Alex Zhavoronkov’s Post

The merger of high tech and biotech is transforming healthcare and research. Innovations like AI-integrated labs on a chip enable the synthesis, analysis, and screening of DNA, RNA, and other molecules on microchips, accelerating complex molecular processes. This convergence is driving advances in personalized medicine and diagnostics, promising more efficient and precise treatments and research methods. The fusion of these fields is set to revolutionize our approach to biology and medicine, offering groundbreaking solutions for the future. Stay tuned for more on this exciting evolution!

Google announced AlphaFold 3, the latest update to Google DeepMind's model, which extends beyond proteins to model the 3D structures of all biologically active molecules, including DNA, RNA, and more. AlphaFold 3 uses a generative approach to identify the spatial arrangements of these molecules, improving our understanding of biomolecular interactions and potentially helping identify all-new medicines. Learn more in #TheBatch: https://hubs.la/Q02xNFTV0

Introducing AlphaFold 3, a new AI model developed by #Google #DeepMind and #IsomorphicLabs. By accurately predicting the structure of proteins, DNA, RNA, ligands and more, and how they interact, we hope it will transform our understanding of the biological world and drug discovery. #innovation in #healthcare

AlphaFold3 – protein prediction at the next level: Google DeepMind and Isomorphic Labs unveiled the newest version of AlphaFold, taking its flagship AI model far beyond predicting the structure of a single protein. AlphaFold 3 can now predict a range of complex biological structures that include virtually any biomolecules, including proteins, DNA and RNA strands, and small molecules. A new Nature research paper, published Wednesday, 2024-05-08, shows AlphaFold 3 producing more accurate predictions than both traditional and AI methods for structures showing how proteins interact with ligands, nucleic acids and other proteins. The predictions aren’t just faster but more accurate. AlphaFold 3 was 76% successful in predicting protein and small molecule interactions compared to 52% or lower with the next best models, which includes some from Baker’s lab, according to the Nature paper. Amazing work. https://lnkd.in/esVwsdEY https://lnkd.in/eQjxMmmJ https://lnkd.in/eckru9C9 https://lnkd.in/esxi7Eby https://lnkd.in/edPAHv5X

If you ever had concerns about the growing impact of AI/ML on drug discovery, take a look at the latest version of AlphaFold3. That is scientific progress with deep impact on quality, cost, timelines of drug discovery.

Recently, Google DeepMind and Isomorphism Lab released an AI model that shocked the industry - Alphafold 3, and introduced its powerful functions. The title of the paper published in the journal Nature clearly states that Alphafold3 can predict the structure and interactions of all living molecules with unprecedented accuracy. This means that structural and interaction data for proteins, DNA, RNA, small molecule ligands, and more can be obtained with just a click of the mouse. I have discussed this with several friends who use AI to design antibodies. They generally believe that AI is indeed very helpful in design, but more structural data is needed to improve it. In addition, functional verification is also essential. Some AI users have already used Gator to verify and screen AI-designed antibodies. As demonstrated in the workflow below, the HT GatorPro is the only BLI with 32-high frequency channels with minimal hands-on time and full automation: Quantitation: 1152 samples/2 hrs Kinetics assay: 96 samples/hr Epitope binning/Receptor Blocking: 96 samples/hr #AI # GatorPro #BLI #Antibody #Protein #DNA #RNA

https://lnkd.in/djxhVAHQ This can change the molecules discovery! Introducing AlphaFold 3, a new AI model developed by Google DeepMind and Isomorphic Labs. By accurately predicting the structure of proteins, DNA, RNA, ligands and more, and how they interact, we hope it will transform our understanding of the biological world and drug discovery. The article published in Nature:

This is so inspiring. AlphaFold 3 is published. Why is this important? AlphaFold 3 will transform our understanding of the biological world and drug discovery. It can accurately predict the structure of proteins, DNA, RNA, and more. Google released a very useful tool: AlphaFold Server. A free and easy-to-use research tool that can help discover new drugs. With announcements like this, I feel energized to work in this field. While many people see AI as a threat, I see AI as a hope. ____ 🔔 Press the notification button to get content like this. 📢 Repost if this content is useful. ✏ Comment with your views.

Google DeepMind has unveiled AlphaFold 3, a new #AI model that it said can predict the intricate structures and interactions of proteins, DNA, RNA, and other biomolecules with "unprecedented accuracy." https://lnkd.in/dVdp-ieC #artificialintelligence #clinicalresearch #DeepMind #Google #healthtech #medicalaffairs

#Alchemab is pleased to announce the publication of its paper, 'A generative foundation model for antibody sequence understanding', in bioRxiv!   The paper details FAbCon, Alchemab's #generative foundation model, demonstrating its suitability to facilitate #antibodyengineering with increasing model scale and extensive evaluations.   The model was trained on NVIDIA’s DGX SuperCloud and Amazon Web Services (AWS) SageMaker.   Read more about Alchemab's model, FAbCon, in the paper linked here: https://bit.ly/3KifrjF   #biotech #lifesciences #antibodies