Prediction of LasR LBD-QslA from Pseudomonas aeruginosa using AlphaFold

( 3.5.26  )                                    Written by Gio Kim                          

During my trip to compete at my state HOSA, I had the fortunate opportunity to talk with Dr. Rahman, who introduced me to bioinformatics. With my interest in the intersection of biology and computers, with my programming skills in both Java and Python, talking with Dr. Rahman gave me an insight into the life of a researcher in the field of bioinformatics. With that, Dr. Rahman introduced me to a software he used to visualize proteins. After learning the basics of the program, I was able to visualize the protein LASR (check figure a), which is used in the pathogen Pseudomonas Aeruginosa to sense the autoinducer molecule 3OC12-HSL When bound to the signal, LasR dimerizes and binds DNA. This activates transcription of virulence genes (like elastase, pyocyanin, and biofilm factors). 

I started out by loading the PBD ID of the Crystal structure of LasR LBD-QslA, which then I formatted to make it look similar to the art style of David Goodsell’s “Molecule of the Month.” With this, I was able to view a snippet of the protein LASR.

Predicting the structure of Transcriptional activator protein LASR Chain A 

With the usage of AlphaFold, I was able to predict a 3D fold of that polypeptide, leading to figure B shown in the picture.  AlphaFold predicted multiple 3D folds of that polypeptide, until it landed on the best model.

Overall, this was an extremely enriching experience and I strongly believe in the future of the integration of AI and biology. I hope to continue growing my skills in this field and help others grow as well.

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References:

https://www.rcsb.org/structure/4NG2 (the protein database)

https://www.nature.com/articles/s41586-021-03819-2 (AlphaFold citation)