Biochemical controls: (Introduction)

by David Turell , Wednesday, October 09, 2024, 18:33 (43 days ago) @ David Turell

Predicting protein folds:

https://www.chemistryworld.com/news/explainer-why-have-protein-design-and-structure-pre...

In 1972, American biochemist Christian Anfinsen was awarded the Nobel prize in chemistry for his discovery that it is the sequence of amino acids that determines the way the polypeptide chain folds itself and that no additional genetic information is required. That means it should be possible, in theory, to predict the shape of a protein just by knowing its amino acid sequence. (my bold)

This finding led to 50-year-long quest to find a way to predict the 3D structure of a protein from its amino acid sequence – but the number of theoretically possible conformations of a protein is, in short, astronomical. (my bold)

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The work of these three scientists is closely interlinked. Hassabis and Jumper used artificial intelligence (AI) to predict the 3D structure of a protein from its sequence alone. Meanwhile, Baker developed computational methods that could solve the inverse problem: starting from a protein with a particular structure, figuring out what sequence it would have. That enabled him to create entirely new proteins that did not previously exist.

All of this work builds on the decades and decades of research – and chemistry Nobel prizes - on understanding the structure of proteins.

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When an amino acid sequence with an unknown structure is fed into the programme, it searches the database for similar amino acid sequences and protein structures. The network then creates an alignment of similar sequences, sometimes from difference species, and looks for correlations between them as well as possible interactions between amino acids. From this information AlphaFold2 can then iteratively refine a distance map - which tells you how close two amino acids are to each other in space – and sequence analysis. Finally, it then converts all that information into a 3D structure.

Now AlphaFold has more than 2 million users and has resulted in the prediction of 200 million protein structures.

Because of these breakthroughs, most monomeric protein structures can now be predicted with high fidelity, and large databases of hundreds of millions of structures have been created as a result. Proteins are such a key component of our biology that being able to design them and predict their structures opens up potential applications in pharmaceuticals, nanomaterials and rapid development of vaccines, as well as many others.

There’s no doubt that the development of AI protein structure prediction tools like AlphaFold represent an important milestone in structural biology, but they are not a replacement for experimental structure determination. Experimentally determined structures are still superior to predictions, and they will also be needed to generate the training datasets for the next generations of AI tools, as well as being used to assess the performance of those tools in predicting structures.

One example of the ongoing need for experimental approaches is in drug design. Although determining a protein’s structure may help generate ideas about what compounds to make next, there are many other factors regarding the biological activity of proteins to consider, such as pharmacokinetics, metabolism and toxicology, that can not currently be solved using AI.

Comment: From:
More miscellany Parts One & Two (Evolution)
by dhw, Tuesday, October 08, 2024, 11:29:

dhw: If they follow your God’s instructions, any mistakes are his. Exit your perfect, omnipotent, omniscient God.(See later.)

DAVID: The fault in reasoning is yours. The proteins make the mistakes trying to follow the instructions!!!

dhw: I don’t like this focus on proteins, since these are just one component of the cell and have to cooperate with other parts.

DAVID: A cell is all proteins in one form or another. The problem is folding in correctly. Proteins are free to do that.

[dhw]:I was a bit surprised to see this, so I googled and found “All cells are made from the same major classes of organic molecules: nucleic acids, proteins, carbohydrates, and lipids.” It doesn’t matter. Let’s just stick to cells.

So much for dhw's distain of the discussion about protein folding. This is a major key to how life functions. Organic molecules (bolded above) are made of amino acids which make up the folding results. Each fold designates a function. All proof of intricate design. Each molecular class listed above depends upon amino acids in construction.