Congrats to EvolutionaryScale for the release of ESM3, an LLM that uses sequence, structure and function to generate new proteins. The model is now on Latch for non-commercial use and gives the academic community access to their cutting-edge industrial research with a few clicks.
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Thermo Fisher Scientific continues to play a major role in the advancement of #cryoEM. Learn about the history and impact of this #ElectronMicroscopy technique, from fundamental research to #DrugDiscovery: https://ter.li/sni9lv
Cryo-EM: Building On a History of Invention and Innovation
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Here we developed a New Method of Graphene Oxide Film formation at the Air/Water Interface. One of my Innovative Works at #ArgonneNationalLaboratory #GrapheneOxide #Interface #Graphene #SFG #Synchrotron #Separation
The best way to avoid substrate effects is to do measurements directly at the air/water interface. Raju Kumal, PhD and Amanda J. Carr, PhD describe a simple method to prepare thin #grapheneoxide films at this interface. Now published in RSC Advances. https://lnkd.in/gNACkQcV
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Mechanical signaling is key in many biological processes. But how do you trigger and quantify these mechanical cues on the level of single cells or molecules? Read how the lab of Carlos Bustamante got surprising insights! https://bit.ly/41mI0Eq
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This paper demonstrates how #terahertz (#THz) signaling can control changes in #protein #shapes in a random environment. The authors studied a communication system involving a #nano-#scale antenna transmitter, a protein receiver, and a channel made up of moving red blood cells. They analyzed the system's selectivity to see how effectively the induced THz interaction could target a specific group of proteins under fading conditions. By optimizing the selectivity metric based on the nanoantenna power and frequency, they enhance the controllability of protein interactions. ---- Hadeel Elayan More details can be found at this link: https://lnkd.in/gAquJr3b
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PhD in (Computational) Chemistry | Multidisciplinary oriented | Prepared to solve any problem at hand, using practical skills and a little bit of quantum magic!
Our latest research represents a deep dive into light-induced synthesis⚗ ✨ : theoretically 💡 ILLUMINATED 💡 intramolecular [2+2] cycloaddition!
Regio‐ and Stereoselective, Intramolecular [2+2] Cycloaddition of Allenes, Promoted by Visible Light Photocatalysis
onlinelibrary.wiley.com
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Master in Organic chemistry | Interest in scientific research | UV | IR | 1D & 2D NMR | Mass | X-ray crystallographic
I'm glad that i participated in #ASC Fall 2023 event which promotes groundbreaking discoveries and public understanding of the world’s mounting challenges and how chemistry can provide solutions. I prepared my poster presentation entitled: (Highly functionalized spirooxindole pyrrolidines: Stereoselective synthesis and their structural elucidation)
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Here, a collaborative research team, including some of my Thermo Fisher Scientific colleagues, reveal the gas-phase structure of β-galactosidase using single-particle #cryoEM down to 2.6-Å resolution, enabled by soft landing of mass-selected protein complexes onto cold TEM grids followed by in situ ice coating. "By providing a direct link between high-resolution imaging and the capability to handle and select protein complexes that behave problematically in conventional sample preparation, the approach has the potential to expand the scope of both native #MassSpectrometry and cryo-EM."
Cryo-EM of soft-landed β-galactosidase: Gas-phase and native structures are remarkably similar
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Exciting advancements in #ProteinDesign! Researchers have developed a deep learning framework, RoseTTAFold Diffusion, that excels in designing new proteins, including de novo binder design and higher order symmetric architectures. This breakthrough could revolutionize therapeutic and metal-binding protein design, paving the way for more effective treatments in the future. #DeepLearning #Biotech #FutureOfMedicine
A paper in Nature describes a highly accurate deep-learning approach for designing novel proteins, termed RoseTTAFold Diffusion. The method enables the generation of diverse functional proteins, including structural topologies that have never been seen in natural proteins. Read the paper: https://lnkd.in/erVxxMnU
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Update: We have taken down the model per their request. We also apologize to their team for our misunderstanding that we could host this if it was exclusively for free academic use.