Week 8: A Clearer Picture

Aditya L -

Hey everyone, welcome back to my blog!

To briefly recap last week, the results were strange. The computer predicted that environmental pollutants can bind better than human molecules, but the experiment did not yield this result. Over the past week, we analyzed the pollutant’s docking to Rhodopsin over multiple states to see which parts of the computer and experiments align.

The beginning part of this week (last Wednesday) started by setting up the experiment to study the Rhodopsin interactions over a much shorter time-frame, which would allow us to properly assess the experimental binding at different stages.

  1. Between Thursday and Monday, while the experiments were still in-progress, I competed in the Arizona Science and Engineering Fair with a different project. While my project was about Bird flu and AI models, I noticed that there are a lot of interesting projects across Arizona, which are also testing how environmental pollutants interfere with humans and ecosystems. One project was using molecular docking simulations (which are dynamic computer simulations that look at the protein changing over time) to see how environmental pollutants can disrupt transmembrane proteins and intercellular proteins. This experience was fun for me because I got to see students presenting research in various categories (Robotics to Plant Science), and also learned about how to use Molecular Dynamics simulations in my current senior project as well.
  2. Yesterday, the results for our shortened simulation came in, and the results supported my hypothesis to a degree. Initially, when the Rhodopsin protein does not have a molecule and is inactive, the environmental pollutant instantly binds to Rhodopsin and outcompetes the human molecule (11-cis-retinal). Then, after adopting a conformational change to the ‘active state,’ the environmental pollutant is released prematurely. This turns the Rhodopsin protein back into an inactive structure, which ends up binding with the weaker 11-cis-retinal. These experiments show that the computer-predicted results were accurate in identifying that the environmental pollutant binds better than the human molecule, but didn’t account for the molecule getting detached prematurely.

Keeping these results in mind, I will be dedicating the next couple of weeks to understanding why the pollutant prematurely detaches, while the human molecule stays attached until the end of the process.

Thanks for reading, and see you next week!

Sincerely,

Aditya

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    alisha_j
    Hi Aditya! It looks like you are making excellent progress on your previous hypothesis. You mentioned that you would be investigating the reasons behind the premature detachment of the pollutant in the coming weeks. Do you have any initial thoughts or theories based on your current understanding and research?
    April 3, 2025 at 6:03 pm - Reply
      aditya_l
      Thanks for reading, Alisha! Yes, so I believe when the dark-state becomes activated and changes into the light-state, the shape of the protein expands. Even though the dark-state engages more interactions with Benzo[A]Pyrene, these interactions reduce due to spatial constraints which increases the distance of interactions within the protein. This would mean that the Benzo[A]Pyrene has a larger interaction distance (which means that it weakens) in the light-state, and ultimately gets released.
      April 11, 2025 at 10:38 am - Reply
    evangeline_c
    It is interesting to see how your experimental data is starting to align with the computer predictions! How do you think you will apply what you learn about Molecular Dynamics simulations at the Arizona Science and Engineering Fair to your senior project?
    April 7, 2025 at 11:35 am - Reply
      aditya_l
      Thanks for reading, Evie! I am not sure if I will be able to apply Molecular Dynamics simulations for this project (given that my project doesn't really require it at the moment, and given how energy inefficient dynamics simulations can be), but its definitely something that I will be exploring with other GPCR proteins (given that they are a bit more simpler to handle). Additionally, Rhodopsin is one of the oldest studied proteins so most of the 'dynamic simulations' have been captured as individual snapshots at multiple stages (which are ultimately easier to use). For other GPCR proteins, which may be relatively understudied, I would like to use molecular dynamics to simulate the process given that we don't have different snapshots at different times for the protein.
      April 11, 2025 at 10:41 am - Reply

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