Antifungal Extract Screening and Binding Models

ISEF Category: Microbiology

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

The Hook

A tiny change in dose can flip a microbe from thriving to stalled. That dose-response curve is the same idea behind many medicine studies, and you can test it with yeast. Natural extracts like propolis, garlic, and grapefruit-seed extract give you a real chance to compare chemistry, biology, and data fitting in one project.

What Is It?

This project asks how well different natural extracts slow yeast growth. Yeast are single-celled fungi, so you can use them as a simple model for antifungal screening. Think of them like a test crowd in a gym. If a compound slows their growth, you can measure how strong that effect is and how much compound you need before the effect really shows up.

The second part adds a prediction layer. Erg11, also called CYP51, is an enzyme fungi need to build cell membranes. If a compound binds to Erg11 well, it may block that enzyme and weaken the yeast. Docking is a computer method that predicts how strongly a molecule might fit into a target protein, a bit like testing whether the right key shape fits a lock.

Why This Is a Good Topic

This is a strong science fair topic because you can measure a clear biological response, growth inhibition, and pair it with a computational prediction. That gives you two angles on the same question, which makes your project feel deeper than a simple yes-or-no test. It also connects to real problems like fungal resistance and the search for new antifungal options. You can learn dose-response analysis, curve fitting, controls, and basic molecular docking without needing a full research lab.

Research Questions

• How does extract type affect the growth of Saccharomyces cerevisiae at different doses?
• What is the effect of propolis concentration on the Hill slope and half-maximal inhibitory dose?
• Does garlic allicin extract inhibit Saccharomyces boulardii more strongly than grapefruit-seed extract?
• To what extent do docking scores for Erg11 predict measured yeast growth inhibition?
• Which extract shows the steepest dose-response curve when tested against the same yeast strain?
• How does the predicted binding pattern to Erg11 change across the three extracts?

Basic Materials

• Yeast culture of Saccharomyces cerevisiae or Saccharomyces boulardii, sourced from a school or university lab.
• Sterile culture plates or microplates.
• Growth medium suitable for yeast.
• Propolis extract prepared in a known solvent.
• Garlic allicin extract or a standardized garlic extract source.
• Grapefruit-seed extract from a standardized commercial source.
• Micropipettes and sterile tips.
• Digital balance with milligram resolution.
• Incubator or temperature-controlled growth area.
• Spectrophotometer or plate reader for growth measurements.
• Blank solvent control.
• Positive antifungal control, if available through a lab supervisor.

Advanced Materials

• Clinical or reference Candida albicans strain, handled under approved lab supervision.
• Recombinant or purified Erg11 target data, if available through a research partner.
• High-performance liquid chromatography access for extract verification.
• LC-MS access for identifying active compounds in each extract.
• Reference antifungal drug for comparison.
• Docking-ready protein structure of Erg11 from a public database.
• Molecular modeling workstation.
• Negative and solvent controls for every assay batch.
• Sterile filtration setup for extract preparation.
• Automated plate reader with kinetic readout.

Software & Tools

• Python: Fits Hill-equation curves, compares doses, and plots inhibition data.
• ImageJ: Measures colony size or color change from plate images when optical density data are not available.
• AutoDock Vina: Predicts how strongly extract compounds may bind to Erg11.
• PubChem: Helps you find chemical structures and identifiers for likely active ingredients.
• R: Runs statistics, curve fitting, and confidence intervals for your results.

Experiment Steps

1. Define one yeast strain, one response metric, and one extract set so your project stays focused.
2. Identify the active or likely active compounds in each extract, then decide how you will standardize them.
3. Plan controls that separate true antifungal effects from solvent effects and nutrient effects.
4. Build a dose-response design with enough concentration points to fit a Hill equation cleanly.
5. Choose a docking workflow for Erg11, then decide which compounds or extract proxies you will compare.
6. Match the wet-lab results and docking results with the same comparison framework, so you can test prediction against measured inhibition.

Common Pitfalls

• Using a crude extract without standardization, which makes one batch stronger than the next.
• Confusing solvent toxicity with antifungal activity, which can fake a positive result.
• Testing too few dose levels, which makes Hill-equation fitting unstable.
• Comparing docking scores from unrelated compounds without checking whether they share a realistic target chemistry.
• Reading growth data from plates with uneven lighting or mixed incubation times, which creates noisy inhibition measurements.

What Makes This Competitive

A stronger version of this project goes beyond a basic screen. You compare multiple extracts with matched controls, fit full dose-response curves, and report confidence intervals, not just averages. You also test whether docking predictions line up with the measured inhibition ranking. If you verify extract chemistry, separate solvent effects, and use careful statistics, your project starts to look like real antifungal discovery work.

Project Variations

• Test the same extracts against baker's yeast and a non-pathogenic Candida surrogate to compare species-specific sensitivity.
• Swap growth inhibition for biofilm prevention, then compare whether the best extract changes when the target shifts from planktonic cells to surface-grown cells.
• Compare crude extracts with purified candidate compounds, then ask whether the mixture acts better than its main ingredient alone.

Learn More

• NIH PubMed: Search for review articles on antifungal natural products, Erg11, CYP51, and yeast-based screening.
• NCBI Protein Database: Find Erg11-related protein structures and sequence records through the NIH/NLM databases.
• PubChem: Look up compound structures, synonyms, and basic bioactivity data for allicin-related and plant-derived molecules.
• AutoDock Vina documentation: Read the free user guide for docking setup, scoring, and ligand preparation.
• MIT OpenCourseWare, molecular biology and biochemistry materials: Use free course notes to review enzymes, membranes, and protein-ligand interactions.
• NOAA and USDA reference materials: Use free plant and food chemistry references when you need background on extract sources and standardization.