Repurposed Antibiotics for E. coli MurA

ISEF Category: Microbiology

Subcategory: Antimicrobials and Antibiotics  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

Some old drugs can hit new bacterial targets. That means a medicine designed for one job may still block a key enzyme in E. coli. You can turn that idea into a real research project by ranking repurposed compounds in a computer model, then testing the best low-cost picks in the lab.

What Is It?

This project asks a simple question, which off-patent drugs might stick to MurA, a bacterial enzyme needed to build the cell wall? If MurA gets blocked, the bacterium cannot make a strong wall, so it struggles to grow. Think of MurA like a worker at the first step of a brick wall assembly line. If the worker stops, the whole wall falls apart.

You start with virtual docking. Docking software estimates how well a small molecule fits into a protein pocket, a bit like testing keys in a lock. A better fit usually means stronger predicted binding, although real biology is messier than a screen on a computer. Then you move to disk diffusion, where you place drug-soaked disks on bacteria and measure whether growth slows around them. That second step checks whether the computer hit also does something useful in a living system.

Why This Is a Good Topic

This is a strong science fair topic because you can test a clear prediction, compare many compounds with the same method, and connect the work to antibiotic resistance. The question matters in the real world because new antibiotics are hard to make, and repurposed drugs can be faster and cheaper to study. You can learn docking, ranking, control design, and basic antimicrobial testing without needing to invent a new drug from scratch.

Research Questions

• How does docking score vary across off-patent drugs when screened against MurA from E. coli?
• What is the effect of compound cost on whether a top-ranked docked drug is practical to test next?
• Does docking rank predict disk-diffusion inhibition strength for the same repurposed compounds?
• To what extent do structurally similar off-patent drugs cluster into the same binding pattern at the MurA active site?
• Which physicochemical properties best predict whether a repurposed drug gives a measurable zone of inhibition?
• To what extent does the ranking change when you compare MurA docking against a second bacterial protein target?

Basic Materials

• Computer with internet access and enough memory to run docking software or access a web-based docking platform.
• Free ligand and protein structure files from PubChem, DrugBank summaries, ZINC, and the Protein Data Bank.
• Open-source molecular viewer such as PyMOL or UCSF ChimeraX.
• Docking software such as AutoDock Vina.
• Spreadsheet software for ranking hits and tracking properties.
• Digital calipers or a metric ruler for measuring inhibition zones.
• Bacterial culture access, sterile disks, agar plates, and basic microbiology supplies through a school or partner lab.
• Personal protective equipment, including gloves, eye protection, and lab coat.

Advanced Materials

• Access to E. coli strain and approved antimicrobial testing setup.
• Certified biosafety cabinet and incubator.
• MurA protein structure file and optional protein preparation tools.
• High-quality docking workstation with GPU support if needed.
• LC-MS or HPLC access for compound identity confirmation, if available.
• Plate imaging setup with fixed lighting and calibration grid.
• Statistical software for enrichment analysis and ranking validation.
• Reference antibiotics for comparison controls.

Software & Tools

• AutoDock Vina: Predicts binding poses and scores for each compound against MurA.
• UCSF ChimeraX: Helps you inspect the protein pocket and check docked poses.
• PyMOL: Lets you compare binding interactions and make clear figures.
• PubChem: Gives structure, synonym, and property data for candidate compounds.
• R or Python: Organizes docking results, plots rankings, and compares them with disk diffusion data.

Experiment Steps

1. Define the exact MurA structure, compound library, and scoring rule you will use so your screen stays consistent.
2. Set your filters for cheap, off-patent, and purchasable compounds before you start ranking.
3. Build a docking workflow that gives every compound the same preparation, search space, and output format.
4. Plan a short list of top hits plus matched negative controls so you can test whether rank predicts biology.
5. Design your validation analysis around inhibition zones, compound cost, and structure-property patterns, not just one score.
6. Decide how you will compare docking predictions with lab results, including what counts as a true hit and a weak hit.

Common Pitfalls

• Using poorly prepared ligand structures, which can create fake docking scores that look better than they should.
• Comparing docked compounds without normalizing for charge, size, or solubility, which can bias the ranking.
• Picking only the top score and ignoring compounds that are affordable or actually purchasable.
• Running disk diffusion with compounds that do not spread well through agar, which can hide real activity.
• Treating one inhibition zone as proof of mechanism, when diffusion, stability, and bacterial uptake can also affect the result.

What Makes This Competitive

A stronger version of this project does more than rank compounds. It tests whether docking scores, cost, and real inhibition all line up, then asks where they do not. You can raise the level by using matched controls, a second target, or a statistical model that predicts validation success from compound features. That gives you a real screening story, not just a list of molecules.

Project Variations

• Screen natural-product drugs from the same off-patent library and compare them with synthetic compounds.
• Dock against a second enzyme in the same cell-wall pathway and see whether multi-target hits survive validation.
• Replace disk diffusion with broth-based growth inhibition and compare how the assay choice changes hit ranking.

Learn More

• RCSB Protein Data Bank: Search for PDB 1UAE and read the structure details for MurA.
• PubChem: Find compound structures, synonyms, and basic property data for candidate drugs.
• NIH PubMed: Search for review articles on MurA inhibitors, antibiotic repurposing, and E. coli cell-wall biosynthesis.
• NCBI Bookshelf: Read free biology and microbiology textbook chapters on bacterial cell walls and enzyme inhibition.
• MIT OpenCourseWare: Search for molecular biology, biochemistry, or computational chemistry materials that explain docking concepts.
• Journal of Antimicrobial Chemotherapy: Search for peer-reviewed studies on repurposed antibacterials and validation methods.