▎ WuXi AppTec content team editor
In a paper released this week by the top academic journal Nature, the research team led by Professor Liu Haiyan and Associate Professor Chen Quan of the University of Science and Technology of China showed a new route of protein design from scratch, especially for the artificial design of proteins - how to fully explore the structure space of protein backbones, providing a systematic solution.
Reviewers in the journal Nature spoke highly of the findings, arguing that the new approach "portrays multidimensional features that are unattainable by more traditional statistical methods, with sufficient novelty and practicality."
Proteins are considered to be the basis of life, the main performers of life functions, and their structure and function are determined by the sequence of amino acids. The amino acid sequence of natural proteins has undergone long-term natural evolution, which can make the protein form a stable three-dimensional structure. However, the structural function of natural proteins is not yet sufficient for application needs, so people try to create proteins that have never been seen in nature by designing amino acid sequences, so that they have specific functions, such as fighting cancer cells or fighting emerging viruses.
According to the research team, when artificially designing proteins, the main method currently reported internationally is to use natural structural fragments as building blocks to splice to produce artificial structures. However, this type of approach has its limitations, including a single design result and too sensitive to the details of the main chain structure, which limits the diversity and variability of the design main chain structure.
The team of Professor Haiyan Liu and Associate Professor Quan Chen has been committed to developing data-driven protein design methods for more than a decade in order to discover novel, "highly designable" backbone structures. After a long period of unremitting efforts, they broke through the limitation that only natural fragments can be used to stitch together to produce new backbone structures, and designed novel structures that are different from known natural proteins.
In this published work, the researchers established an ABACUS model for the design of amino acid sequences for a given backbone structure, and then developed a SCUBA (Side Chain-Unknown Backbone Arrangement) model that can design a new backbone structure from scratch when the amino acid sequence is waiting.
Principles of protein design using the SCUBA model: (a) the very small size of the energy surface of the SCUBA backbone corresponds to the designable backbone structure of the protein, that is, the lowest free energy structure under a specific amino acid sequence; (b) the statistical energy term represented by the neural network in SCUBA; (c) and (d) the method framework for learning the analytical energy function from the original data of the protein structure using the near neighbor counting (NC)-neural network (NN) method. (Image source: References[1])
A major feature of this statistical model is the energy term in the form of a neural network. Specifically, based on the kernel density estimation (or neighbor count, NC) and neural network fitting (NN) methods, the analytical energy function in the form of a neural network is obtained from the original structural data, which can reflect the high-dimensional correlation between different structural variables in the actual protein structure with high fidelity, continuously and extensively search the main chain structure space under the premise of uncertain sequence, and automatically generate a "highly designable" main chain.
This calculation method has also been experimentally verified in this study. The team reported X-ray crystal structures of 9 de novo designed protein molecules (as shown in the figure below), whose actual structures are consistent with the design model, with 5 proteins having novel topologies that have not yet been observed in native proteins.
Comparison of the high-resolution crystal structure (sky blue) of the de novo design protein with the design model (green) (Image source: Reference[1])
The press release of the University of Science and Technology of China pointed out that this work has achieved original innovation of key core technologies in the frontier science and technology field of protein design, laying a solid foundation for the design of functional proteins such as industrial enzymes, biomaterials, and biomedical proteins. Professor Liu Haiyan and Associate Professor Chen Quan of the Faculty of Life Sciences and Medicine are the corresponding authors of the paper, and doctoral students Huang Bin, Xu Yang and Hu Xiuhong are the co-first authors of the paper.
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