For billions of years, evolution has been fine -tuning life at the molecular level. Protein is the basic foundation of life. Through this process, from the role, from resistance to infection to digestive food. These complex molecules include long chains arranged in accurate sequences, which determine their structure and functions. Although the extraordinary diversity of protein is naturally produced, understanding their structure and design new protein have always been a complicated challenge for scientists.
The latest progress of artificial intelligence is changing our ability to deal with the most important challenges in biology. In the past, AI was used to predict how the given protein sequences folded and perform-due to a large amount of configuration, this is a complex challenge. Recently, AI has improved a new protein that has been generated by unprecedented scale. ESM3 is implemented by a multi -mode generation language model ESM3 designed by EvolutionaryScale. Unlike the conventional AI system for text processing, ESM3 is trained to understand protein sequence, structure and function. What is really noticeable is that it can simulate the development of 500 million years, which has led to creating a brand new fluorescent protein, which has never been seen in nature.
This breakthrough is an important step to make biology more programmable and open up new possibilities to design custom proteins with medical, material science and other applications. In this article, we discussed the working principle of ESM3. Its achievements and why this progress has reshaped our understanding of biology and evolution.
Satisfy ESM3: AI that simulate evolution
ESM3 is a multi -mode model that understands and generate protein by analyzing its sequence, structure and function. Unlike Alphafold, which can predict the existing protein structure, ESM3 is essentially a protein engineering model that allows researchers to specify function and structure requirements to design new proteins.
The model’s in -depth understanding of protein sequence, structure and function, and the ability to generate protein through interaction with users. This ability gives the model that may not exist but may not exist but biologically feasible protein. Creating a new type of green fluorescent protein (ESMGFP) is an amazing demonstration of this ability. The fluorescent protein found in jellyfish and corals was widely used in medical research and biotechnology. In order to develop ESMGFP, researchers provide key structure and functional characteristics of known fluorescent protein for ESM3. Then, the model iterates the design and uses the thinking method to optimize the sequence. Although natural evolution may take millions of years to produce similar proteins, ESM3 accelerates this process to achieve it within a few days or weeks.
AI -driven protein design process
This is how researchers use ESM3 to develop ESMGFP:
- Prompt AI -News input sequences and structure prompts to guide ESM3 to reduce the characteristics of fluorescence.
- New type of protein -ESM3 explores huge potential sequences to produce thousands of candidate proteins.
- Filtration and improvement -The most promising design is filtered and synthesized for laboratory testing.
- Verification of living cells -Seled AI designed protein is expressed in bacteria to confirm its fluorescence and function.
Unlike anything in nature, this process leads to fluorescent protein (ESMGFP).
Comparison of ESMGFP and natural protein
The reason why ESMGFP is extraordinary is how far it is from the known fluorescent protein. Although most of the newly discovered GFP is slightly different from the existing GFP, ESMGFP’s sequence identity is only 58 % of its closest natural relatives. In terms of evolution, this difference corresponds to different time for more than 500 million years.
As a result, the protein of similar evolutionary distance appeared last time, the dinosaurs have not yet appeared, and the multi -cell life is still in the early stages. This means that AI not only accelerates evolution-it simulates a new evolutionary approach, which produces proteins that may never be created.
Why is this discovery important
This development is an important step in protein engineering and deepen our understanding of evolution. By simulating the development of millions of years in just a few days, AI is opening the door for exciting new possibilities:
- Faster drug discovery: Many drugs work by targeting specific proteins, but it is slow and expensive to find the right protein. The protein designed by AI can speed up this process and help researchers find new treatment methods more effectively.
- New solution to biological engineering: From decomposition plastic waste to detection of diseases, protein is used for protein. With AI -driven design, scientists can create custom proteins for medical care, environmental protection and even new materials.
- AI as an evolution emulator: One of the most interesting aspects of this research is that it positions AI as an evolutionary simulator, not just a tool for analysis. Traditional evolution simulation involves iteration through gene mutations, and usually requires several months or years to generate candidates. However, ESM3 bypasses these slow constraints by directly predicting functional protein. The change of this method means that AI can not only imitate evolution, but actively explore the possibility of evolution outside nature. In view of sufficient computing power, the evolution of AI drivers can find the new biochemical characteristics that have never existed in the natural world.
Moral consideration and the development of the person in charge
Although the potential benefits of AI -driven protein engineering are huge, the technology has also raised morality and security issues. What happens when AI starts to design an unspeakable protein? How can we ensure that these proteins can be used for medical or environmental use?
We need to focus on the responsible AI development and thorough test to solve these problems. Like ESMGFP, the protein generated by AI should conduct a wide range of laboratory testing before considering practical applications. In addition, the moral framework for AI -driven biology is developing to ensure transparency, security and public trust.
Bottom line
The launch of ESM3 is an important development in the field of biotechnology. ESM3 shows that evolution should not be a slow repeated test process. It can open a future in just a few days to compress the evolution of 500 million protein to a short day. Scientists can design new protein at the incredible speed and accuracy. The development of ESM3 means that we cannot just use AI to understand biology, and we can reshape biology. This breakthrough helps us improve the ability to program biological programming software, so as to solve the possibility we just started imagination.
