Logan Abbott’s Post

Google DeepMind Scientists Win Nobel Chemistry Prize for Work on Proteins: Three scientists won the 2024 Nobel Prize in Chemistry on Wednesday for their groundbreaking work in predicting and designing protein structures, the Royal Swedish Academy of Sciences announced in Stockholm. David Baker of the University of Washington shares the prize with Demis Hassabis and John Jumper of Google DeepMind. Baker pioneered the creation of novel proteins, while Hassabis and Jumper developed AlphaFold, an AI model that predicts protein structures from amino acid sequences. The laureates will split the 11 million Swedish kronor ($1 million) award for their contributions to computational protein design and structure prediction. Baker's team has produced proteins with applications in medicine and materials science since his initial breakthrough in 2003. Hassabis and Jumper's AlphaFold, announced in 2020, has predicted structures for nearly all 200 million known proteins. "We glimpsed at the beginning that it might be possible to create a whole new world of proteins that address a lot of the problems faced by humans in the 21st century," Baker said at a press briefing. "Now it's becoming possible," Heiner Linke, chair of the Nobel chemistry committee, called the discoveries "spectacular," noting they fulfilled a 50-year-old dream of predicting protein structures from amino acid sequences. The breakthroughs have wide-ranging implications, from understanding antibiotic resistance to developing enzymes that decompose plastic. Over 2 million researchers worldwide have already utilized AlphaFold in various applications. Read more of this story at Slashdot.

The Royal Swedish Academy of Sciences has decided to award the 2024 Nobel Prize 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.” The Nobel Prize in Chemistry 2024 is about proteins, life’s ingenious chemical tools. David Baker has succeeded with the almost impossible feat of building entirely new kinds of proteins. Demis Hassabis and John Jumper have developed an AI model to solve a 50-year-old problem: predicting proteins’ complex structures. These discoveries hold enormous potential. The diversity of life testifies to proteins’ amazing capacity as chemical tools. They control and drive all the chemical reactions that together are the basis of life. Proteins also function as hormones, signal substances, antibodies and the building blocks of different tissues. Proteins generally consist of 20 different amino acids, which can be described as life’s building blocks. In 2003, David Baker succeeded in using these blocks to design a new protein that was unlike any other protein. Since then, his research group has produced one imaginative protein creation after another, including proteins that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors. The second discovery concerns the prediction of protein structures. In proteins, amino acids are linked together in long strings that fold up to make a three-dimensional structure, which is decisive for the protein’s function. Since the 1970s, researchers had tried to predict protein structures from amino acid sequences, but this was notoriously difficult. However, four years ago, there was a stunning breakthrough. In 2020, Demis Hassabis and John Jumper presented an AI model called AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified. Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic. Life could not exist without proteins. That we can now predict protein structures and design our own proteins confers the greatest benefit to humankind. #NoblePrize2024 #ComputationalChemistry #DrugDesign #ProteinStructure

After consecutive Nobel Prizes for Nucleic Acid research, Protein chemistry takes the spotlight with a blend of computational biology and AI in this year's Chemistry Nobel Prize. Congratulations to David Baker, Demis Hassabis, and John Jumper on this prestigious recognition! David Baker's pioneering work in computational protein design has unlocked new possibilities for tailored proteins in pharmaceuticals, vaccines, and nanomaterials. Demis Hassabis and John Jumper's AlphaFold2 (and this year's AlphaFold3) have revolutionized protein structure prediction, benefiting over 2 million protein researchers worldwide and accelerating discoveries in various fields. The recognition of computational approaches at this level prompts a discussion on establishing a dedicated Nobel category for computational biology. The field's rapid advancements and profound impact on life sciences merit specialized acknowledgment. AlphaFold's success showcases the vast potential of AI in scientific exploration. As we leverage computational power to unravel nature's mysteries, expect more groundbreaking discoveries on the horizon. Kudos to the laureates for their outstanding contributions at the intersection of biology, chemistry, and computer science, driving scientific progress and enhancing humanity's well-being. #NobelPrize2024 #ComputationalBiology #AIinScience #ProteinResearch https://lnkd.in/ghzu68Qu

The Royal Swedish Academy of Sciences has decided to award the #Nobel_Prize in Chemistry 2024 with one half to #David_Baker University of Washington, Seattle, WA, USA “for computational protein design” and the other half jointly to #Demis_Hassabis Google DeepMind, London, UK John M. Jumper Google DeepMind, London, UK “for protein structure prediction” They cracked the code for proteins’ amazing structures The Nobel Prize in Chemistry 2024 is about pro­teins, life’s ingenious chemical tools. David Baker has succeeded with the almost impossible feat of building entirely new kinds of proteins. Demis Hassabis and John Jumper have developed an AI model to solve a 50-year-old problem: predicting proteins’ complex structures. These discoveries hold enormous potential. The diversity of life testifies to proteins’ amazing capacity as chemical tools. They control and drive all the chemi­cal reactions that together are the basis of life. Proteins also function as hormones, signal substances, antibodies and the building blocks of different tissues. “One of the discoveries being recognised this year concerns the construction of spectacular proteins. The other is about fulfilling a 50-year-old dream: predicting protein structures from their amino acid sequences. Both of these discoveries open up vast possibilities,” says Heiner Linke, Chair of the Nobel Committee for Chemistry. Proteins generally consist of 20 different amino acids, which can be described as life’s building blocks. In 2003, David Baker succeeded in using these blocks to design a new protein that was unlike any other protein. Since then, his research group has produced one imaginative protein creation after another, including proteins that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors. The second discovery concerns the prediction of protein structures. In proteins, amino acids are linked together in long strings that fold up to make a three-dimensional structure, which is decisive for the protein’s function. Since the 1970s, researchers had tried to predict protein structures from amino acid sequences, but this was notoriously difficult. However, four years ago, there was a stunning breakthrough. In 2020, Demis Hassabis and John Jumper presented an AI model called #AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified. Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic. #AI_Revolution

The 2024 Nobel Prize for chemistry was shared by David Baker “for computational protein design” along with Demis Hassabis and John Jumper “for protein structure prediction,” the Royal Swedish Academy of Sciences announced on Wednesday (October 9, 2024). DeepMind’s Demis Hassabis and John Jumper scoop Nobel Prize in Chemistry for AlphaFold The news comes a day after AI pioneers Geoff Hinton and John Hopfield won the Nobel Prize in Physics for their foundational work in machine learning and AI. Hassabis and Jumper won the award, specifically, for “protein structure prediction,” while Baker’s was for “computational protein design.” Proteins are the building blocks of life, which is why DeepMind’s work on AlphaFold has been so revolutionary. Though its potential had been touted for years, the Google subsidiary presented the second version of the AI model in 2020, going much of the way toward solving a problem that had stumped scientists for years by predicting the 3D structure of proteins using nothing more than their genetic sequence. The shape of a protein dictates how it works, and figuring out its shape was historically a slow, labor-intensive process that would often require years of lab experiments. With AlphaFold, DeepMind was able to accelerate this to mere hours, covering most of the 200 million proteins in existence. The ramifications of this can’t be overstated, as this kind of data is vital to things like drug discovery, diagnosing diseases, and bioengineering. “One of the discoveries being recognised this year concerns the construction of spectacular proteins,” Heiner Linke, chair of the Nobel Committee for Chemistry, said in a statement. “The other is about fulfilling a 50-year-old dream: predicting protein structures from their amino acid sequences. Both of these discoveries open up vast possibilities.” Baker, for his part, secured his half of the prize for engineering entirely new kinds of proteins, designed computationally to perform specific functions within pharmaceuticals, vaccines, and so on. Google acquired DeepMind in 2014 for more than $500 million, with Jumper joining as research scientist three years later. It’s also worth noting here that Hassabis was awarded a U.K. knighthood for ‘services to artificial intelligence’ back in March. In addition to the global prestige of winning such an award, the Nobel Prize in Chemistry comes with a cash prize of 11 million Swedish kronor ($1 million), with half of that going to David Baker and the other split between Hassabis and Jumper. AlphaFold is an AI system developed by DeepMind that predicts a protein’s 3D structure from its amino acid sequence. It is designed as a deep learning system. AlphaFold makes state-of-the-art accurate predictions of a protein’s structure from its amino-acid sequence. It regularly achieves accuracy competitive with experiment. 👇The Nobel prize website has a pretty well made 1-pager on how AlphaFold works.

BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 Nobel Prize 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.”   The Nobel Prize in Chemistry 2024 is about proteins, life’s ingenious chemical tools. David Baker has succeeded with the almost impossible feat of building entirely new kinds of proteins. Demis Hassabis and John Jumper have developed an AI model to solve a 50-year-old problem: predicting proteins’ complex structures. These discoveries hold enormous potential.   The diversity of life testifies to proteins’ amazing capacity as chemical tools. They control and drive all the chemical reactions that together are the basis of life. Proteins also function as hormones, signal substances, antibodies and the building blocks of different tissues.   Proteins generally consist of 20 different amino acids, which can be described as life’s building blocks. In 2003, David Baker succeeded in using these blocks to design a new protein that was unlike any other protein. Since then, his research group has produced one imaginative protein creation after another, including proteins that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors.   The second discovery concerns the prediction of protein structures. In proteins, amino acids are linked together in long strings that fold up to make a three-dimensional structure, which is decisive for the protein’s function. Since the 1970s, researchers had tried to predict protein structures from amino acid sequences, but this was notoriously difficult. However, four years ago, there was a stunning breakthrough.   In 2020, Demis Hassabis and John Jumper presented an AI model called AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified. Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic.   Life could not exist without proteins. That we can now predict protein structures and design our own proteins confers the greatest benefit to humankind. #nobel #nobelprize #nobelprize2024 #chemistry #science #research

About the Speaker: Dr. Michael Gromiha received his Ph.D. from Bharathidasan University, India. He carried out his postdoctorate at the International Center for Genetic Engineering and Biotechnology (ICGEB), Italy, and The Institute of Physical and Chemical Research (RIKEN), Japan. He also served as a Research Scientist and a Senior Research Scientist at Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Japan. He is currently a professor in the Department of Biotechnology, IIT, Madras About the Lecture: Proteins perform several functions in living organisms as enzymes, transporters, receptors, antibodies, and others. These functions are mainly dictated by their structures. Deciphering the three-dimensional structure of a protein from its amino acid sequence, known as protein folding problem, is a challenging task in structural and computational biology. In this talk, the speaker will briefly introduce the fundamental concepts of protein structure and function along with recent developments and achievements for predicting protein 3D structures, which led to the recognition of a Nobel prize. Further, other equally important tasks such as understanding the stability of protein structures and protein folding rates will be discussed. These aspects are integrated for designing proteins successfully with potential applications, which brought for a reward of a Nobel prize. In addition, various computational resources such as databases and tools available for predicting protein structures, stability, folding rates, binding affinity and design will be highlighted.

The Nobel Prize in Chemistry was awarded on Wednesday (Oct. 9) to three scientists who have help unravel some of the enduring secrets of proteins, the building blocks of life. While Demis Hassabis and John Jumper of Google's DeepMind lab used artificial intelligence techniques to predict the structure of proteins, biochemist David Baker managed to design totally new ones never seen in nature. These breakthroughs are hoped to lead towards numerous advances, from discovering new drugs to enzymes that decompose pollutants. What about the new proteins? US biochemist Baker started at the opposite end of the process. First, he designed an entirely new protein structure never seen in nature. Then, using a computer program called Rosetta that he had developed, he was able to work out the amino acid sequence that it started out as. To achieve this, Rosetta trawled through all the known protein structures, searching for short protein fragments similar to the structure it wanted to build. Rosetta then tweaked them and proposed a sequence that could end up as the structure. What is all this for? Mastering such fundamental and important little machines as proteins could have a vast number of potential uses in the future. "It allows us to better understand how life functions, including why some diseases develop, how antibiotic resistance occurs or why some microbes can decompose plastic," the Nobel website said. Making all-new proteins could lead to new nanomaterials, targeted drugs and vaccines, or more climate-friendly chemicals, it added. Asked to pick a favorite protein, Baker pointed to one he "designed during the pandemic that protects against the coronavirus". "I've been very excited about the idea of a nasal spray of little design proteins that would protect against all possible pandemic viruses," he told the Nobel ceremony via videolink. Calebiro emphasized how "transformative" this research would be. "I think this is just the beginning of a completely new era."

🚨 BREAKING NEWS 🚨 The Royal Swedish Academy of Sciences has awarded the 2024 Nobel Prize in Chemistry to two groundbreaking discoveries in protein science! 🏅 One half of the prize goes to David Baker for his remarkable work in computational protein design. Baker achieved the incredible feat of building entirely new proteins, opening the door to innovations in pharmaceuticals, vaccines, nanomaterials, and sensors. His work redefines the boundaries of what's possible in protein engineering. 🏅 The other half is awarded jointly to Demis Hassabis and John M. Jumper for developing AlphaFold2, a revolutionary AI model that solves the 50-year-old problem of protein structure prediction. AlphaFold2 has predicted the structure of virtually all known proteins, with profound implications for research on antibiotic resistance, enzyme engineering, and beyond. Since 2020, this AI breakthrough has been used by millions globally, accelerating scientific discovery in ways we couldn’t have imagined just a few years ago. Proteins are the building blocks of life—they control and drive all the chemical reactions that sustain life, functioning as hormones, antibodies, and much more. With these two monumental achievements in protein design and prediction, we are witnessing a new era of possibilities in biology, medicine, and materials science. 🌍🔬 This year’s Nobel Prize in Chemistry highlights the vast potential of proteins as life’s ingenious chemical tools, and these discoveries are set to benefit humankind in extraordinary ways. Parul University #NobelPrize2024 #Chemistry #Proteins #AlphaFold #ProteinDesign #DavidBaker #DemisHassabis #JohnJumper #AI #ScienceInnovation #LifeSciences #Academics #Research #phd

Nobel Prizes in Science 2024 🎊 The Nobel Prize Last week was Nobel week for sciences ; Medicine and physiology, chemistry and physics. The innovations were very impressive particularly the chemistry one which took just 4 years to be awarded, what a feat! Of importance to note was the fact that all the awards were impactful to the field of biological sciences, maybe that's why its known as the science of life 😃. The award for medicine and physiology was for the discovery of a vital regulatory mechanism used in cells to control gene activity. This research was done in in the 90s which makes it all the more interesting. With research moving more towards genetic research, this is vital to the advancement of biological research. It also goes to show the importance of Biological research in improving healthcare outcomes. The award for chemistry was for computational protein design and for physics was for machine learning with artificial neural networks. These awards show how computational biology and machine learning can be leveraged to speed up biological discoveries and change genetic research that will improve agriculture, healthcare and drug discoveries.