{"id":28562,"date":"2023-03-07T09:43:40","date_gmt":"2023-03-07T15:43:40","guid":{"rendered":"https:\/\/otech.uaeh.edu.mx\/noti\/?p=28562"},"modified":"2023-03-07T09:43:40","modified_gmt":"2023-03-07T15:43:40","slug":"scientists-are-using-ai-to-dream-up-artificial-enzymes-2","status":"publish","type":"post","link":"https:\/\/otech.uaeh.edu.mx\/noti\/ciencia\/scientists-are-using-ai-to-dream-up-artificial-enzymes-2\/","title":{"rendered":"Scientists Are Using AI to Dream Up Artificial Enzymes"},"content":{"rendered":"

One of my favorite childhood summertime memories is being surrounded by fireflies. As the sun set, their shimmering glow would spark up the backyard like delicate fairy lights. The fact that living beings could produce light felt like magic.<\/span><\/p>\n

But it\u2019s not magic. It\u2019s enzymes.<\/span><\/p>\n

Enzymes are the catalysts of life. They drive every step of our metabolism, power photosynthesis in plants, propel viruses to replicate\u2014and in certain organisms, trigger bioluminescence so they shine like diamonds.<\/span><\/p>\n

Unlike manmade catalysts, which help speed up chemical reactions but often require high heat, pressure, or both, enzymes are incredibly gentle. Similar in concept to yeast for baking, enzymes work at life-sustaining temperatures. All you need to do is give them a substrate and working conditions\u2014for example, flour and water\u2014and they\u2019ll perform their magic.<\/span><\/p>\n

It\u2019s partially why enzymes are incredibly valuable. From brewing beer to manufacturing medications and breaking down pollutants, enzymes are nature\u2019s expert chemists.<\/span><\/p>\n

What if we can outperform nature?<\/span><\/p>\n

This week,\u00a0a new study<\/a>\u00a0in\u00a0Nature<\/em>\u00a0tapped into AI to engineer enzymes from scratch. Using deep learning, Dr. David Baker\u2019s team at the University of Washington designed a new enzyme that mimics the firefly\u2019s ability to spark light, but inside human cells in Petri dishes. Overall, the AI \u201challucinated\u201d over 7,500 promising enzymes, which were further experimentally tested and optimized. The resulting light was bright enough to see with bare eyes.<\/span><\/p>\n

Compared to its natural counterpart, the new enzyme was highly effective, requiring just a little bit of substrate to light up the dark. It was also highly specific, meaning that the enzyme only preferred one substrate. In other words, the strategy could design multiple enzymes, each never seen in nature, to simultaneously perform multiple jobs. For example, they could trigger multiple-colored bioluminescence like a disco ball for imaging different biochemical pathways inside cells. One day, the engineered enzymes could also \u201cdouble-tap\u201d medicine and, say, diagnose a condition and test a treatment at the same time.<\/span><\/p>\n

\u201cLiving organisms are remarkable chemists. Rather than relying on toxic compounds or extreme heat, they use enzymes to break down or build up whatever they need under gentle conditions. New enzymes could put renewable chemicals and biofuels within reach,\u201d\u00a0said<\/a>\u00a0Baker.<\/span><\/p>\n

Proteins by Design<\/span><\/h2>\n

At their core, enzymes are just proteins. That\u2019s great news for AI.<\/span><\/p>\n

Back in 2021, the Baker lab developed an algorithm that accurately predicts protein structures based on the amino acid sequence alone. The team next nailed down\u00a0functional sites<\/a>\u00a0in proteins using trRosetta, an AI architect that imagines and then hones in on hot spots that a drug, protein, or antibody can grab onto\u2014paving the way for medications humans can\u2019t dream up.<\/span><\/p>\n

So why not use the same strategy to design enzymes and fundamentally rewire nature\u2019s biochemistry?<\/span><\/p>\n

Enzyme 2.0<\/span><\/h2>\n

The team focused on luciferase as their first target\u2014the enzyme that makes fireflies sparkle.<\/span><\/p>\n

It\u2019s not for childhood nostalgia: luciferase is widely used in biological research. With the right partner substrate, luminescent photons shine through the dark without the need for an external light source, allowing scientists to directly peek inside a cell\u2019s inner workings. So far, scientists have only identified a few types of these valuable enzymes, with many unsuitable for mammalian cells. This makes the enzyme a perfect candidate for AI-driven design, the team said.<\/span><\/p>\n

They set out with several goals. One, the new light-emitting enzyme should be small and stable in higher temperatures. Two, it needed to play well with cells: when coded as DNA letters and delivered into living human cells, it could hijack the cell\u2019s internal protein-making factory and fold into accurate 3D structures without causing stress or damage to its host. Three, the candidate enzyme had to be selective for its substrate to emit light.<\/span><\/p>\n

Selecting the substrates was easy: the team focused on two chemicals already useful for imaging. Both are in a family dubbed \u201cluciferin,\u201d but they differ in their exact chemical structure.<\/span><\/p>\n

Then they ran into problems. A critical factor to train an AI is tons of data. Most previous studies used open-sourced databases such as the\u00a0Protein Data Bank<\/a>\u00a0to screen for possible protein scaffolds\u2014the backbone that makes up a protein. Yet DTZ (diphenylterazine), their first luciferin of choice, had few entries. Even worse, changes to their sequence caused unpredictable results in their ability to emit light.<\/span><\/p>\n

As a workaround, the team generated their own database of protein scaffolds. Their backbone of choice started from a surrogate protein, dubbed NTF2 (nuclear transport factor 2). It\u2019s a wild bet: NTF2 has nothing to do with bioluminescence, but contained multiple pockets in size and structure feasible for DTZ to bind to\u2014and potentially emit light.<\/span><\/p>\n

The adoption strategy worked. With a method called \u201cfamily-wide hallucination,\u201d the team used deep learning to hallucinate over two thousand potential enzyme structures based on NTF2-like protein backbones. The algorithm then optimized the core regions of the binding pocket, while allowing creativity in more flexible regions of the protein.<\/span><\/p>\n

In the end, the AI hallucinated over 1,600 protein scaffolds, each better suited for DTZ than the original NTF2 protein. Next, with the help of\u00a0RosettaDesign<\/a>\u2014a suite of AI and other computational tools for protein design\u2014the team further screened for active sites for DTZ while keeping the scaffold stable. Overall, over 7,600 designs were selected for screening. In a matchmaker\u2019s dream (and a grad student\u2019s nightmare), the designs were encoded into DNA sequences and inserted into bacteria to test their enzymatic strengths.<\/span><\/p>\n

One winner reigned. Dubbed LuxSit (from the Latin for \u201clet light exist\u201d), it\u2019s compact\u2014smaller than any known luciferases\u2014and incredibly stable, retaining full structure at 95 degrees Celsius (203 Fahrenheit). And it works: when given its substrate, DTZ, the testing apparatus glowed.<\/span><\/p>\n

The Race for Designer Enzymes<\/span><\/h2>\n

With LuxSit in hand, the team next set out to optimize its ability. Focusing on its binding pocket, they generated a library of mutants in which each amino acid was mutated one at a time to see if these \u201cletter\u201d changes affected its performance.<\/span><\/p>\n

Spoiler: they did. Screening for the most active enzyme, the team found LuxSit-i, which pumps out 100 more photons every second onto the same area compared to LuxSit. The new enzyme also triumphed over natural luciferases, lighting up cells 40 percent more than naturally-occurring luciferase from the sea pansy\u2014a species that glow on the luminescent beaches on the warm shores of Florida.<\/span><\/p>\n

Compared to its natural counterparts, \u00a0LuxSit-i also had an \u201cexquisite<\/a>\u201d ability to target its substrate molecule, DTZ, with a 50-fold selectivity over another substrate. This means the enzyme played well with other luciferases, allowing researchers to monitor multiple events inside cells simultaneously. In a proof-of-concept the team proved just that, tracking two critical cellular pathways involved in metabolism, cancer, and immune system function using LuxSit-i and another luciferase enzyme. Each enzyme grabbed onto their substrate, emitting a different color of light.<\/span><\/p>\n

Overall, the study further illustrates the power of AI for altering existing biochemical processes\u2014and potentially designing synthetic life. It\u2019s not the first to hunt for enzymes with additional, or more efficient, abilities.\u00a0Back in 2018<\/a>, a team at Princeton engineered a new enzyme by experimentally mutating each \u201chotspot\u201d amino acid at a time\u2014a tedious, if rewarding attempt. Flash forward and deep learning is, cough, catalyzing the entire design process.<\/span><\/p>\n

\u201cThis breakthrough means that custom enzymes for almost any chemical reaction could, in principle, be designed,\u201d said study author Dr. Andy Hsien-Wei Yeh.<\/span><\/p>\n

Image Credit:\u00a0Joshua Woroniecki<\/a>\u00a0from\u00a0Pixabay<\/a><\/em><\/span><\/p>\n

Fuente:<\/p>\n

Fan, S. (2023b, febrero 28). Scientists Are Using AI to Dream Up Artificial Enzymes<\/i>. Singularity Hub. https:\/\/singularityhub.com\/2023\/02\/28\/scientists-are-using-ai-to-dream-up-artificial-enzymes\/<\/p>\n","protected":false},"excerpt":{"rendered":"

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