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fourth-year undergrad here so any help is super appreciated! Also this is not something I am working on for a grade, so pls don't think I am just looking for someone to do my homework lol!

In a gist, the project I am currently working on requires me to compare the same proteins involved in the Calvin cycle from both an extremophile and a mesophile. Specifically, I am supposed to figure out if the extremophile (which lives in the Arctic) protein's are more hydrophobic than the mesophile. I am expected just to use in sillico/bioinformatic techniques to figure this out

So far, all I have done is run the amino acid sequences through various hydrophobicity scales so each residue is given a ranking of hydrophobicity, then calculated an average from that. Obviously, this has a lot of flaws and is not proving to be very effective If anyone has any ideas of programs or methodologies that could produce more accurate results I would be so grateful! I have been going in circles with this for a while now

Thank-you!

Hannah Lye
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  • This question is hardly in the scope of Stack Overflow, which is about programing. And you can not just ask some code from scratch, this site is not a free code service. – PierU Aug 07 '23 at 13:59

1 Answers1

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Here are a few suggestions that might help you refine your analysis:

  1. Structure Prediction and Analysis: If the 3D structures of the proteins you're studying are known or can be predicted, you can use molecular dynamics simulations to analyze the behavior of the proteins in a water environment. This can give you insights into how the hydrophobic regions behave in different contexts.

  2. Phylogenetic Analysis: Compare the protein sequences using phylogenetic analysis. This can give you insights into how these proteins have evolved over time. If you see significant differences between the extremophile and mesophile sequences, it might indicate functional adaptations related to their environment.

  3. Machine Learning Approaches: Consider using machine learning algorithms to predict hydrophobicity or other related properties. You can train models on known data and then apply them to predict properties of your protein sequences. Tools like Python's scikit-learn or specialized bioinformatics libraries can be helpful.

  4. Hydrophobicity Scales Combination: Instead of using a single hydrophobicity scale, consider combining results from multiple scales to get a more comprehensive view. Some scales might be more accurate for certain types of sequences or proteins.

  5. Conservation Analysis: Analyze the conservation of hydrophobic regions across different species. If the hydrophobic regions are conserved in the extremophile but not in the mesophile, it might indicate a functional difference.

  6. Functional Site Prediction: Use tools that predict functional sites on proteins. This might give you insight into whether the hydrophobic regions play a role in the protein's function or interaction with other molecules.

7.Collaboration and Literature Review: Don't hesitate to reach out to experts in the field or consult scientific literature. You might find that other researchers have faced similar challenges and have devised effective methods or approaches.

Ketan
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