regions and why do you think they are low confidence?