Tag: AlphaFold

Global Proteomics Market Top Key Leaders, Industry Analysis, Size, Share, Revenue Growth And Forecast 2028

PRESS RELEASE Published February 6, 2023 Global Proteomics Market size was valued at USD 25.39 billion in 2021, and it is expected to reach a value of USD 75.29 billion by 2028, at a CAGR of more than 16.8% over the forecast period (2022–2028). As the world of genomics continues…

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20 generative AI power players in Europe

As excitement around generative AI continues to sweep across the world of tech and startups, it can be difficult to know who to listen to, as just about everyone seems to be an expert on the topic now. So who are the European founders, experts and operators worth knowing in…

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How will AI and automation change chemistry? | Opinion

In January, Jennifer Newton asked how long it would be until an AI was listed among the authors on a research paper. Well, it turns out the answer was not very long at all. ChatGPT, the generative text algorithm that has rapidly become a cultural phenomenon, was recently listed as…

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PhD fellowship in Bioinformatics/Data Science at the Department of Drug Design and Pharmacology – University of Copenhagen – job portal

Job Portal PhD fellowship in Bioinformatics/Data Science at the Department of Drug Design and Pharmacology Faculty of Health and Medical Sciences University of Copenhagen We are looking for a highly motivated and ambitious bioinformatician / data scientist for a three-year PhD fellowship commencing 1 May 2023 or as soon as…

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In Pursuit of Rare, Subtle, and Fleeting Post-Translational Modifications

Post-translational modifications (PTMs)—the chemical changes that proteins undergo following biosynthesis—account for most protein forms, or proteoforms. Indeed, according to conservative estimates, there are 1 million proteoforms, 90% of which are believed to be PTM-derived proteoforms. Estimates for the number of proteoforms and the percentage of PTM-derived proteoforms sometimes range quite…

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Phylogenetic and AlphaFold predicted structure analyses provide insights for A1 aspartic protease family classification in Arabidopsis

Introduction Proteases regulate various biological processes including protein synthesis and maturation, activity modification, degradation and turnover. Depending on their catalytic mechanisms, these proteases are primarily classified into cysteine, metallo-, serine, threonine and aspartic protease family (Beers et al., 2004). The latter protease family is known as acid protease family because they…

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Google’s MusicLM Generates Music from Text

Google Research has released a new generative AI tool called MusicLM. MusicLM can generate new musical compositions from text prompts, either describing the music to be played (e.g., “The main soundtrack of an arcade game. It is fast-paced and upbeat, with a catchy electric guitar riff. The music is repetitive…

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AI and Computational Design Advance Protein Engineering

Therapeutic protein design is evolving—and it is doing so in more than one sense of that word. Protein design is being guided by artificial intelligence (AI), which drug developers are using to systematically exploit the complex physical mechanisms behind macromolecule formation in nature. Indeed, drug developers anticipate that AI technology…

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AlphaFill: An AI Algorithm to Fill Missing Ligands and Cofactors in AlphaFold Models

According to Levinthal’s paradox, each protein may adopt around 10300 distinct structures. We now know 3-D structures for about 98% of the human proteome thanks to DeepMind’s AI system, AlphaFold. However, AlphaFold has limitations, such as its inability to generate coordinates for tiny molecules and ligands that are critical to…

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AlphaFold models of NF155, CNTN1 and Caspr extracellular domains

Citation Deane, J., McKie, S., & Graham, S. (2023). AlphaFold models of NF155, CNTN1 and Caspr extracellular domains [Dataset]. doi.org/10.17863/CAM.93310 Description AlphaFold2 Multimer models and associated quality statistics for NF155-ECD, CNTN1-ECD and Caspr-ECD generated using default parameters and run via a locally installed version of ColabFold (version 1.3.0). The final…

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Postdoc in Bioinformatics/Data Science at Department of Drug Design and Pharmacology – University of Copenhagen – job portal

Job Portal Postdoc in Bioinformatics/Data Science at Department of Drug Design and Pharmacology Faculty of Health and Medical Sciences University of Copenhagen We are looking for a highly motivated and dynamic postdoc for an ambitious bioinformatician / data scientist for a two-year Postdoc with possibilities for extension commencing 1 May…

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issues with amber_minimize.py failing to use CUDA within alphafold

issues with amber_minimize.py failing to use CUDA within alphafold 0 When I try and run alphafold from ubuntu command line with amber enabled, it’s throwing these errors. I0125 17:33:14.174568 47215575258112 amber_minimize.py:407] Minimizing protein, attempt 1 of 100. I0125 17:33:14.555528 47215575258112 amber_minimize.py:68] Restraining 685 / 1336 particles. I0125 17:33:14.747518 47215575258112 amber_minimize.py:417]…

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EMDB < EMD-28585

Field: Choose…EMDB IDTitleAuthorORCIDEM methodCurrent statusDeposition dateRelease dateDeposition siteLast processing siteFitted modelsRaw dataResolutionResolution methodSoftwareLigand nameComplex nameDomain nameDrug nameGO term nameInterPro term nameChEBI term nameExternal reference Publication titlePublication yearJournalPublication author Sample typeSample nameOrganismOrganism (NCBI code)StrainOrganTissueCellOrganelleCellular LocationE.C. numberMolecular Weight methodMolecular Weight (Da)Recombinant ExpressionRecombinant organismRecombinant organism (NCBI code)Recombinant strainRecombinant expression cellRecombinant expression plasmidDNA/RNA classificationDNA/RNA…

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EMDB < EMD-13594

Field: Choose…EMDB IDTitleAuthorORCIDEM methodCurrent statusDeposition dateRelease dateDeposition siteLast processing siteFitted modelsRaw dataResolutionResolution methodSoftwareLigand nameComplex nameDomain nameDrug nameGO term nameInterPro term nameChEBI term nameExternal reference Publication titlePublication yearJournalPublication author Sample typeSample nameOrganismOrganism (NCBI code)StrainOrganTissueCellOrganelleCellular LocationE.C. numberMolecular Weight methodMolecular Weight (Da)Recombinant ExpressionRecombinant organismRecombinant organism (NCBI code)Recombinant strainRecombinant expression cellRecombinant expression plasmidDNA/RNA classificationDNA/RNA…

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Isolation and infection cycle of a polinton-like virus virophage in an abundant marine alga

Koonin, E. V. & Dolja, V. V. Virus world as an evolutionary network of viruses and capsidless selfish elements. Microbiol. Mol. Biol. Rev. 78, 278–303 (2014). Article  CAS  Google Scholar  Pritham, E. J., Putliwala, T. & Feschotte, C. Mavericks, a novel class of giant transposable elements widespread in eukaryotes and…

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five areas set to be transformed in 2023 –

2022 was a banner year for genomics. In March, the collaborative T2T consortium published the first complete telomere-to-telomere sequence of the human genome, filling in the last 8% of the 3 billion base pairs that make up our DNA. And in the UK specifically, genomics remained high on the national…

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OpenAI’s Tiny Army vs Meta-Google’s Dream Team

With a lean workforce of just about 375 individuals, San Francisco-based OpenAI has achieved an impressive record of breakthroughs and advancements in the field of AI, especially in the past two years. Chief Sam Altman recently took to Twitter to applaud and “not brag” about the talent density of the…

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AI Finds Drug Candidate for Liver Cancer in 30 days

DeltaWorks/Pixabay A major artificial intelligence (AI) breakthrough occurred that may herald the start of a new era in drug discovery that may completely revamp biotechnology, pharmaceutical, healthcare, and life sciences industries. Scientists have broken new ground with the AI discovery of a novel drug candidate for liver cancer in just…

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The Frontiers of Knowledge Award goes to Davi

image: David Baker, Frontiers of Knowledge Award winner in Biomedicine. view more  Credit: BBVA Foundation. The BBVA Foundation Frontiers of Knowledge Award in Biology and Biomedicine has gone in this fifteenth edition to David Baker, Demis Hassabis and John Jumper “for their contributions to the use of artificial intelligence for the…

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Efficient Discovery of a Novel Small Molecule Inhibitor CDK20

A new study uses AlphaFold to identify a potential new treatment for liver cancer The application of AlphaFold in identifying potential liver cancer drugs has been making waves in the medical community. A new study published in Chemical Science, “AlphaFold Accelerates AI-Powered Drug Discovery: Efficient Discovery of a Novel Small…

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Study reveals dynamics of DNA ligation during genome replication

AlphaFold prediction of the Lig1–PCNA complex. a First ranked model showing the Lig1 N-terminal region (residues 1-263) and Lig1 Core (residues 264-919) as yellow and red ribbons, respectively, and PCNA trimer as ribbons in different shades of blue. The insets show close-ups of the three predicted binding sites and associated…

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First Application of AlphaFold in Identifying Potential Liver Cancer Drug

Of the thousands of diseases that affect humans, treatments exist for only a handful. This lack of available therapeutics and efficiency in drug discovery and development processes is poised for transformation with the advent of artificial intelligence (AI). AlphaFold’s phenomenal success in predicting protein structures for the entire human genome…

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Case study: AlphaFold uses open data and AI to discover the 3D protein universe

Open data played a pivotal role in the development of the AlphaFold AI. The same open principles now apply to AlphaFold predictions. Credit: Nuclear pore complex prediction by AlphaFold.Edited by Karen Arnott/EMBL-EBI.Background image from Adobe Stock Images Related links AlphaFold predicts structure of almost every catalogued protein known to science…

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The Rad52 SSAP superfamily and new insight into homologous recombination

Mortensen, U. H., Lisby, M. & Rothstein, R. Rad52. Curr. Biol. 19, R676–R677 (2009). Article  CAS  Google Scholar  Newing, T. et al. Redβ177 annealase structure reveals details of oligomerization and λ Red-mediated homologous DNA recombination. Nat. Commun. 13, 5649 (2022). Article  CAS  Google Scholar  Caldwell, B. J. et al. Structure…

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Alphafold in Linux – HHblits error

When I try to run alphafold on a cluster from the ubuntu shell, I am getting this error in HHBlits: RuntimeError: HHblits failed stdout: stderr: 17:40:03.749 ERROR: Could find neither hhm_db nor a3m_db! Does anybody know why this might be happening? I assumed it would be an issue with the…

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Rare 7kg meteorite found in Antarctica, one of five new space rocks discovered

New Delhi: An international team of scientists has discovered five new meteorites, including one that weighs a whopping 7.6 kilograms from Antarctica. According to the researchers, including those from the Field Museum, Chicago, and the University of Chicago, out of the roughly 45,000 meteorites retrieved from Antarctica over the past…

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Database Of Human Protein Structures Released

The most important database since the mapping of the human genome has been released freely and openly, revolutionising the life sciences industry overnight. The collaboration between the European Molecular Biology Laboratory (EMBL) and Google-owned artificial company DeepMind, has led to the release of a database of over 20,000 3D structures…

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[chimerax-users] ChimeraX Alphafold Multiple jobs

[chimerax-users] ChimeraX Alphafold Multiple jobs Tom Goddard goddard at sonic.net Fri Dec 16 12:37:56 PST 2022 Hi Rayees, ChimeraX can only run one AlphaFold prediction at a time. I tried various tricks to run two predictions at a time and they did not work. I tried starting two copies of…

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protein-folding contest seeks next big breakthrough

A protein’s function is determined by its 3D shape.Credit: Leonid Andronov/Alamy “In some sense the problem is solved,” computational biologist John Moult declared in late 2020. The London-based company DeepMind had just swept a biennial contest co-founded by Moult that tests teams’ abilities to predict protein structures — one of…

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Liberate Bio is Bringing Precision Delivery to Genetic Medicines

The development of efficient delivery technologies has lagged behind significant advancements in nucleic acid therapeutics, such as antisense oligonucleotids (ASOs), short interfering RNA (siRNA), mRNA therapeutics, and genome editors. There must be a renaissance in genetic medicine delivery for these strategies to realize their full potential. Increasingly, the greatest hope…

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EMDB < EMD-20433

Field: Choose…EMDB IDTitleAuthorORCIDEM methodCurrent statusDeposition dateRelease dateDeposition siteLast processing siteFitted modelsRaw dataResolutionResolution methodSoftwareLigand nameComplex nameDomain nameDrug nameGO term nameInterPro term nameChEBI term nameExternal reference Publication titlePublication yearJournalPublication author Sample typeSample nameOrganismOrganism (NCBI code)StrainOrganTissueCellOrganelleCellular LocationE.C. numberMolecular Weight methodMolecular Weight (Da)Recombinant ExpressionRecombinant organismRecombinant organism (NCBI code)Recombinant strainRecombinant expression cellRecombinant expression plasmidDNA/RNA classificationDNA/RNA…

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“Our generation will see an artificial intelligence that equals or exceeds that of the human being”

since he saw as a child 2001: A Space Odyssey, Oriol Vinyals knew that he wanted to dedicate himself to artificial intelligence. “I was very interested in how naturally Hal 9000, the computer, spoke. Could we achieve something like this?”, this teenager from Sabadell was already wondering. Today, at 39,…

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Ancient origin and constrained evolution of the division and cell wall gene cluster in Bacteria

Miyakawa, T., Matsuzawa, H., Matsuhashi, M. & Sugino, Y. Cell wall peptidoglycan mutants of Escherichia coli K-12: existence of two clusters of genes, mra and mrb, for cell wall peptidoglycan biosynthesis. J. Bacteriol. 112, 950–958 (1972). Article  CAS  PubMed  PubMed Central  Google Scholar  Ayala, J. A., Garrido, T., De Pedro,…

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Much ado about artifical intelligence

In 2017, I visited one of the world’s first and most innovative artificial intelligence companies, DeepMind Technologies on Pancras Square in London. This was an eye-opening experience for me as it heightened my understanding of what the best people in the game worked on and just how far exactly the…

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Meta’s new AI just predicted the shape of 600 million proteins in 2 weeks

Scientists at Meta, the parent company of Facebook and Instagram, have used an artificial intelligence (AI) language model to predict the unknown structures of more than 600 million proteins belonging to viruses, bacteria and other microbes. The program, called ESMFold, used a model that was originally designed for decoding human…

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New Algorithms That Harnessed Protein-folding Power in 2022

Big pharma companies have been researching protein folding for a long time now. Discoveries and innovations in the field can revolutionise the development of drug and other biological advancement. Recently, the development of the COVID-19 vaccine was also supported by tackling this issue.  Protein folding prediction process involves a combination…

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Protein folding with Alphafold 2, Mon, Nov 14, 2022, 6:00 PM

After a long hiatus, Papers We Love Montreal will be meeting again! Max McCrea will present “Highly accurate protein structure prediction with AlphaFold” by Jumper, J., Evans, R., Pritzel, A. et al. In 2018, Deepmind submitted a model to the Critical Assessment of protein Structure Prediction (CASP) competition whose results…

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Measuring perception in AI models

New benchmark for evaluating multimodal systems based on real-world video, audio, and text data From the Turing test to ImageNet, benchmarks have played an instrumental role in shaping artificial intelligence (AI) by helping define research goals and allowing researchers to measure progress towards those goals. Incredible breakthroughs in the past…

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The determination of the effect(s) of solute carrier family 22-member 2 (SLC22A2) haplotype variants on drug binding via molecular dynamic simulation systems

International Diabetes Federation (IDF). Diabetes Atlas 8th Edition 2017. www.idf.org/our-network/regions-members/africa/welcome.html. Accessed 15 July 2018 (2018). Singh, S., Usman, K. & Banerjee, M. Pharmacogenetic studies update in type 2 diabetes mellitus. World J. Diabetes. 7, 302. doi.org/10.4239/wjd.v7.i15.302 (2016). Article  PubMed  PubMed Central  Google Scholar  Inzucchi, S. E. et al. Management of…

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How to interpret AlphaFold structures

This webinar will introduce AlphaFold system for prediction and interpretation of protein structures. This webinar is designed for experimental biologists who wish to understand the strengths and limitations of AlphaFold and use the models to guide their experimental studies. In this webinar we will provide an overview for the AlphaFold…

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Confrontation of AlphaFold models with experimental structures enlightens conformational dynamics supporting CYP102A1 functions

Prediction of alternate structures of CYP102A1 The competitive modelling approach was designed considering that the CYP102A1 FMNd must form alternate electron transfer complexes with the FADd and the P450d to support catalytic cycles, but that a direct electron transfer from FADd to P450d is not possible. In the dimeric structure…

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biomedical research: A database of 200 million-plus protein shapes is hypercharging biomedical research

On July 28, DeepMind, an artificial intelligence (AI) subsidiary of Alphabet, Google’s parent company, published a free, online database of the likely shapes of more than 200 million proteins known to science. This has set off a virtual carnival of biomedical research, which will transform healthcare as well as research…

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Can AlphaFold be used?MIT new research: not much better than random guessing, still needs to continue to improve

After AlphaGo defeated Ke Jie, the world’s No. 1 Go player in 2017, AlphaFold 2 was born in 2020, making artificial intelligence (AI) successful again. 2 years later, what about AlphaFold today? In July this year, DeepMind and EMBL-EBI used AlphaFold to predict almost all known proteins on the earth,…

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Bioinformatics Scientist I/II – Codexis

          Are you ready to join our mission to improve the health of people and the planet?  Do you have a passion for science and the transformational role that enzymes are playing?   Come be part of our team at Codexis, Inc. We are a leading enzyme engineering company leveraging our…

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AlphaFold reveals the structure of the protein universe

Just one year after its breakthrough release of predicted structures for some 350,000 proteins, DeepMind has unveiled the likely structures of nearly all known proteins — more than 200 million from bacteria to humans — paving the way for the development of new medicines or technologies to tackle global challenges…

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AI Continues To Build The Foundation For A Remarkable Future In Biology

Black_Kira By Christopher Gannatti July 28, 2022, was a historic day in both biology and artificial intelligence (AI). DeepMind, an Alphabet-owned (GOOG) (GOOGL) AI research firm, made the structural data on more than 200 million proteins from its AlphaFold tool freely available. This represents data on roughly 1 million species…

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DeepMind has predicted the shape of every protein known to science. How excited should we be?

It doesn’t have much photogenic appeal or the glamour of seeing back in time, but a new development in computational biochemistry has been hailed as a discovery as important as the images of distant galaxies recently seen through the James Webb Space Telescope. Researchers at DeepMind—the AI company owned by…

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AlphaFold, Google’s AI that holds the key to finding a cure for cancer or Alzheimer’s

Share Google succeeds in opening the key to finding the cure for diseases such as cancer or Alzheimer̵7;s. AlphaFold, your AI system has the answer. We all know that companies like Google work with systems based on artificial intelligence that are unique in the world and can solve problems that…

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How AlphaFold can realize AI’s full potential in structural biology

Tomorrow’s AI applications will not happen without research being shared openly in repositories such as that maintained by the European Molecular Biology Laboratory’s European Bioinformatics Institute near Cambridge, UK.Credit: Edmund Sumner/View Pictures/Universal Images Group/Getty “I wake up and type AlphaFold into Twitter.” John Jumper couldn’t hold back his excitement. He…

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DeepMind research cracks structure of almost every known protein

Enlarge / An image released by the EMBL’s European Bioinformatics Institute showing the structure of a human protein that was modeled by the AlphaFold computer program. EMBL-EBI/AFP/Getty Images Artificial intelligence has surpassed the limits of scientific knowledge by predicting the shape of almost every known protein, a breakthrough that will…

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This Vast Database Could Upend Science Research

The database includes information that could be incredibly useful to scientists trying to solve some of humanity’s most pressing problems. Seventeen of the database’s proteins relate to “neglected tropical diseases,” which affect the lives of over a billion people worldwide. The Drugs for Neglected Diseases Initiative (DNDI) predicts that the database…

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DeepMind just uncovered the 3D structure of almost every protein known to science

Researchers have deciphered the three-dimensional structures of almost every protein known to science, which could lead to major advances in a wide range of research areas including the treatment of diseases, sustainability and food insecurity. The findings were announced on Thursday by artificial intelligence (AI) technology company DeepMind, which said…

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AI predicts shape of nearly every known protein

The structure of the vitellogenin protein — a precursor of egg yolk — as predicted by the AlphaFold tool.Credit: DeepMind From today, determining the 3D shape of almost any protein known to science will be as simple as typing in a Google search. Researchers have used AlphaFold — the revolutionary…

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Challenges facing AI in science and engineering

Join executives from July 26-28 for Transform’s AI & Edge Week. Hear from top leaders discuss topics surrounding AL/ML technology, conversational AI, IVA, NLP, Edge, and more. Reserve your free pass now! One exciting possibility offered by artificial intelligence (AI) is its potential to crack some of the most difficult…

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Google’s AI helps determine the most complex protein knots so far

A particularly interesting phenomenon occurs for proteins that contain a topological knot in their polypeptide backbone, that is, proteins that do not completely unravel after being pulled from both ends. Over the past two decades, only about 20 different protein families containing knots have been identified. However, knotted proteins present…

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Alpha Fold Working

AlphaFold: The making of a scientific breakthrough The inside story of the DeepMind team of scientists and engineers who created AlphaFold, an AI system that is recognised as a solution to “protein folding”, a grand scientific challenge for more than 50…

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What is AlphaFold? What does it mean for the future of science and humanity? : explainlikeimfive

Alphafold means we can take the “code” of protein structure, which is just the order in which amino acids are arranged in a straight line, and predict the shape of the resulting protein molecule. Alphafold AI allows us to do this much more accurately than we could in the past,…

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2165: Symmetric Pentamer Design with AlphaFold Predictions

2165: Symmetric Pentamer Design with AlphaFold Predictions Status: Active Name: 2165: Symmetric Pentamer Design with AlphaFold Predictions Status: Active Created: 06/24/2022 Points: 100 Expires: 07/01/2022 – 23:00 Difficulty: Intermediate Description: Design a symmetric protein pentamer, with 5 identical…

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How a scientist taught chemistry to the AlphaFold AI

Artificial intelligence has changed the way science is done by allowing researchers to analyze the massive amounts of data modern scientific instruments generate. It can find a needle in a million haystacks of information and, using deep learning, it can learn from the data itself. AI is accelerating advances in gene hunting, medicine, drug…

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File:Human Dact1 Alphafold structure prediction.png

Summary DescriptionHuman Dact1 Alphafold structure prediction.png English: Using algorithm developed in Jumper, J et al. Highly accurate protein structure prediction with AlphaFold. Nature (2021), predicted the 3D structure of human Dact1. Date 5 December 2021 Source alphafold.ebi.ac.uk/entry/Q9NYF0 Author Jumper, J et al. Highly accurate protein structure prediction with AlphaFold. Nature…

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The impact of AlphaFold on experimental structure solution

AlphaFold2 is a machine-learning based program that predicts a protein structure based on the amino acid sequence. In this article, we report on the current usages of this new tool and give examples from our work in the Coronavirus Structural Task Force. With its unprecedented accuracy, it can be utilized…

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Research Engineer – AlphaFold Improvements at DeepMind – London, UK

At DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity,…

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In vivo hypermutation and continuous evolution

Arnold, F. H. Design by directed evolution. Acc. Chem. Res. 31, 125–131 (1998). Google Scholar  Packer, M. S. & Liu, D. R. Methods for the directed evolution of proteins. Nat. Rev. Genet. 16, 379–394 (2015). Google Scholar  Drake, J. W., Charlesworth, B., Charlesworth, D. & Crow, J. F. Rates of…

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Predicted complexes from ModelArchive now on PDBe-KB pages

High-quality, predicted protein complexes, generated using RoseTTAFold and AlphaFold, are now available in ModelArchive and accessible through the 3D-Beacons Network. These predicted complexes are also integrated into the PDBe-KB aggregated views of proteins. High-quality, predicted protein complexes, generated using RoseTTAFold and AlphaFold, are now available in ModelArchive and accessible through…

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Nature Depth: Where will this revolutionary technology go when artificial intelligence predicts protein structure?

▎ WuXi AppTec content team editor Last July, DeepMind published a study in the journal Nature on artificial intelligence (AI) systems AlphaFold predicting the three-dimensional structure of proteins based on amino acid sequences. The researchers also released the source code of the AI system, making this technology available to scientists…

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PubReading – PubReading [113] – Highly accurate protein structure prediction with AlphaFold – J. Jumper, P. Kohli, D. Hassabis et al

PubReading by Mando Mourad Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort, the structures of around 100,000 unique proteins have been determined5, but this represents a small fraction of the billions of known protein sequences. Structural…

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What’s next for AlphaFold and the AI protein-folding revolution : biotech

u/zilifrom whoever came up with X-Corp in Google was a genius. For awhile, DeepMind and Google Brain worked on the stuff that you listed. However, nowadays a lot of the research is being directed towards deriving actionable insights that can result in a product. Calico, Verily, and a few other…

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The Statistical Trends of Protein Evolution: A Lesson from AlphaFold Database

Abstract The relationship between species evolution and protein evolution has been remaining as a mystery. The recent development of artificial intelligence provides us with new and powerful tools for studying the evolution of proteins and species. In this work, based on the AlphaFold Protein Structure Database (AlphaFold DB), we perform…

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AlphaFold encodes the principles to identify high affinity peptide binders

Abstract Machine learning has revolutionized structural biology by solving the problem of predicting structures from sequence information. The community is pushing the limits of interpretability and application of these algorithms beyond their original objective. Already, AlphaFold’s ability to predict bound conformations for complexes has surpassed the performance of docking methods,…

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Assist in drug research and development, accelerate alphafold training at low cost from 11 days to 67 hours, and accelerate reasoning 11 times

AlphaFold By Science and Nature The selection of 2021 year The top ten scientific breakthroughs . LuChen technology and Huashen Zhiyao jointly open source AlphaFold Training reasoning acceleration scheme FastFold, take GPU Optimization and large model training technology are introduced AlphaFold The training and reasoning of , Will succeed AlphaFold…

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Time for Proteomics To Shine

This article includes research findings that are yet to be peer-reviewed. Results are therefore regarded as preliminary and should be interpreted as such. Find out about the role of the peer review process in research here. For further information, please contact the cited source. Over the last 20 years, advances…

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A-Prot: protein structure modeling using MSA transformer | BMC Bioinformatics

Benchmarking contact prediction First, we benchmarked the long-range contact prediction performance of A-Prot using the FM and FM/TBM targets of CASP13 [24]. The benchmark results show that the performance of our model outperforms that of the existing methods (Table 1). We compared the precision of our model’s top L/5, L/2,…

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HPC-AI’s FastFold Shortens AlphaFold Training Time from 11 Days to 67 Hours

DeepMind’s AlphaFold 2 grabbed headlines last year by leveraging a transformer-based model architecture to achieve atomic accuracy in protein structure prediction. While the development of deep neural networks (DNNs) has enabled significant performance improvements across a variety of natural language processing and computer vision tasks, AlphaFold’s success showed that DNNs…

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When proteome meets AI, what is accelerated

What meaningful or interesting information can an ordinary person obtain by performing mass spectrometry detection of the whole blood proteome? Who will be the 23andMe (DNA identification company) in the proteome space? In July last year, when 98.5% of the protein structure of the human proteome was deciphered by the…

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Predicting the structure of large protein complexes using AlphaFold and sequential assembly

Abstract AlphaFold and AlphaFold-multimer can predict the structure of single- and multiple chain proteins with very high accuracy. However, predicting protein complexes with more than a handful of chains is still unfeasible, as the accuracy rapidly decreases with the number of chains and the protein size is limited by the…

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Crystallography, cryo-EM and AlphaFold shed light on key human antibacterial proteins

Figure 1. Model of the human UMOD/FimH interaction, assembled by combining the structural information described in the study. A, The high-mannose sugar chain (green) of the decoy modules branching out from a filament of UMOD (shades of blue) is bound by the FimH sugar-binding domain at the tip of bacterial…

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AI revolutions in biology: Opinions on Alphafold from Instruct-NL

Anastassis Perrakis and Titia Sixma of Instruct-NL explore the role that the new AlphaFold AI system has in the world of structural biology. The paper, published in EMBO Reports, outlines the problems that have been facing computerised protein prediction models since their inception nearly 40 years ago, and assesses the…

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AlphaFold, GPT-3 and How to Augment Intelligence with AI

This is the first post in a two-part series. Read Part 2 here. Around the same time that Alan Turing was shaping his theories of machine intelligence in Manchester, another future giant of the computing world, Douglas Engelbart, was developing an alternative computing paradigm over 5,000 miles away in…

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Google Researchers Use Machine Learning Approach To Annotate Protein Domains

Source: www.nature.com/articles/s41587-021-01179-w.epdf Proteins play an important part in the construction and function of all living organisms. Each protein is made up of a chain of amino acid building blocks. Much like an image might have numerous things, a protein can have multiple components, known as protein domains. Researchers have been…

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DNASTAR Releases NovaFold AI Powered by AlphaFold 2

February 28, 2022, Madison, WI DNASTAR® announced today a new release of their leading protein structure prediction software, NovaFold, that incorporates the award-winning AlphaFold 2 AI system developed by Google-owned DeepMind. AlphaFold 2 was the top-ranked protein structure prediction method in the CASP14 challenge in 2020, significantly outperforming the other…

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DeepMind’s AlphaFold changed how researchers work

Hassabis has been thinking about proteins on and off for 25 years. He was introduced to the problem when he was an undergraduate at the University of Cambridge in the 1990s. “A friend of mine there was obsessed with this problem,” he says. “He would bring it up at any…

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Requirement of Xk and Vps13a for the P2X7-mediated phospholipid scrambling and cell lysis in mouse T cells

Significance The extracellular concentration of adenosine triphosphate (ATP) reaches several hundred micromoles in the inflamed tissues or tumor environment. A high concentration of ATP activates P2X7, a purinergic receptor, and induces the formation of a nonselective cation channel, accompanied by reversible phosphatidylserine (PtdSer) exposure, leading to cell lysis. Here, we…

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Learning from Deep Learning: inspirational story behind AlphaFold

DeepMind Chief Executive visits EMBL Heidelberg to discuss current and future implications of Artificial Intelligence for life science research A delegation from DeepMind visited EMBL Heidelberg to discuss current and future implications of Artificial Intelligence for life science research (John Jumper 2nd from left, Edith Heard 6th from left, Demis…

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google colaboratory – AlphaFold out of memory error with 15 GB of RAM and 95 GB of disc space unused?

I’m trying to use this notebook to run AlphaFold to predict the structure of a large protein. I’ve used this notebook many times for proteins of reasonable size (300-800 aa, if that’s helpful) without any problems, but this protein is almost 2,400 aa. I first tried to run it on…

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google cloud platform – AlphaFold on VertexAI – Stuck in setting up notebook for 2 hours

I finally gave up and Canceled the notebook creation. When I went back to the Workbench screen, THEN it displayed me this error message: So, turns out that the new Google Cloud account I created has no quota for GPUs. In order to increase the quota, I first had to…

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Seven technologies to watch in 2022

The Telomere-to-Telomere Consortium is sequencing whole chromosomes.Credit: Adrian T. Sumner/SPL From gene editing to protein-structure determination to quantum computing, here are seven technologies that are likely to have an impact on science in the year ahead. Fully finished genomes Roughly one-tenth of the human genome remained uncharted when genomics researchers…

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Bioinformatician job with EMBL | 1401746299

Are you creative, curious, and ambitious and like to tackle challenging biological data analysis problems? We have an exciting opportunity for a bioinformatician interested in structural biological data and functional annotations to work within the Protein Data Bank in Europe Team (PDBe) at the European Bioinformatics Institute (EMBL-EBI). In this…

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Deciphering Protein Structure-Dynamics-Function Relationships in the Post AlphaFold Era

AI techniques have come of age – Google DeepMind’s AlphaFold, and other competitive approaches such as RosettaFold, and the more recent efforts at folding RNA structures using Atomic Rotationally Equivariant Scorer (ARES), have enabled accurate predictions of protein and RNA three-dimensional (3D) structures starting with just their primary sequences….

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FASTA Sequences for mutant alleles : bioinformatics

Background: I’m trying to run AlphaFold on an ACT1 allele in yeast e.g. www.yeastgenome.org/allele/act1-105. It has been sequenced, and it has two known amino-acid mutations (E311A, R312A).  My question is: Is there a database that has the .fasta sequence for such alleles, which include the mutations? I can get the fasta sequence…

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2096: Symmetric Trimer Design with AlphaFold Predictions

2096: Symmetric Trimer Design with AlphaFold Predictions Status: Active Name: 2096: Symmetric Trimer Design with AlphaFold Predictions Status: Active Created: 01/15/2022 Points: 100 Expires: 01/21/2022 – 23:00 Difficulty: Intermediate Description: Design a symmetric protein trimer, with 3 identical…

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File:Alpha fold model for DmBCA – Drosophila melanogaster.png

No higher resolution available. Summary DescriptionAlpha fold model for DmBCA – Drosophila melanogaster.png English: This is an alpha fold model of the beta class Carbonic Anhydrase enzyme DmBCA from the invertebrate Drosophila melanogaster. Date 17 December 2021 Source alphafold.ebi.ac.uk/entry/Q9VHJ5 Author AlphaFold Data Copyright (2021) DeepMind Technologies Limited. Jumper, J et…

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Google turns AlphaFold loose on the entire human genome

The AI-driven structural predictions are being shared through a public database. Sloan-Kettering Just one week after Google’s DeepMind AI group finally described its biology efforts in detail, the company is releasing a paper that explains how it analyzed nearly every protein encoded in the human genome and predicted its likely…

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Molecular biologists: let’s reconnect with nature

Charles Darwin’s voyage on HMS Beagle led to a treasure trove of observations: the behaviour of cuttlefish, a parasitic ichneumon wasp feasting inside live caterpillars, fossils of extinct giant sloths and ‘mastodons’. The result, of course, was his theory of natural selection. Darwin needed the complex natural world to inspire…

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Running on CUDA 10.X – Python alphafold

Hi! It looks like our server’s GPU nodes only support up to CUDA 10.2. With the downgraded versions of tensorflow and other modules/packages, will be output consistent with those produced from the default set-up? Thanks! Asked Jul 25 ’21 at 22:21 skyungyong 1 Answer: Hi, Looking at storage.googleapis.com/jax-releases/jax_releases.html it appears…

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The 2021 Good Tech Awards

In the tech industry, 2021 was a year of profits and pivots. Thanks in part to the pandemic and the digitization of our lives, all of the big tech companies got bigger. Facebook changed its name to Meta, Jeff Bezos went to space, Jack Dorsey left Twitter and Silicon Valley…

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Custom genetic database – Deepmind/Alphafold

It is possible, but only with a code change in data/pipeline.py: If the database is a FASTA file, you could add a new Jackhmmer searcher for that database. You can take a look at the jackhmmer_uniref90_runner and basically follow the same logic for your database. If the database is a…

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Bridging functional annotation gaps in non-model plant genes with AlphaFold, DeepFRI and small molecule docking

%PDF-1.4 % 95 0 obj > endobj 103 0 obj >stream 2021-12-22T23:19:29Z Word 2021-12-23T17:11:13-08:00 2021-12-23T17:11:13-08:00 macOS Version 12.0.1 (Build 21A559) Quartz PDFContext application/pdf Bridging functional annotation gaps in non-model plant genes with AlphaFold, DeepFRI and small molecule docking uuid:7ab375c7-1dd2-11b2-0a00-0209277d8900 uuid:7ab375cd-1dd2-11b2-0a00-d30000000000 endstream endobj 5 0 obj > endobj 2 0 obj >…

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CMG lists the top 10 global sci-tech news of 2021

The China Media Group released its list of this year’s top 10 science and technology news from around the world on Monday. It includes major events and discoveries, such as the availability of the FAST telescope for global scientists, China-Russia cooperation on the international lunar base, and the operation of…

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AI-sparked life sciences revolution, greatest scientific achievement of 2021

The revolution that Artificial Intelligence has brought about for the life sciences has been considered by Science magazine the main scientific advance of the year 2021. The prestigious journal highlights the feat carried out by the DeepMind research laboratory, in association with the EMBL European Bioinformatics Institute (EMBL-EBI), which has…

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Gravity, AlphaFold and neural interfaces: a year of remarkable science

. 2021 Dec;600(7890):617-620. doi: 10.1038/d41586-021-03730-w. No authors listed Item in Clipboard No authors listed. Nature. 2021 Dec. Show details Display options Display options Format AbstractPubMedPMID . 2021 Dec;600(7890):617-620. doi: 10.1038/d41586-021-03730-w. Item in Clipboard Cite Display options Display options Format AbstractPubMedPMID No abstract available Keywords: Neuroscience; Physics; Solid Earth sciences; Structural…

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