闻乐 发自 凹非寺 量子位 | 公众号 QbitAI 你敢信？有人用AI，拯救了自家毛孩子。 一个搞科技的哥们收养的爱犬Rosie，被诊断出肥大细胞癌，兽医说可能只剩几个月的时间。 没想到这一试，直接研制出了专为Rosie定制的mRNA癌症疫苗。 让它腿上的肿瘤缩小了50%，原本奄奄一息的狗狗，现在能满公园追兔子了。 OpenAI总裁Greg Brockman表示这是 首例专为犬类设计的个性化癌症疫苗 。 AI这是真能治病了…… 零生物学背景借助AI研制专属疫苗 毛孩子家长不想坐以待毙，凭借多年和科技打交道的经验，决定让GPT试试寻找治疗方案。 具体的事情经过是这样的。 原本活泼好动的狗狗Rosie突然出现精神萎靡、身体肿胀的症状，辗转多家权威宠物医院后，被确诊为一种恶性程度极高、临床几乎无法治愈 的罕见癌症。 兽医给出的结论是，传统手术无法完整切除病灶，市面上也没有匹配的靶向药。 但作为科技从业者，毛孩子的家长Paul决定再通过AI寻找一些治疗思路。 于是，ChatGPT给Paul讲解了各种生物学知识，并建议 免疫疗法 ，给他指了一个基因测序的方向。 还指引Paul联系了新南威尔士大学（UNSW）的拉马乔蒂 ...

Cool use case of AlphaFold, this is just the beginning of digital biology!None (@None):None ...

Core Viewpoint - The article discusses a significant breakthrough in AI-driven drug discovery through the development of DrugCLIP, a platform that can perform high-throughput virtual screening of drugs at a genomic scale, achieving 10 trillion protein-molecule pairing calculations within 24 hours [1][4][36]. Group 1: DrugCLIP Platform - DrugCLIP is an AI-driven ultra-high-throughput virtual screening platform developed by Tsinghua University, which allows for rapid identification of candidate drug molecules from vast chemical libraries [2][3]. - The platform has successfully completed virtual screening covering the human genome scale, identifying potential drug molecules for diseases such as depression, cancer, and Parkinson's disease [6][54]. Group 2: Challenges in Traditional Drug Screening - Traditional drug screening faces three main challenges: slow processing speed, lack of starting points for many disease-related proteins, and a narrow focus on popular targets [8][12][18]. - Only 10% of protein targets have mature drugs available, while 90% remain without identified drugs [11]. Group 3: Methodology of DrugCLIP - DrugCLIP employs a novel approach by using contrastive learning to train AI encoders that create vector representations of protein binding pockets and chemical molecules [20][22]. - The model processes 5 billion candidate molecules, generating vector representations to quickly identify the most promising candidates for new drug development [32][34]. Group 4: Performance and Validation - DrugCLIP has demonstrated superior performance in virtual screening benchmarks, outperforming traditional docking tools and other AI methods in identifying effective molecules [37][39]. - Experimental validation showed that from 78 screened molecules related to depression, 8 were found to activate the target protein, with the best molecule exhibiting a binding affinity of 21 nM [42][43]. Group 5: Future Prospects - The DrugCLIP platform is set to collaborate with industry partners to accelerate the discovery of new drug targets and first-in-class drugs for various diseases [64]. - The database created by DrugCLIP, which is now open to the global research community, represents the largest known protein-ligand screening database, potentially providing "drug seeds" for nearly half of human proteins [55][59].

AlphaFold's Impact on Science and Industry - AlphaFold identified over 240 million protein structures in approximately two years, a thousandfold increase compared to the 210 thousand structures discovered in the previous 100 years [2][3] - AlphaFold, an AI system, won the Nobel Prize in Chemistry in 2024, signifying the increasing recognition of AI in scientific advancements [4][5] - AlphaFold accelerates drug discovery, disease understanding, and vaccine development by predicting protein structures in 3D [6][7] - AlphaFold's capabilities are expanding to include DNA, RNA, and small molecules, demonstrating AI's growing influence in diverse scientific fields [7] Implications for Corporate Leadership and Strategy - The business world is characterized as "Barney" (brittle, anxious, nonlinear, and incomprehensible), requiring companies to adapt to rapid changes and disruptions [8][9] - AI managers face the dilemma of balancing emerging technologies, internal operations, and evolving market dynamics [10][11] - Companies need to shift from outdated quantitative management to visionary foresight, emphasizing learning and proactive action [12] - Businesses should explore how AlphaFold-like technologies can be applied beyond medicine and biology, such as in polymers, adhesives, and new materials [13][14] - New physics simulation trains 430 thousand times faster than reality [19] - Route optimization tools like Nvidia Cosmos can significantly improve logistics and shipping efficiency [20] Call to Action for Boardrooms and Executives - Boardrooms and executives must embrace and experiment with new technologies to envision the future and make informed decisions [23] - Leaders need to transition from traditional management approaches to visionary foresight to stay ahead of competitors [24] - The advancements enabled by AlphaFold represent a groundbreaking era for society, environment, technology, and business [26]