Ligands and Proteins and Assays! Oh My!



Over the past few weeks of 20.109, I have learned many new lab and analytic skills that will make me a better researcher and bioengineer. But mostly, I learned how to curb frustration when the FKBP12 does not show up on the SDS-PAGE, create coherent notebook entries that detail the day's experiment(s), and explain why almost none of our data was significant using scientific writing.

And I’ve had a blast in the process!

From the beginning I couldn’t wait to spend hours in lab study ligand-binding interactions with our protein of interest FKBP12…

…instead, at the end my partner and I spent more time trying to figure out why our 
ligands didn’t bind.

*an accurate representation of attempted ligand-FKBP12 binding*

We worked so hard and for so long for unexpected and, honestly, disappointing results. 
Such is the life of a scientist.

Lab can be exhausting and long, and from day one, the most challenging aspect of the class for me has been time management.


Figure 1: My time in lab over the duration of Module 1 of 20.109. With recently acquired figure-making skills in Excel and PowerPoint, I constructed a figure of my time in lab. As you can see, I still struggle a lot with unit conversions. 

Next time, I hope to find more time to construct a more thorough lab notebook to reference later. Completing lab notebook entries while working on the lab itself is ideal, though it doesn’t always get done.

Even more exhausting than lab is data analysis. Though we were given so many options on how to interpret our results of the assays, the sheer amount of data was a bit overwhelming. And trying to put it all together to tell a cohesive, comprehensive and concise story for the data summary was a new and challenging experience.

Three most important things I learned when summarizing Mod 1 data:
  1. Just because a comparison might be statistically significant doesn’t mean it’s relevant to what happened. 
  2. Creating a title that accurately represents your data and conveys your take-home message is actually super hard but makes the summary. 
  3. A lot of stuff goes wrong in lab, but that’s okay as long as you can explain how and why it may have affected your results.


But when all was said and done, I loved seeing everything come together.

With the help of my lab partner, the BE Comm Lab, and the wonderfully patient 20.109 staff, completing the lab assignments has become increasingly doable and enjoyable. The collaborative nature of 20.109 enhances my overall learning and allows me to feel comfortable in the once unfamiliar lab setting.

I also like feeling independent while working through lab protocols or making figures to interpret the data. I like completing labs that don’t follow “cookie cutter” instructions and I like trying to work out what the next step in the procedure will reveal about our experimental conditions.  

And even when the data didn’t follow the trend we expected, I still enjoyed the process.

That’s why we all love science. Even when your hypothesis is wrong or the data shows an unusual trend, when can make an educated guess as to what happened, how it deviated from what we expected, and what we can do next time.


Since coming to MIT, I have found the most challenging classes here tend to be the most rewarding and the most fun. So far, 20.109 has fit this trend, and I can’t wait for the rest of the semester!

- Marissa McPhillips

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