From: mk_thisisit
The 2024 Nobel Prize in Chemistry recognized Professor David Baker for his pioneering work in creating synthetic proteins [00:01:41]. His research, conducted at the Institute for Protein Design, marks a significant shift in biological engineering, moving it beyond relying solely on natural evolution [00:00:25].
The Genesis of Synthetic Proteins: Top 7
A pivotal breakthrough was the laboratory creation of Top 7, the world’s first protein designed entirely using a computer [00:00:12], [00:00:16], [00:01:44], [00:04:52], [00:05:06]. Unlike all previously known proteins that resulted from billions of years of natural evolution [00:00:09], [00:15:21], Top 7 demonstrated humanity’s ability to create entirely new protein structures from scratch [00:15:37], [00:15:46].
The name “Top 7” was given by its designer, Brian Kulman, who explored various protein topologies, with the seventh successful design being Top 7 [00:16:35], [00:16:42]. The confirmation that Top 7’s laboratory-created structure perfectly matched its computer model, achieved through X-ray crystallography, was an “extremely exciting stage” [00:05:32], [00:16:00], [00:16:07]. While Top 7 itself had no specific biological function, it opened the door to designing proteins with precise structures and new functions [00:15:53], [00:16:17].
Taking Biology Out of the Stone Age
Professor Baker likens current biological engineering to the “Stone Age” of technology [00:00:21], [00:08:47]. In the Stone Age, people sought existing natural solutions (e.g., a stick or stone) and made minor modifications [00:09:00]. Similarly, until recently, biological engineers would modify existing natural proteins [00:10:07].
Modern engineering, however, involves building solutions from scratch (e.g., bridges instead of logs, planes instead of modified birds) [00:09:30], [00:09:52]. The ability to design proteins from scratch, understanding the principle of protein folding, allows for the creation of completely new structures to solve specific problems, thereby “taking biology out of the Stone Age” [00:10:39], [00:10:49].
The “protein space”—the number of possible protein combinations—is immense; a protein 100 residues long with 20 amino acids results in 20^100 possible combinations [00:04:08]. The challenge lies in finding the best solutions within this vast space [00:04:23].
Impact and Applications of Designed Proteins
The possibilities opened by designed proteins are extensive [00:05:51], [00:06:12]:
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Medicine:
- Creation of precise drugs for effective disease treatment, minimizing side effects seen in therapies like anti-cancer treatments [00:06:16].
- Designing “universal vaccines” to strengthen resistance to various threats [00:06:27].
- Significant progress in disease treatment and more effective drugs [00:13:30].
- Advancements in genetic drugs and other exciting biological machines at the protein level [00:13:56].
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Ecology:
- Designing enzymes to break down plastic [00:04:41], [00:06:38].
- Neutralizing pollution [00:06:40].
- Removing greenhouse gases from the atmosphere to combat climate change [00:06:43], [00:08:26].
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Technology:
- Creation of innovative materials [00:06:54].
- Development of advanced measurement instruments [00:06:58].
- Developing new kinds of hybrid materials similar to teeth and bones [00:20:08].
- Creating catalysts for various chemical reactions [00:20:26].
The Interplay of Human Ingenuity and Artificial Intelligence
The 2024 Nobel Prize recognized the profound influence of artificial intelligence in various scientific fields [00:03:22]. Professor Baker’s work, while having roots before the AI era, has increasingly leveraged AI for design methods in recent years [00:03:31]. He shared the Nobel Prize with co-founders of DeepMind, who developed an AI system [00:03:03].
The protein folding problem, once a mystery, was significantly aided by an extensive database of about 200,000 protein structures, which serves as ideal material for deep learning methods [00:07:32]. These methods analyze data, identify patterns, and predict protein structures with high accuracy [00:07:41], [00:14:23].
Baker views his work and DeepMind’s as complementary rather than competitive [00:11:33]. DeepMind focuses on predicting protein structures, while Baker’s team focuses on designing them, even utilizing tools developed by DeepMind [00:11:12].
In this field, both human ingenuity and computer technology are vital [00:08:06]. Technology provides the tools, but humans decide which problems to solve and bring intuition to identify problems addressable by protein design [00:08:09], [00:08:35].
The Future of Scientific Discovery
Predicting the future of science and technology remains challenging, as breakthroughs often emerge unpredictably [00:12:43]. However, current research is focused on:
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Digitization of Smell: Work is underway to create synthetic olfactory receptors capable of detecting various molecules [00:17:51]. The goal is to embed these sensors directly into silicon chips, computers, and cell phones, connecting proteins with electronics [00:18:50], [00:19:01]. This “electronic nose” would surpass human olfaction, detecting far more compounds [00:19:43]. This represents a blend of biology and electronics [00:20:37].
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Artificial General Intelligence (AGI): While recognizing the rapid advancement of AI, such as GPT chats and large language models [00:14:34], Baker notes the difficulty in defining “superhuman artificial intelligence” [00:11:40]. He believes computers will increasingly perform tasks as well as or better than humans [00:23:06]. However, the nature of consciousness itself remains largely unknown, making it difficult to assess if AI could ever achieve consciousness [00:23:33].
The most challenging problem for humanity, as identified by Professor Baker, is not a scientific one, but rather how to foster cooperation among people to make the world a better place, given historical patterns of conflict [00:24:26].