𝗣𝗿𝗼𝘁𝗲𝗶𝗻 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻 𝗪𝗶𝗻𝘀 𝟮𝟬𝟮𝟰 𝗡𝗼𝗯𝗲𝗹 𝗣𝗿𝗶𝘇𝗲 𝗶𝗻 𝗖𝗵𝗲𝗺𝗶𝘀𝘁𝗿𝘆.....not surprising to me! (Aimee Cossins that makes 2/2 correct!). The Royal Swedish Academy of Sciences just announced The Nobel Prize in Chemistry, and it's been split between two groundbreaking advancements in the field of proteins🧬: David Baker has contributed enormously with his incredible work in computational #proteindesign, being able to design entirely new proteins with specific functions, paving the way for new #pharmaceuticals, #vaccines, and #nanomaterials. Demis Hassabis and John Jumper's revolutionary AI model, #AlphaFold2 (Google DeepMind), can predict the complex 3D structures of proteins from their #aminoacid sequence, solving a 50-year-old mystery in #proteinscience. The possibility (and huge advantage) of predicting protein structures holds immense potential and it's already used by millions of #researchers around the world for applications ranging from understanding #antibioticresistance to creating #enzymes that break down plastic. #NobelPrize
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. Learn more Press release: https://bit.ly/3TM8oVs Popular information: https://bit.ly/3XYHZGp Advanced information: https://bit.ly/4ewMBta
Helping Solve Pharma and Diagnostics Manufacturing Problems to Reduce Time to Market
2moI think this one was so obvious though so you get less points for this one! (Hooray for Protein structure and Function) This was one of the things Biosynth featured in our submission to The Medicine Maker "Multifaceted Future of Pharma" article series for their 10 year anniversary- ("views on the future of the pharma and biopharma industries, including key disruptors and what can be improved… The key trends? AI, cell and gene therapies, and a need to reduce costs and improve patient access.")