Forbes 2024 China's Most Disruptive Founders: Xu Jinbo of Molecular Matchmaker, a Pioneer and Leader in AI Protein Field

Forbes 2024 China's Most Disruptive Founders: Xu Jinbo of Molecular Matchmaker, a Pioneer and Leader in AI Protein FieldRecently, Forbes officially announced its 2024 China's Most Disruptive Founders list, featuring Xu Jinbo, founder and chief scientist of Molecular Matchmaker. This honor is a testament to his outstanding contributions to the AI protein field and his groundbreaking technological innovations

Forbes 2024 China's Most Disruptive Founders: Xu Jinbo of Molecular Matchmaker, a Pioneer and Leader in AI Protein Field

Recently, Forbes officially announced its 2024 China's Most Disruptive Founders list, featuring Xu Jinbo, founder and chief scientist of Molecular Matchmaker. This honor is a testament to his outstanding contributions to the AI protein field and his groundbreaking technological innovations. The selection, jointly initiated by Forbes China and GBRC (Global Business Research Center), aims to recognize founders who demonstrate creative thinking and disruptive achievements in the new round of technological revolution and industrial upgrading. Xu Jinbo's inclusion shines a spotlight on the convergence of AI and biotechnology, signifying China's rise to a global leading position in this field.

Professor Xu Jinbo is a renowned scientist in the interdisciplinary field of AI and biotechnology. As early as 2016, his pioneering researchthe deep learning-based RaptorX-Contact methodsent shockwaves through the scientific community. This technology demonstrated, for the first time, the ability of artificial intelligence to significantly improve the accuracy of protein structure prediction, bringing a glimmer of hope to solving the long-standing scientific puzzle of protein folding.

The protein folding problem centers on predicting how the amino acid sequence of a protein folds into its unique three-dimensional structure, which directly determines its function. Traditional methods, such as X-ray crystallography and nuclear magnetic resonance, are often time-consuming, expensive, and have low success rates, making them unsuitable for large-scale protein structure prediction. Professor Xu's RaptorX-Contact method cleverly utilizes deep neural networks to capture global protein information, significantly improving prediction accuracy and efficiency.

This technological success not only provided a powerful tool for biological research but also pioneered the new research paradigm of AI for Life Science, profoundly influencing subsequent studies. The most notable example is Google DeepMind's AlphaFold, whose success partly benefited from Professor Xu's earlier research, marking a new stage in the application of artificial intelligence in biology. RaptorX-Contact achieved breakthrough results in the "Protein Olympics"the Critical Assessment of protein Structure Prediction (CASP) competitionraising the accuracy of protein structure prediction to new heights and powerfully demonstrating its technological advantages and application prospects. CASP, a top-tier event in the protein structure prediction field, attracts the world's best research teams. Professor Xu's team has consistently maintained a leading position in past competitions, making outstanding contributions to the advancement of protein structure prediction technology.

However, Professor Xu's research did not stop at protein structure prediction. He keenly recognized that AI technology could be used not only to predict protein structures but also to design them. He was a pioneer in expanding research into the AI protein design field, a revolutionary breakthrough in biotechnology. AI technology enables comprehensive and systematic exploration of protein space, designing super proteins that do not exist in nature, thus bringing disruptive changes to the biopharmaceutical and biomanufacturing industries. These super proteins can possess novel functions, such as more efficient enzymes, more specific antibodies, and more stable materials, offering limitless possibilities for developing novel drugs, environmentally friendly materials, and high-quality foods.

To better promote the industrial application of AI protein technology, Professor Xu returned to China at the end of 2021 and founded Molecular Matchmaker. This company quickly assembled a top-tier team of multidisciplinary talents with experience in AI protein research and extensive industrial practice, dedicated to the R&D of AI protein prediction, optimization, and design technologies. In just over two years, Molecular Matchmaker has achieved more than ten globally leading technological breakthroughs, demonstrating remarkable development speed and innovation capabilities.

Molecular Matchmaker's AI protein optimization and design platform, MoleculeOS, is a powerful tool integrating various advanced algorithms and technologies, greatly simplifying the protein design process and significantly improving design efficiency and success rates. They also developed NewOrigin (Darwin), the first industrial-grade AI protein generation large model integrating sequence, structure, function, and evolution. The development of this large model marks a new stage in AI protein design technology, and its powerful prediction and design capabilities can provide more accurate and efficient support for the biopharmaceutical and biomanufacturing industries.

Molecular Matchmaker's revolutionary AI protein technologies have been deeply applied to high-difficulty industrial tasks in innovative drug R&D, biomanufacturing, and new materials. These technologies not only improve the efficiency and success rate of protein performance optimization and de novo design but also provide more efficient and intelligent solutions to long-standing bottlenecks in biomanufacturing, such as long R&D cycles, high costs, and high product selection risks. For example, in drug R&D, AI protein design technology can help scientists quickly design drug molecules with specific targeting and activity, thereby shortening drug R&D cycles and reducing R&D costs; in biomanufacturing, it can help design more efficient enzymes to improve the yield and quality of biological products; and in new materials, it can help design new materials with special properties, such as biocompatible medical materials and high-strength engineering materials.

Professor Xu and the Molecular Matchmaker team have not only achieved breakthrough progress at the technical level but have also achieved remarkable results in commercial applications. Their technology has established partnerships with several industry-leading companies and successfully applied AI protein design technology to actual production, bringing significant economic and social benefits to these enterprises. This fully demonstrates the enormous application potential of AI protein design technology and the outstanding contributions of Professor Xu and his team in driving technological innovation and industrial development.

Professor Xu's success is not only a reflection of personal achievement but also a microcosm of China's enhanced scientific and technological strength. The team he leads, through independent innovation, has achieved a leading position in the internationally competitive AI protein field, making important contributions to China's development in the biotechnology sector. His story encourages more young people to dedicate themselves to scientific and technological innovation and contribute to national development. In the future, with the continuous development and application of AI protein technology, we can expect more AI-based innovative achievements to create a better future for humanity. Professor Xu and Molecular Matchmaker will undoubtedly continue to lead the direction of the AI protein field in this exciting era.

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