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The work of the team of the University of Science and Technology of China has realized the original innovation of key core technologies in the frontier technology field of protein design, and laid a solid foundation for the design of functional proteins such as industrial enzymes, biomaterials, and biomedical proteins.
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Of these three papers, I think the one that needs to be introduced to the public is the one on protein design, because it belongs to the "original innovation of key core technologies." The authors of this article are Professor Haiyan Liu and Associate Professor Quan Chen of the HKUST Department of Life Sciences and Medicine, and the title of this article is "A backbone-centred energy function of neural networks for protein design." Isn't it inexplicable to listen to this title? The headline on HKUST's homepage is much easier to understand: "HKUST Establishes a New Protein De Novo Design Approach" (http://news.ustc.edu.cn/info/1055/78363.htm).
People who have been to high school know that protein is the basis of life, protein is composed of amino acids, and there are a total of 20 kinds of amino acids in proteins. Given an amino acid sequence, how is its spatial structure determined, and then how is its function determined? This is a positive problem, namely protein structure prediction. You can also ask in reverse: we want to achieve a certain function, we want to get a certain spatial structure, what kind of amino acid sequence will produce such a structure? This is the problem of the reverse, that is, protein design.
For practical purposes, it is clear that protein design is more useful and more difficult than structural prediction. For example, a protein has 100 amino acids, each location has 20 possibilities, and the total number of sequences is 20 to the power of 100, which is an astronomical number. How do you know which of these 20 amino acid sequences to the 100th power can perform a function? Waiting for the sun to explode one by one, you must look for fast algorithms.
My friend Dr. Cai Tao, the first author of synthetic carbon dioxide starch and an associate researcher at the Tianjin Institute of Industrial Biotechnology of the Chinese Academy of Sciences, is looking forward to protein design. Because their work depends on finding the right enzyme catalyst, enzymes are proteins. If they can quickly design enzymes that can catalyze a certain reaction, they can further improve the efficiency of carbon dioxide synthesis of starch, or create more miracles.
Cai Tao told me that he hoped that quantum computers could help them achieve this goal. I told him that quantum computers were far from practical. Now the good news is that before the quantum computer is practical, the method of Liu Haiyan and others is expected to take protein design a big step forward!
Why do designable skeleton structures exist in the world? It is conceivable that this is because the interaction that determines it is irrelevant to or insensitive to the sidechain. This suggests that we can construct such an energy function, which is completely determined by the skeletal structure and has nothing to do with the side chain. The specific implementation method is a neural network. Now you can understand what the title "Skeleton-centered Neural Network Energy Functions for Protein Design" means, right?
The energy function proposed by Liu Haiyan et al. is called SCUBA, which is an abbreviation for Side Chain-Unknown Backbone Arrangement, that is, "sidechain unknown skeleton arrangement". They also proposed a model called ABACUS, which means "abacus," but here is the abbreviation for A Backbone Based Amino Acid Usage Survey, which is "a skeleton-based amino acid use survey."
SCUBA is about finding out which skeletons can be designed without limiting the skeleton. ABACUS is the case of finding out which amino acid sequences correspond to this skeleton given the skeleton. Combined, the two form a completely new protein design route from scratch.
What are the benefits of this route? Compare it with the traditional practice. The traditional practice is called RosettaDesign, and it's a method designed by scientists at the University of North Carolina at Chapel Hill. In retrospect, natural proteins are all designable, but not vice versa. Their idea is to use the information of natural proteins as much as possible, and to use the natural protein structure as a template to stitch together. This is equivalent to swimming only in shallow water, safety can be guaranteed, but there are a lot of places that cannot be reached.
Liu Haiyan and the others reached the deep water area. They designed 9 proteins from scratch, measured their high-resolution crystal structure, and confirmed that their actual structure was consistent with the design model. Best of all, 5 of these proteins have novel topologies that have not yet been observed in native proteins. If you use traditional methods, you will never find these structures!
So The Nature reviewer commented: "Unlike existing methods, existing methods either use parametric equations to describe the space of predefined spiral structures, or methods based on fragment assembly rely on known protein fragments." The SCUBA method in principle allows one to explore arbitrary backbone structures and then populate sequences, allowing one to design a wider range of protein geometries than those observed in nature. "News report: The work of the team of the University of Science and Technology of China has achieved the original innovation of key core technologies in the cutting-edge scientific and technological field of protein design, laying a solid foundation for the design of functional proteins such as industrial enzymes, biomaterials, and biomedical proteins. Everyone appreciates the weight of these words!
Finally, I would like to say that I met Teacher Liu Haiyan more than 20 years ago when I was a doctor, and his hair was already gray. In the latest team photo, his hair is completely white. In fact, Teacher Liu was born in 1969 and is only 53 years old this year. From this white hair, you can see how hard he is.
When I was a doctoral student, I also met the founder of their team, Academician Shi Yunyu, who was the daughter of Mr. Shi Shiyuan, a predecessor of continental physics. Shi Shiyuan is the only doctor of physics trained by Marie Curie for China, and the teacher of Wu Jianxiong, the "Curie of China". The conditions in their 1930s and 1940s were very difficult, and the conditions were very limited when Professor Shi Yunyu opened up the direction of computational structural biology at HKUST. The hard work of generations can bear fruit: the sword blade comes out of the grinding, and the plum blossom fragrance comes from the bitter cold.