The research team, led by Associate Professor Kazuhiro Abe and Professor Satoshi Yokoshima from the Graduate School of Pharmaceutical Sciences at Nagoya University, adopted an innovative approach to developing gastric acid inhibitors. Their focus was on the complex structure of the gastric proton pump, a protein in the stomach lining responsible for transporting the H+ protons that make up gastric acid. To analyze this structure, they employed "Deep Quartet," an AI-based drug discovery platform. Using AI, the researchers designed new candidate compounds with unique chemical structures, aiming to effectively target the gastric proton pump. The goal was to identify compounds capable of binding to multiple sites on the proton pump, thus enhancing the overall effectiveness of the drug. These candidates were chemically synthesized, and their interactions with proteins were analyzed through cryo-electron microscopy. Subsequently, the compounds were further modified to enhance their binding capacity.
AI assisted in generating over 100 candidate compounds with unique chemical structures. Scientists, along with experts in chemical and structural biology, selected the most promising candidates for synthesis and tested them for their binding and inhibition capacity of the gastric proton pump. The result was remarkable: the sixth synthesized compound (DQ-06) demonstrated a stronger binding affinity than existing reference compounds. Prof. Abe admitted to having initial reservations about AI: "I was skeptical when I saw some of the peculiar chemical structures, including DQ-02, but we suspected that AI had a reason to suggest such unusual compounds. We then found that AI was very accurate in designing for the specific binding site." To gain further insights into the binding mechanism, the research team employed cryo-electron microscopy, revealing that there was room for further improvement in binding strength.
Based on this information, they synthesized a new compound, DQ-18, achieving an even stronger binding by introducing a chlorine atom into DQ-06.
This innovative approach led to the creation of a compound with a nearly tenfold higher binding affinity compared to a prototype gastric acid inhibitor. Prof. Abe emphasized the importance of collaboration between humans and AI in drug discovery, explaining that "AI is helpful in structure-based design, a task where humans don't excel, but the selection of candidates for synthesis and the improvement of compounds are still essential human tasks to achieve successful final results. The synergy between AI and scientists is crucial in advancing the development of cutting-edge drugs. This research represents a significant step forward in the development of drugs for the treatment of gastric acid-related disorders, offering the promise of more efficient and reliable therapies. Furthermore, it demonstrates the potential of artificial intelligence in the medical field and as a collaborative tool for scientists.
But the use of AI in medicine goes beyond drug discovery. It is a rapidly growing technology that is transforming medical diagnosis and treatment personalization. Machine learning algorithms can analyze medical images with astonishing accuracy, enabling early diagnosis of diseases such as cancer. Additionally, the analysis of genomic data and patient information allows for treatment customization, improving effectiveness and reducing side effects. AI is also revolutionizing healthcare management, enabling healthcare providers to analyze large amounts of data to identify trends and predict epidemics. This leads to more effective and timely patient care. In conclusion, artificial intelligence is opening new frontiers in medicine. Its ability to analyze data, design drugs, improve diagnostics, and personalize treatments represents a remarkable innovation for the future of medicine. The collaboration between scientists and AI is a clear example of how technology is improving human health and leading to new medical discoveries that will change the course of history. AI-assisted medical research is a growing reality promising to enhance the lives of millions of people worldwide.
Scientists build on artificial intelligence to create next-generation gastric acid treatment
