Homework

Weekly homework submissions:

  • First, describe a biological engineering application or tool you want to develop and why. This could be inspired by an idea for your HTGAA class project and/or something for which you are already doing in your research, or something you are just curious about.
  • Your task this week is to Create a Python file to run on an Opentrons liquid handling robot. Review this week’s recitation and this week’s lab for details on the Opentrons and programming it. Generate an artistic design using the GUI at opentrons-art.rcdonovan.com. Using the coordinates from the GUI, follow the instructions in the HTGAA26 Opentrons Colab to write your own Python script which draws your design using the Opentrons. You may use AI assistance for this coding — Google Gemini is integrated into Colab (see the stylized star bottom center); it will do a good job writing functional Python, while you probably need to take charge of the art concept. If you’re a proficient programmer and you’d rather code something mathematical or algorithmic instead of using your GUI coordinates, you may do that instead.
  • Part A. Conceptual Question 1. 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) Meat contains about 20 - 25% protein by weight. For 500g of meat, that’s approximately: 500g x (20/100) = 100g of protein
  • Open the structure of your protein in any 3D molecule visualization software: PyMol Tutorial Here (hint: ChatGPT is good at PyMol commands) Visualize the protein as “cartoon”, “ribbon” and “ball and stick”. Color the protein by secondary structure. Does it have more helices or sheets? Color the protein by residue type. What can you tell about the distribution of hydrophobic vs hydrophilic residues? Visualize the surface of the protein. Does it have any “holes” (aka binding pockets)?
  • Part A: SOD1 Binder Peptide Design (From Pranam) 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. Your challenge: Design short peptides that bind mutant SOD1. Then decide which ones are worth advancing toward therapy. You will use three models developed in our lab: PepMLM: target sequence-conditioned peptide generation via masked language modeling https://colab.research.google.com/drive/1z37YcBtwhd-RzNrWaTiKUhTHwZGKzdGc?usp=sharing
  • Assignment: DNA Assembly Answer these questions about the protocol in this week’s lab What are some components in the Phusion High-Fidelity PCR Master Mix and what is their purpose? Phusion High-Fidelity PCR Master Mix is a pre-formulated reagent designed to streamline PCR setup while delivering accurate, high-yield amplification. It bundles all the core enzymatic and chemical components needed for PCR into a single 2X concentrated solution, so the only additions needed are primers, template, and water. The central component is Phusion DNA Polymerase, a thermostable enzyme derived from a archaeal source and engineered for exceptional fidelity. Unlike standard Taq polymerase, Phusion carries a 3’ to 5’ exonuclease (proofreading) activity that corrects misincorporated nucleotides during synthesis, resulting in an error rate roughly 50 times lower than Taq. This is especially critical in this lab because any unintended mutations outside the chromophore region could compromise protein folding or color expression.
  • Assignment Part 1: Intracellular Artificial Neural Networks (IANNs) 1. What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? Incoherent Analog Neural Networks (IANNs) represent a significant conceptual leap beyond traditional Boolean genetic circuits. Where Boolean circuits reduce biological signals to binary on/off states, IANNs exploit the full continuous, graded nature of molecular concentrations and reaction kinetics, enabling a far richer computational repertoire within living cells. Here is a structured academic overview of their key advantages.
  • Homework Part A: General and Lecturer-Specific Questions General homework questions 1. Explain the main advantages of cell-free protein synthesis over traditional in vivo methods, specifically in terms of flexibility and control over experimental variables. Name at least two cases where cell-free expression is more beneficial than cell production. 2. Describe the main components of a cell-free expression system and explain the role of each component. 3. Why is energy provision regeneration critical in cell-free systems? Describe a method you could use to ensure continuous ATP supply in your cell-free experiment. 4. Compare prokaryotic versus eukaryotic cell-free expression systems. Choose a protein to produce in each system and explain why. 5. How would you design a cell-free experiment to optimize the expression of a membrane protein? Discuss the challenges and how you would address them in your setup. 6. Imagine you observe a low yield of your target protein in a cell-free system. Describe three possible reasons for this and suggest a troubleshooting strategy for each.
  • Part A: The 1,536 Pixel Artwork Canvas | Collective Artwork Contribute at least one pixel to this global artwork experiment before the editing ends on Sunday 4/19 at 11:59 PM EST. A personalized URL was sent to the email address associated with your Discourse account, and you can discuss the artwork on the Discourse. If you did not have a chance to contribute, it’s okay, just make sure you become a TA this fall! 😉 Make a note on your HTGAA webpages including: what you contributed to the community bioart project (e.g., “I made part of the DNA on the bottom right plate”) what you liked about the project, and what about this collaborative art experiment could be made better for next year.’ I have participated in HTGAA Bioart 2026. It’s really amazing. Seems like, Science is not ONLY series; but also FUN.