AlphaFold 3 is a Fantastic Breakthrough and Deserves all the
AlphaFold is helping researchers build models, but it can’t yet simply find all protein states. F@H has always focused on molecular dynamics, while Rosetta@Home (a BOINC project) looked for protein structures and has been more supplanted by AlphaFold. F@H also open sources all its results and was probably used to train AlphaFold.
How important of a breakthrough is DeepMind's AlphaFold?
Nov 28, 2021 · Alicecomma. • 3 yr. ago. The problem with AlphaFold is it's trained on a limited set of known data, specifically annotated data where a large number of similar structures exist. It sucks at predicting membrane proteins and some barrel proteins I fed it, as the active sites tend to be cocked up to the point where it can't fit known substrates.
Announcing AlphaFold 3: our state-of-the-art AI model for
May 8, 2024 · Yes, AlphaFold has been involved in several recent medical breakthroughs and advancements: Accelerating drug discovery for neglected diseases: The Drugs for Neglected Diseases Initiative (DNDi) is using AlphaFold to help identify new drug candidates for diseases like Chagas disease and leishmaniasis that disproportionately affect developing ...
People are overestimating Alphafold and it’s a problem
AlphaFold isn’t saying that, that it is you interpreting the AlphaFold output. Very low pLDDTs are very strongly correlated with flexible or disordered regions. You can’t get high resolution structural info on highly flexible or disordered regions with crystallography or other techniques, so your interpretation would be wrong anyway.
AlphaFold3 was just announced : r/bioinformatics - Reddit
"we describe our AlphaFold 3 model with a substantially updated diffusion-based architecture, which is capable of joint structure prediction of complexes including proteins, nucleic acids, small molecules, ions, and modified residues" the possibilities are endless Too excited to see how it will change the structural bioinformatics
Google DeepMind: AlphaFold 3 predicts the structure and ... - Reddit
In a paper published in Nature, we introduce AlphaFold 3, a revolutionary model that can predict the structure and interactions of all life’s molecules with unprecedented accuracy. For the interactions of proteins with other molecule types we see at least a 50% improvement compared with existing prediction methods, and for some important ...
So what has the consequences so far been of AlphaFold?
Jul 30, 2022 · Drug development takes decades, even if alphafold does all it was promised to it's gonna take years before it creates viable drugs, and thats not even considering pharmaceutical companies having to rewrite lots of their software stack to incorporate it. But in the meantime check out unfolded from the deepmind youtube channel.
AlphaFold: How Google’s AI Solved One of Life’s Greatest Problems
Jul 31, 2021 · Google’s AlphaFold AI solved it in 48 hours by determining the three-dimensional shape of almost all proteins in the human proteome by predicting their amino acid sequence. Scientists explained how AlphaFold findings might bring forward a new era in science by paving the way for potential cures for any and all diseases, from hereditary to ...
What is better right now? AlphaFold or RoseTTAFold?
Jun 5, 2022 · As a structural biologist: alphafold by far. It’s been a hit since I read up on it, but from my understanding alpha fold 2 tended to be more accurate, while roseTTA was able to predict complexes. However I know that recently alpha fold 2 has a multimer colab notebook, not sure how good it is tho.
After AlphaFold cracked a 50-year-old problem of structural
After AlphaFold cracked a 50-year-old problem of structural bioinformatics by learning to predict protein structures, it couldn't solve the mutant protein stability problem. And the AI has not really “learned” the physics of proteins either, a new study concludes.