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Congratulations to the 2024 Nobel prize in Chemistry has been awarded to David Baker, Demis Hassabis, and John Jumper for their work on understanding the structure of proteins. Hassabis and Jumper, of Google DeepMind, have developed an artificial intelligence that predicts the structure of proteins. Baker, at the University of Washington, has been recognised for his work on designing new proteins. See article below #nobelprize #chemistry #google #deepmind #proteins #ai #NextPhase

The 2024 #NobelPrize laureates in chemistry Demis Hassabis and John Jumper have successfully utilised artificial intelligence to predict the structure of almost all known proteins. When Demis Hassabis and John Jumper confirmed that AlphaFold2 really worked, they calcu­lated the structure of all human proteins. Then they predicted the structure of virtually all the 200 million proteins that researchers have so far discovered when mapping Earth’s organisms. #AlphaFold2 is a groundbreaking artificial intelligence system developed by DeepMind, a subsidiary of Alphabet Inc. It has revolutionized the field of protein structure prediction by accurately predicting the 3D structure of a protein from its amino acid sequence with unprecedented accuracy. AlphaFold2 can predict protein structures with an accuracy comparable to experimental methods like X-ray crystallography and cryo-electron microscopy. It can predict the structure of a protein in a matter of days or even hours, significantly reducing the time and cost involved in traditional experimental methods. Additionally, AlphaFold2 can be applied to a wide range of proteins, including those that are difficult to study using experimental methods. The system is based on deep learning techniques, specifically neural networks, which enable it to learn complex patterns in protein sequences and structures. Google #DeepMind has also made the code for AlphaFold2 publicly available, and anyone can access it. The AI model has become a gold mine for researchers. By October 2024, AlphaFold2 had been used by more than two million people from 190 countries. Previously, it often took years to obtain a protein structure, if at all. Now it can be done in a few minutes. The AI model is not perfect, but it estimates the correctness of the structure it has produced, so researchers know how reliable the prediction is. Read on ... https://lnkd.in/g5Vdx47C #AIML #TechInnovations #AIusecases

Google Scientists Win Nobel Prize in Chemistry, Marking a Milestone in AI's Evolution The Royal Swedish Academy of Sciences has awarded the 2024 Nobel Prize in Chemistry to Demis Hassabis and John Jumper of Google DeepMind, along with David Baker of the University of Washington. This prestigious award recognizes their groundbreaking work in using artificial intelligence (AI) to predict and design novel proteins. AI's Ascendancy in Scientific Discovery ➡️ This isn't just a win for Google or DeepMind; it's a landmark moment for the entire field of AI. It demonstrates the transformative power of AI in pushing the boundaries of scientific discovery and addressing some of humanity's most pressing challenges. ➡️ Pioneering the Future of Medicine and Beyond The laureates' work has the potential to revolutionize medicine, materials science, and numerous other fields. By enabling the accurate prediction and design of protein structures, their AI models are paving the way for the development of new drugs, therapies, and materials with unprecedented precision and efficiency. 💡 A Journey of Innovation and Collaboration This Nobel Prize is a testament to the dedication, ingenuity, and collaborative spirit of these brilliant scientists. It also highlights the crucial role of interdisciplinary research in driving innovation and pushing the frontiers of knowledge. ✅ The Future of AI is Bright As AI continues to evolve and mature, we can expect even more groundbreaking discoveries and applications in the years to come. This Nobel Prize serves as an inspiration and a reminder of the immense potential of AI to shape a better future for all. ❕ With Great Power Comes Great Responsibility While the win is a significant milestone, it also comes with a great responsibility. As AI becomes more powerful and integrated into our lives, it's crucial to ensure its responsible development and use. This includes addressing ethical concerns, mitigating potential biases, and establishing clear boundaries for its application. #AI #NobelPrize #Chemistry #GoogleDeepMind #Innovation #Science #Technology #FutureOfWork #ResponsibleAI #Ethics #Boundaries https://lnkd.in/dkCrU8TM

I’d like to share an article about the recent Nobel Prize winners in Chemistry, Demis Hassabis, John Jumper, and David Baker, whose pioneering work in AI has revolutionized our understanding of protein structures. Their breakthroughs not only advance drug discovery but also open new avenues for industrial applications. A key highlight is their dedication to open science, exemplified by the release of their software, which promotes collaboration and innovation across the scientific community. This milestone reinforces the profound impact of AI in biology and medicine. Moreover, it highlights the importance of shared knowledge in scientific progress.

I wanted to share this insightful Opinion piece by the Editorial Board of The Washington Post. It's a great example of how GenAI can serve humanity, even as we remain mindful of the associated risks. The AlphaFold Protein Structure Database being in the public domain is a tremendous benefit, especially for those with rare diseases that have often been overlooked by the pharmaceutical industry. This importance has been recognized by The Royal Swedish Academy of Sciences, awarding this year’s The Nobel Prize in Chemistry for these achievements, even though biology is not traditionally one of the prize categories. This flexibility ensures the Nobel Prizes remain relevant and impactful as scientific fields evolve. Regarding the Nobel Prize, it’s interesting to note that there has been ongoing discussion about the inclusion of other awards. However, making changes to the categories and the maximum number of award winners for each award is challenging due to the very detailed stipulations in Alfred Nobel’s will from 1895. On a personal note, it's wonderful to see X-ray crystallography mentioned—one of the technologies I used during my master's thesis on the sedimentological and petrophysical characterization of a 100-meter-long cored Westphalian sandstone from the 🇧🇪 Campine Basin under the supervision of Rudy Swennen at Katholieke Universiteit Leuven (KU Leuven) and Koen Weber at TU Delft and Shell. #GenAI #AlphaFold #NobelPrize #Chemistry #PublicDomain #RareDiseases #Pharmaceuticals #XRayCrystallography #Science #Innovation #Research #Biotechnology #AI #MachineLearning #ProteinStructure #Healthcare #ScientificBreakthrough #WestphalianSandstone

🌟 Nobel Prize in Chemistry 2024: Unlocking a New World of Protein Design with AI 🧬✨ The 2024 Nobel Prize in Chemistry has shattered boundaries, unveiling revolutionary advances in protein design and prediction that could transform #drugdiscovery, medicine, technology, and beyond. Johan Åqvist, professor of theoretical chemistry and Nobel Committee member, shared on this just minutes, after the live announcement, calling this year’s breakthroughs “mind-blowing.” This year’s prize is all about cracking the code of protein structures—massive molecules vital to life, made up of amino acids that fold into mind-boggling 3D shapes. David Baker, one of the laureates, was recognized for designing proteins that have never existed in nature. Using sophisticated algorithms, Baker's work allows scientists to create virus inhibitors, opioid sensors, and even futuristic nanomaterials—pushing the limits of what we thought possible. Two additional laureates Demis Hassabis and John Jumper were also recognised for using advanced neural networks to predict protein structures from their amino acid sequences. This breakthrough has already led to a massive database of 200,000 protein structures, setting the stage for design of various drugs. “This prize opens up a completely new world of possibilities,” Åqvist said, as AI and protein design collide to revolutionize the future of science and technology. #DrugDiscoveryNews #ComputationalChemistry #ResearchNews

👍 The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in #Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.” 1>> In 2003, this year’s chemistry laureate #David Baker succeeded in designing a new protein that was unlike any other protein. This was the first step in something that can only be described as an extraordinary development. A few of the many spectacular proteins created in Baker’s laboratory using his computer software #Rosetta can be seen in the picture. Baker’s research group has produced one imaginative protein creation after another, including proteins that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors. 2.) 2024 #NobelPrize laureates Demis Hassabis and John Jumper have used their AI model AlphaFold2 to calculate the structure of all human proteins. They also predicted the structure of virtually all the 200 million proteins that researchers have so far discovered when mapping Earth’s organisms. Google DeepMind has also made the code for AlphaFold2 publicly available, and anyone can access it. The AI model has become a gold mine for researchers. By October 2024, AlphaFold2 had been used by more than two million people from 190 countries. @Thenobelprize #NobelPrize2024 #ArtificialI #ML #Protein #Chemistry #Research #Science

It's Nobel-award day for Google Deepmind 🎉 🧬 Our Co-founder and CEO of Google DeepMind and Isomorphic Labs Sir Demis Hassabis, and Google DeepMind Director Dr. John Jumper were co-awarded the 2024 Nobel Prize in Chemistry for their work developing AlphaFold, a groundbreaking AI system that predicts the 3D structure of proteins from their amino acid sequences. Before AlphaFold, predicting the structure of a protein was a complex and time-consuming process. AlphaFold’s predictions, made freely available through the AlphaFold Protein Structure Database, have given more than 2 million scientists and researchers from 190 countries a powerful tool for making new discoveries. The AlphaFold 2 paper, published in 2021, remains one of the most-cited publications of all time. #NobelPrize #Chemistry #AI #DeepMind #AlphaFold #Science #Innovation #ProteinFolding #DrugDiscovery

This is super exciting!!! The Nobel Prize in Chemistry was awarded on Wednesday to three scientists for discoveries that show the potential of advanced technology, including artificial intelligence, to predict the shape of proteins, life’s chemical tools, and to invent new ones. During my Masters in Biophysics at AIIMS in 1996-1998, as part of my research I had written a code in the ancient scientific coding language: Fortran to predict the structure of proteins by calculating the attraction and repulsion between the independent molecules of each amino acid that was part of the protein. We had at the time used this model to predict/ invent a protein that could act as an HIV vaccine. The work was published, patented, earned a grant and was at the time taken up by NIH, USA for further research. The news of this year's Nobel prize reminded me of this work from my past life. And so exciting to see how far it has come since!! Super duper exciting!!!! https://lnkd.in/gY5a4QNi

The 2024 Nobel Prize in Chemistry has been awarded to Demis Hassabis, John Jumper, and David Baker for their revolutionary work in AI-driven protein structure prediction. Their achievements with AlphaFold and related deep learning methods are transforming the fields of chemistry and biology. AlphaFold, developed by DeepMind, solved one of biology’s biggest challenges: predicting the 3D structure of proteins based solely on their amino acid sequences. This breakthrough, led by Hassabis and Jumper, has revolutionized the way we understand biological molecules, speeding up drug discovery, disease research, and molecular design. Meanwhile, David Baker’s work has focused on designing new proteins that do not exist in nature, using AI to create molecules that could have significant impacts on medicine and materials science. These AI-driven approaches are now shaping the future of chemistry and biomedicine, allowing scientists to simulate molecular behavior, optimize drug design, and improve our understanding of biological systems with unprecedented precision. By combining deep learning and cutting-edge molecular research, this year’s laureates have demonstrated the incredible power of AI to solve real-world scientific challenges. Their contributions will inspire a new generation of innovation at the intersection of AI, chemistry, and biology. #NobelPrize #AlphaFold #DemisHassabis #JohnJumper #DavidBaker #DeepLearning #AIInBiology #ProteinFolding #DrugDiscovery #AIRevolution #Chemistry #Biology #MolecularScience #DeepMind #ScientificBreakthrough #MachineLearning #Innovation