Biological complexity: magic molecular reactions (Introduction)

by David Turell @, Sunday, June 07, 2020, 19:32 (1630 days ago) @ David Turell

It depends on enzymatic help, as previously described but also on molecular surface actions most of which involve two molecular reactikons:

https://www.quantamagazine.org/new-machine-learning-system-decodes-how-proteins-interac...

"Correia’s system, called MaSIF (short for molecular surface interaction fingerprinting), avoids the inherent complexity of a protein’s 3D shape by ignoring the molecules’ internal structure. Instead, the system scans the protein’s 2D surface for what the researchers call interaction fingerprints: features learned by a neural network that indicate that another protein could bind there. “The idea [is that when] any two molecules come together, what they’re essentially presenting to one another is that surface. So that’s all you need,” said Mohammed AlQuraishi, a protein researcher at Harvard Medical School who also uses deep learning. “It’s very, very innovative.”

***

"One version of the system, called MaSIF-site, can examine the whole surface of a protein and predict where another protein is most likely to bind, an approach similar to painting a target on a curved canvas. “It’s what we like to call the one-body problem,” Correia said. “You can think about this as a way to understand where the functional sites on a particular protein are.” MaSIF-site performed roughly 25% better at this task than two leading site-interaction predictors.

"Another version of the system, called MaSIF-search, tackles what Correia calls the many-to-many problem: Instead of predicting how one protein will fit together with one target molecule (as typically happens in docking simulations), the system compares the interaction fingerprints of many proteins to many others, looking for fits. (“In a cell you have 10,000 proteins, and many of them are bumping into each other all the time,” explained Correia.) On this task, MaSIF didn’t outperform a leading molecular-docking predictor; it found roughly half as many potential fits within a random set of 100 proteins. But the docking predictor needed nearly 100 days’ worth of computing time to perform its search. MaSIF took four minutes.

"That massive speedup “opens interesting possibilities” for basic research, said Bronstein. After all, in the human body, proteins form functional networks comprising tens of thousands of interactions. “Constructing these graphs takes a lot of time,” Bronstein said. “With methods [like MaSIF], it may only be an approximation, but it allows you to at least build some rough version of these protein-to-protein networks for any organism.”

"AlQuraishi noted that while MaSIF’s skin-deep approach to predicting protein interactions made sense, it wasn’t able to capture a phenomenon called induced fit: the way molecular surfaces change shape (and chemistry) when they get close to each other. In other words, the surfaces of two proteins may not exhibit complementary fingerprints until they’re already almost touching — a factor MaSIF will miss, since induced fit depends on the structure beneath a protein’s surface. “What evolution is probably optimizing for is precisely this induced fit,” said AlQuraishi. “What’s surprising about [MaSIF] is that even with this caveat, it still works pretty well.” (my bold)

"Incorporating induced fit and other surface dynamics into MaSIF is something Correia plans to explore. “To me it’s the last frontier of understanding [protein] function,” he said. “That’s probably how I’m going to be spending my next 10 years.'”

Comment: This article discusses new techniques in studying protein molecule functions in order to react together. What I have picked out are the actual molecular actions and reactions that occur constantly in cellular production of biologic products. Note my bold. These molecules have built-in automatic reactions. They do not think, but innately are built to produce what they have to do. What should be carefully remembered is these are molecule on molecule reactions. Most reactions require enormous enzyme molecules to force reactions that otherwise might take centuries to happen. None of this can develop by chance.


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