MoleculeMind Secures Tens of Millions in USD in Series A Funding Led by Sequoia China

Investment Circle (ID: pedaily2012) April 18 News: Recently, AI protein design platform company "MoleculeMind" has completedTens of millions of dollars in angel round financing, led by HongShan, with participation from Baidu Ventures, LSV CAPITAL, Neux Capital, and MoleculeMind Inc.This round of financing will be used for further team expansion, the continuous evolution of the AI protein platform, and the productization of scientific research achievements.

MoleculeMind was founded under the leadership of Professor Jinbo Xu. In China, the company has assembled a team of computational biology experts, all of whom have overseas academic backgrounds from prestigious universities. Xu currently serves as a professor at the Toyota Technological Institute at Chicago and a visiting professor at BIOPIC, Peking University. He has been engaged in the research of "AI protein folding technology" for many years. In 2016, he developed the RaptorX-Contact method, which was the first to demonstrate that deep learning could significantly improve the accuracy of protein structure prediction. In 2020, DeepMind applied this method in the development of AlphaFold, making a significant contribution to solving the protein prediction challenge.

Based on Xu Jinbo's scientific research achievements, MoleculeMind continues to develop "AI Protein Prediction and Design" and has independently developed the AI large molecule optimization and design platform "MoleculeOS." Using data-driven deep learning methods, it assists biotechnology experts in identifying and generating proteins to scale laboratory research results into industrial-level applications. This platform can be used for the research and design of peptides, antibodies, enzymes, and small proteins, transforming the development of large-molecule innovative drugs into a predictable and programmable process, thereby improving efficiency across the entire drug R&D workflow. It can also be applied to protein optimization and design in fields such as chemistry, materials, industry, and agriculture.

"Using a high-throughput, integrated dry and wet biological computing engine, this platform already possesses the ability to predict protein structures and characteristics, optimize peptides and proteins, and will continue to add value in areas such as drug development and the prediction of protein-protein interactions."Xu Jinbo said that, very soon, the platform will be able to design proteins and entirely new antibodies that do not exist in nature.

Based on the AI platform, MoleculeMind is conducting research on monoclonal antibody drugs targeting special epitopes, small protein drugs, bispecific epitope antibody drugs, etc., and has established cooperation with national-level life science and medical laboratories to promote the transformation of AI protein research and design achievements.

In addition to biopharmaceutical R&D, the AI large molecule optimization and design platform is also applied to synthetic biology. For example, it can be used to produce renewable biofuels to address energy and environmental issues, or to create new industrial enzymes with stable functions using AI.

Xu Jinbo believes that although AI is currently still in an auxiliary position in protein research and development, it is expected to become a key driver of innovation through the joint efforts of academia and industry.

After years of research, the academic and industrial communities have reached a consensus: deep learning significantly improves protein structure prediction, enabling the accurate prediction of the general 3D shapes of most proteins. In 2021, the introduction of the Transformer model in AlphaFold2 and end-to-end training further elevated the accuracy of this task.

Xu Jinbo stated that proteins are the most spectacular machines in nature. Protein drugs or related products have unimaginable potential in treating diseases and advancing social productivity. MoleculeMind will leverage AI capabilities to deeply cultivate this field, hoping to establish a world-class computational biology discipline in China and promote industrial-level transformation of scientific achievements.

This article is sourced from Pedaily, original text: https://news.pedaily.cn/202204/490319.shtml