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Does Bioinformatics have any relationship with protein modeling and simulation?

In other words, is there a research area where Bioinformatics uses protein modeling and simulation to achieve its goal or vice versa?

Note: No wet lab, only computer-based modeling, and simulation. E.g., Molecular Dynamics and Coarse-Grain Modeling with Monte Carlo for protein design.

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  • $\begingroup$ I would say computational Biophysics deals with computer-based modeling and simulations. One thing I know about bioinformatics is that they look at the genome or sequence data and use tools like BLAST to get an idea of what the function of the protein could be. Sometimes they would even find a sequence motif that is crucial for the functioning of the protein. $\endgroup$
    – Vasista
    Commented Mar 4, 2023 at 11:19

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Yes - protein and RNA folding has been a subject of research in bioinformatics for several decades, and have received much development in the last couple of years due to application of machine learning. Let me add a few more detailed comments:

  • Application of machine learning in bioinformatics is not a recent invention - see, e.g., Bioinformatics: The Machine Learning Approach is a book published more than two decades ego, outlining the main uses of ML in bioinformatics, including protein and RNA folding. Of course, the general development of machine learning methods, computational capacities and importantly sequencing technologies in the last two decades mean that the topic is still very much relevant - but there is a lot to learn.
  • When it comes to protein and RNA structure, there is a significant overlap between bioinformatics and biophysics, since predicting protein structure requires understanding and modeling of how amino-acids bind together, the mechanisms of this binding, etc. So sometimes one uses term computational biology, using bioinformatics in a narrower sense, as the subject concerned only with sequence analysis and mostly with the lower end sequence analysis (cleaning data, mapping reads, sequence assembly, etc.)
  • RNA structure prediction is a domain in itself, rather different from protein modeling. There are some rather original and by now classical contributions here, compulsory in nearly every bioinformatics course, - like Nussinov algorithm or the use of context-free grammars - see, e.g., the book by Durbin et al. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids.

I could suggest a few of my posts in other communities for further exploration:
What are the applications of DNA or RNA pattern matching?
How to model RNA-DNA and DNA-DNA binding as a “string matching" problem in statistical physics?
Does physics explain why the laws and behaviors observed in biology are as they are?

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