Core Insights - Levinthal Biotech, a leading company in AI-driven protein design, has successfully completed a multi-million RMB Pre-A round financing, led by Jinyumaowu and with participation from JunKedanmu, aiming to accelerate the development of its Pallatom platform and expand its product pipeline [2][3] Group 1: Company Overview - Levinthal Biotech was founded in September 2021, focusing on AI algorithms for protein design, named after Cyrus Levinthal, who proposed the "Levinthal Paradox" regarding protein folding [3] - The company is led by Dr. Wang Haobo, who has a strong background in AI protein design research and has assembled a team of experts from prestigious institutions [3] Group 2: Technology Platforms - Pallatom is a high-performance, all-atom protein design platform that has been recognized alongside models like AlphaFold 3 and ESM3, showcasing its advanced capabilities in precise protein structure design [4][9] - The platform has achieved significant breakthroughs, including solving the design challenges of mixed chirality cyclic peptides, opening new avenues for next-generation cyclic peptide drug development [10] Group 3: Commercial Applications - Pallatom has demonstrated commercial value by overcoming technical barriers in antibody purification, successfully designing a Protein A alternative that surpasses imported products, thus enhancing supply chain autonomy for Chinese biopharmaceutical companies [10] - The Lésign platform integrates evolutionary information and physical potential into AI co-evolution analysis, achieving scalable applications in industrial enzymes and functional proteins [11] Group 4: Business Strategy - Levinthal Biotech has established a comprehensive value chain from molecular design to process development, successfully launching multiple product lines across various sectors, including synthetic biology, new pharmaceuticals, and health foods [13] - The company's innovative approach has significantly reduced the research and development cycle from years to months, drastically lowering experimental validation scales and costs, thereby providing unprecedented momentum for biomedicine and industrial manufacturing [13]