Tag: AlphaFold

Abstract The speed and accuracy of deep learning-based structure prediction algorithms makes it now possible to perform in silico pull-downs to identify protein-protein interactions at a proteome-wide scale. However, existing scoring algorithms struggle to accurately identify correct interactions at such a large scale, resulting in an excessive number of false…

The scientific enterprise enriches the debate about models. In particular, in the field of structural biology, a new deep-learning neural network system called AlphaFold has been applied for many purposes. It allows us to predict a protein’s structure with high accuracy. I will present the system in light of the…

A few hours before the CASP14 (14th Critical Assessment of Structure Prediction) meeting, the latest biannual structure prediction experiment where participants build models of proteins given their amino acid sequences, this image went viral on twitter. Ranking of participants in CASP14, as per the sum of the Z-scores of their…

The company aims to use the power of AI to tackle various diseases and could receive nearly $3bn from its new research collaborations. DeepMind spin-out Isomorphic Labs has signed two deals with pharma giants to discover new drugs, which could lead to billions in profit for the company. The Alphabet…

Isomorphic Labs is a digital biology company that says its mission is to redefine drug discovery using artificial intelligence (AI) and says the collaboration with Novartis is to discover small molecule therapeutics against three undisclosed targets.   “Isomorphic Labs and Novartis hold a shared purpose to reimagine medicine to improve and…

Isomorphic Labs, a London-based spin-out of Alphabet Inc GOOG GOOGL Google’s AI R&D division DeepMind, has announced strategic partnerships with Eli Lilly And Co LLY and Novartis AG NVS.  These alliances aim to leverage AI to discover new medications to treat diseases.  The combined value of these deals is around $3 billion.  Isomorphic will receive $45 million upfront from Eli Lilly, potentially…

Open this photo in gallery: Dr. Petrina Kamya in her office at Insilico Medicine in Montreal on Dec. 11, 2023. Dr. Kamya is the head of AI Platforms at Insilico Medicine, where her team oversees the development and implementation of artificial intelligence systems in the medical field.Evan Buhler/The Globe and…

Introduction Picture this: your morning alarm isn’t some obnoxious beeping anymore, but a soothing voice reminding you your self-driving car is preheated and your personalized smoothie is ready. Your coffee? Made by a robo-barista who knows you better than your BFF. Welcome to the wild, fascinating world of AI, folks,…

Abstract: Protein science is being transformed by powerful computational methods for structure prediction and design: AlphaFold2 can predict many natural protein structures from sequence, and other AI methods are enabling the de novo design of new structures. This raises a question: how much do we understand the underlying sequence-to-structure/function relationships…

Be carefull when predicting the protein’s topology with AlphaFold Introduction AlphaFold, a deep learning tool, has taken the scientific world by storm, revolutionizing the way we predict protein structures. However, like all groundbreaking technologies, it’s not without its limitations. In this article, we delve into one such limitation: AlphaFold’s struggle…

Abstract The AlphaFold computer program predicted protein structures for the whole human genome, which has been considered as a remarkable breakthrough both in artificial intelligence (AI) application and structural biology. Despite the varying confidence level, these predicted structures still could significantly contribute to structure-based drug design of novel targets, especially…

Pioneering new approaches to drug design Using Chemistry42 to generate compounds based on the predicted CDK20 structure from AlphaFold, more than 8918 molecules were generated. One compound, ISM042-2-001 was particularly successful in cancer cell growth inhibition. Further experimentation following this discovery enabled the team to generate further compounds, eventually finding…

– Advertisement – The science events to watch for in 2024: OpenAI is expected to release GPT-5, the next generation of the AI model that powers ChatGPT, showcasing more advanced capabilities. Google’s GPT-4 competitor, Gemini, is also being closely watched by scientists for its capabilities in processing various types of…

AI advances The rise of ChatGPT had a profound effect on science this year. Its creator, OpenAI in San Francisco, California, is expected to release GPT-5, the next generation of the artificial intelligence (AI) model that underpins the chatbot, late next year. GPT-5 is likely to showcase more advanced capabilities…

AlphaFold, a groundbreaking artificial intelligence (AI) system developed by DeepMind, has revolutionized the field of protein structure prediction. Released in 2020, AlphaFold addresses one of the most significant challenges in biology—accurately predicting the three-dimensional (3D) structures of proteins. This accomplishment has profound implications for understanding diseases, drug discovery, and advancing…

Share Tweet Share Share Email Artificial intelligence (AI) is one of the most exciting and rapidly evolving fields of science and technology. AI has the potential to transform various domains, such as healthcare, education, entertainment, business, and more. In this article, we will…

How AlphaFold2 fits within Nuclera – guided protein design Widely hailed as a breakthrough in biological research and a leap in the development of vaccines and synthetic materials, AlphaFold2 is an AI model developed by DeepMind for predicting the 3D structure of a protein based on its 1D amino acid…

2023 has been a year full of AI developments that helped shape the future across industries. Photo : iStock 2023 was a year where artificial intelligence (AI) truly stepped into the spotlight. From groundbreaking breakthroughs in language models to ethical debates and real-world applications, AI dominated headlines and sparked conversations…

Given the number of advancements artificial intelligence (AI) has made this year itself, it’s no surprise that it has been a significant point of discussion throughout 2023. AI now finds its use case in almost every realm, and one of its exciting and useful applications is in healthcare and medicine….

Deep learning has the potential to enhance molecular docking by improving scoring functions. Current sampling protocols often need prior information to generate accurate ligand binding poses, limiting scoring function accuracy. Two new protocols, GLOW and IVES, developed by researchers from Stanford University, address this challenge, demonstrating enhanced pose sampling efficacy….

Deep learning has the potential to revolutionize molecular docking by improving the accuracy of scoring functions. However, current sampling protocols often require prior information, limiting the effectiveness of these scoring functions. In a breakthrough study, researchers from Stanford University have developed two new protocols, GLOW and IVES, that address these…

What is the impact of AlphaFold on biotechnological research and development? It has limited the scope of biotechnological research to protein folding studies exclusively or It has significantly advanced our ability to predict protein structures, facilitating breakthroughs in drug design and disease understanding or AlphaFold has made traditional laboratory methods…

Abstract The rapid advancement of protein sequencing technology has resulted in a gap between proteins with identified sequences and those with mapped structures. Although sequence-based predictions offer insights, they can be incomplete due to the absence of structural details. On the other hand, structure-based methods face challenges with newly sequenced…

Unfolding the Benefits of AlphaFold for Scientific Discovery Who Stands to Benefit from AlphaFold? Picture a vast sea of scientists, their brows furrowed in concentration, diving deep into the mysteries of proteins and their complex folds. It is these brave explorers who stand to reap the plentiful rewards of AlphaFold…

The company said its FunSearch AI model has an automated ‘evaluator’ to prevent hallucinations, allowing the model to find the best answers for advanced problems. Google-owned DeepMind claims one of its AI models found a new answer for an unsolved mathematical problem, by tackling one of the biggest issues in…

Drug discovery — from original idea to the launch of a finished product — is a complex process that takes 12–15 years and over a billion dollar of investment. Yet, an alarmingly large number of drugs end up as ‘failures’ in one of the three phases of clinical trials. Something…

Summary DescriptionFAM86B1 540px.gif English: Protein structure of human FAM86B1 isoform 1 predicted by AlphaFold. Colored by secondary structure, with alpha helices in red and beta strands in yellow. The SKL2 peroxisomal targeting signal is shown in green. Remaining coils are blue. gif shows FAM86B1 slowly spinning, so that the full…

The RCOR gene repertoire expanded in the ancestor of jawed vertebrates To understand the duplicative history of the RCOR genes, we reconstructed gene phylogenies with different taxonomic samplings. The first analysis aimed to understand the evolution of RCOR genes in vertebrates (Fig. 2), whereas in the second, our sampling effort included…

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Prediction with AlphaFold2 and AlphaFold-Multimer For each PDB the release date in the Protein Data Bank34 was recorded. AlphaFold 2 (2.2.2) was run setting the –max_template_date flag to be the day before the release date of the PDB and the –model_preset to be either monomer for AF or multimer for…

For instance, computational approaches led by the Materials Project and other groups have helped develop 28,000 new materials till date. But this is an expensive and time-consuming process, and researchers may find it difficult to develop radically different structures since they mostly work with existing materials. Recently, though, Google unit…

Image sourced from 3D Tour of the Cell Proteins permeate every corner of our world. Indeed, the entirety of Earth’s organic composition emerges as a result of an intricate choreography involving roughly 200 million proteins. These proteins intricately interlace, giving rise to the myriad structures that underpin the creation of…

The Advent of AI in Scientific Research Artificial Intelligence (AI) is revolutionizing the scientific landscape, accelerating the pace of advancement and discovery in various fields. From medicine to molecular biology, neuroscience, astronomy, and physics, AI models have emerged as powerful tools to foster innovation and optimize processes. Notably, models such…

This summer, a pill intended to treat a chronic, incurable lung disease entered mid-phase human trials. Previous studies have demonstrated that the drug is safe to swallow, although whether it will improve symptoms of the painful fibrosis that it targets remains unknown; this is what the current trial will determine,…

BLAST1 is widely used in molecular biology to search for nucleotide and protein sequences. Three decades after BLAST was introduced, there were major breakthroughs in structure prediction, and tools such as RoseTTAFold2 and AlphaFold3 emerged. Consequently, every protein sequence in the major sequence databases now comes with a model of…

Transcribed image text: 1. Give one of AlphaFold’s limitations in structure prediction. ( 20% ) 2. Give ONE example of intrinsically disordered proteins’ functional advantages. (20 %) 3. Please use the VSL2 algorithm in PONDR to predict the sequence disorder level of human’s TDP-43 (search it from UniProt). (Please show…

The groundbreaking application of artificial intelligence (AI) in creating new proteins is reshaping the landscape of biotechnology, bioengineering, and healthcare. The ability to design proteins with specific functions via AI algorithms presents a new frontier in scientific discovery, enabling researchers to develop innovative solutions across multiple fields. The potential of…

A structure prediction for a massive protein discovered by computational biologist Jacob West-Roberts and his colleagues.Credit: West-Roberts, J. et al./bioRxiv Jacob West-Roberts, a computational biologist at the University of California (UC) Berkeley, was scouring microbial DNA sequences for giant genes and discovered what he thought was a whopper: a gene…

Cell culture All cell lines used in this study were cultured at 37 °C in 5% CO2 in a humidified incubator. Human cell lines were authenticated by STR profiling using Promega GenePrint 10 and tested for Mycoplasma using Mycoalert (Lonza). Other than HCT116 p21−/− (a gift of B. Vogelstein60) all cell…

Carsten Wierwille, CEO of digital product studio ustwo. We help businesses grow by creating digital products and services that matter. getty Rarely has a new technology elicited as strong a response as artificial intelligence (AI). Depending on who you ask, AI will either “save the world” or usher in the…

We created tracks with Alphafold-linked proteins for selected genome browsers allowing for links to predicted 3D structures. Publication: Jumper et al. Nature (2021) – “The AlphaFold Protein Structure Database is available through EMBL-EBI” In those select browsers, you will find the following protein track: The following organisms contain protein tracks…

Google DeepMind has announced its much-anticipated family of artificial intelligence chatbots, Gemini, which will compete with OpenAI’s GPT series. According to Google, Gemini Ultra, its largest and most capable new model, outperforms OpenAI’s most capable model, GPT-4, at a number of text-based, image-based, coding, and reasoning tasks. Gemini Ultra will…

In late 2023, DeepMind unveiled the latest iteration of its revolutionary protein structure prediction system, AlphaFold. Dubbed “AlphaFold 3”, this new version represents a major leap forward, with the ability to predict structures not just for proteins, but for other crucial biological molecules with unparalleled accuracy. The Origins of AlphaFold…

In a remarkable breakthrough, a new artificial intelligence (AI) algorithm has demonstrated an unprecedented ability to predict the three-dimensional structures of proteins with high accuracy. This groundbreaking achievement, published in the journal Nature, marks a significant step forward in the field of bioinformatics and holds immense promise for advancing our…

In the history of AI, two remarkable moments stand out: the success of AlphaGo and the advent of ChatGPT. These two milestones serve as instructive events for analyzing how far we are from truly useful quantum computing. AlphaGo’s 2016 triumph over world champion Go player Lee Sedol marked a pivotal…

Abstract HDAC11 is a class IV histone deacylase with no crystal structure reported so far. The catalytic domain of HDAC11 shares low sequence identity with other HDAC isoforms which makes the conventional homology modeling less reliable. AlphaFold is a neural network machine learning approach that can predict the 3D structure…

As we are nearing the end of 2023, we are probably standing at the high crest of the generative AI wave. From being termed word of the year to being the crux of every major big tech company announcements this year, including Google, Microsoft, and others, it is a no-brainer…

Receptor.AI has announced the ArtiDock – the best-in-class model for “AI docking”, which predicts the binding poses of small molecule ligands in protein binding pockets with unprecedented speed and accuracy. We performed a comprehensive comparison of ArtiDock with the best modern AI docking techniques and with the most widely used conventional…

Like many people I know, I am badly undereducated in biology. Whatever I was taught in high school was instantly forgotten when I left, and I never got near it again. Except that it is in our faces daily — diet, health, diseases, cures — we are all bouncing against…

Why is alphafold revolutionary?3 answersAlphaFold is revolutionary because it has transformed structural biology by predicting protein structures with high accuracy and confidence. It has surpassed the performance of traditional methods in predicting protein-peptide binding conformations. Additionally, AlphaFold’s predictions can be used to predict dynamic protein regions at the individual residue…

Look for AI systems, like AlphaFold, to deliver new models that are more accurate and precise than ever Of the many areas of science to which AI is being applied, it is arguable that the field of protein structure prediction is where it has had the most impact. Programs like…

Centers for Disease Control and Prevention (U.S.). Antibiotic Resistance Threats in the United States, 2019. doi.org/10.15620/cdc:82532 (2019). Centers for Disease Control and Prevention. COVID-19: U.S. Impact on Antimicrobial Resistance, Special Report 2022. doi.org/10.15620/CDC:117915 (2022). Fricks-Lima, J. et al. Differences in biofilm formation and antimicrobial resistance of Pseudomonas aeruginosa isolated from…

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Abstract Machine-learning prediction algorithms such as AlphaFold and RoseTTAFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including new experimental information such as a density map, a greater portion of a…

Abstract Experimental structure determination can be accelerated with artificial intelligence (AI)-based structure-prediction methods such as AlphaFold. Here, an automatic procedure requiring only sequence information and crystallographic data is presented that uses AlphaFold predictions to produce an electron-density map and a structural model. Iterating through cycles of structure prediction is a…

Abstract The precise prediction of Major Histocompatibility Complex (MHC)-peptide complex structures is pivotal for understanding cellular immune responses and advancing vaccine design. In this study, we enhanced AlphaFold’s capabilities by fine-tuning it with a specialized dataset comprised by exclusively high-resolution MHC-peptide crystal structures. This tailored approach aimed to address the…

GNoME alone Google DeepMind is using a new tool that uses deep learning to dramatically speed up the process of discovering new materials. Called graphical networks for material exploration (GNoME), the technology has already been used to predict structures for 2.2 million new materials, of which more than 700 have…

The company claims its AI model has already been used by researchers to create 736 new materials in laboratory settings. Google-owned DeepMind claims to have made a new discovery that could lead to the creation of new materials for future tech. The company said one of its AI models has…

Artificial intelligence (AI) is swiftly becoming a powerful force in the world of science and technology. This isn’t just about machines getting smarter; it’s about how they’re helping us make leaps in understanding and innovation that were once thought impossible. AI is not just a buzzword; it’s a tool that’s…

Researchers at Google DeepMind have used artificial intelligence to predict the structures of more than 2 million new materials, in a breakthrough that could have wide-reaching benefits in sectors such as renewable energy and computing. DeepMind published 381,000 of the 2.2 million crystal structures that it predicts to be most…

If you are not a subscriber to our free, weekly newsletter with fact-based optimistic news, you really should be! 😊 The most surprising news for me in November was that dementia is not increasing, but decreasing. You hear so much about dementia, and with increased lifespans, it seems reasonable that…

The quest for new materials, pivotal for technological breakthroughs in fields like EV batteries, solar cells, and microchips, has historically been a slow and labor-intensive process. This scenario, according to a new report from the MIT Technology Review, is set for a dramatic change with Google DeepMind’s introduction of a…

Overview of the method DeepAssembly is designed to automatically construct multi-domain protein or complex structure through inter-domain interactions from deep learning. Figure 1 shows an overview of the DeepAssembly protocol. Starting from the input sequence of multi-domain protein (or protein complex), DeepAssembly first generates multiple sequence alignments (MSAs) from genetic databases…

GNoME can be described as AlphaFold for materials discovery, according to Ju Li, a materials science and engineering professor at the Massachusetts Institute of Technology. AlphaFold, a DeepMind AI system announced in 2020, predicts the structures of proteins with high accuracy and has since advanced biological research and drug discovery….

Abstract The mitochondrial genome, mtDNA, is present in multiple copies in cells and encodes essential subunits of oxidative phosphorylation complexes. mtDNA levels have to change in response to metabolic demands and copy number alterations are implicated in various diseases. The mitochondrial HMG-box proteins Abf2 in yeast and TFAM in mammals…

AI has been making waves in multiple fields for its ability to detect patterns more efficiently than humans. In one such field, Astrobiology, new deep learning techniques are poised to discover a treasure trove of new protein families that could help unlock new mysteries. In a study published in Nature,…

Hi Structural biologist colleagues! Our article that helps you make the case that the experiment is still very much needed is now out: www.nature.com/articles/s41592-023-02087-4 “AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination.” Nature Methods (2023) Also, here is a video on the Phenix Tutorials…

Scientists are at the forefront of exploring the age-old question of how life began, and they have now turned to cutting-edge artificial intelligence (AI) to unravel the mysteries of our origins. AI, with its powerful machine-learning tools, is helping researchers navigate the complex pathways that led from simple chemical soups…

In recent decades, the development of computational and bioinformatics tools and websites for life sciences has increased exponentially. This great development has gone hand in hand with the availability of genome, proteome and macromolecule structure databases, and also of functional experiments, including microarray and RNAseq expression data, RNA-protein interactions, ChIP-seq,…

Artificial Intelligence (AI) has witnessed unprecedented growth over the past few years. This remarkable growth has led to the development of an array of AI Top Tools, each playing a pivotal role in reshaping industries, enhancing operational efficiency, and redefining the realms of possibility. As we venture into 2023, it’s…

Abstract The European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI) is one of the world’s leading sources of public biomolecular data. Based at the Wellcome Genome Campus in Hinxton, UK, EMBL-EBI is one of six sites of the European Molecular Biology Laboratory (EMBL), Europe’s only intergovernmental life sciences organisation. This…

About Arcadia Science Arcadia Science is pushing the boundaries of open science and innovating at every step in the research, development, and commercialization process. Job Description A Bit About Us:   We are Arcadia Science. Arcadia is a science company founded and led by scientists. Our mission is to transform…

In the ever-evolving landscape of artificial intelligence, Stanford HAI’s fall conference “New Horizons in Generative AI: Science, Creativity, and Society” illuminated the profound impact of AI on scientific exploration. While generative AI for vision and language has garnered public attention, the conference delved deeper, spotlighting the diverse spectrum of generative AI…

Artificial intelligence (AI) has rapidly evolved from a futuristic concept to an integral part of our daily lives. From powering virtual assistants to driving self-driving cars, AI has permeated various industries, transforming how we live, work, and interact with the world around us. As AI continues to advance at an…

# Google Science: Innovations and Contributions in Science Google, primarily known for its search engine, has evolved into a multifaceted tech giant with significant contributions to the field of science. Through its various subsidiaries and initiatives, Google has been at the forefront of technological innovation, pushing the boundaries of what’s…

Wang H, Huang W, Fei Y-J, Xia H, Yang-Feng TL, Leibach FH, et al. Human placental Na+-dependent multivitamin transporter. J Biol Chem. 1999;274:14875–83. Article  CAS  PubMed  Google Scholar  Baumgartner MR, Suormala T. Biotin-responsive Disorders. In: Inborn Metabolic Diseases. Springer Berlin Heidelberg. 2016. p. 375–83. Byrne AB, Arts P, Polyak SW,…

sam13 November 27, 2023, 12:33am 1 GROMACS version: 🙂 GROMACS – gmx grompp, 2023.3-Homebrew (-:GROMACS modification: No Hello,I have been trying to do MD simulation for a protein whose 3D structure is predicted by AlphaFold. The ligand is Aspartate molecule. I am following a similar approach to the Protein-Ligand GROMACS…

Artificial general intelligence, or AGI, has become a much-abused buzzword in the AI industry. Now, Google DeepMind wants to put the idea on a firmer footing. The concept at the heart of the term AGI is that a hallmark of human intelligence is its generality. While specialist computer programs might…

Construction of the VgrG database Encoded as a stand-alone gene or fused at the N-terminus of the toxin, the MIX domains can assist the delivery of their cognate T6SS effector19,20. As the central component of the spike complex, VgrG is a good marker to explore the potential conserved domains involved…

This conference will take place at EMBL Heidelberg, with the option to attend virtually. www.embl.org/about/info/course-and-conference-office/events/csb23-01/  Conference overview The field of computational structural biology is undergoing a revolution. AlphaFold, a program based on Artificial Intelligence (AI), has transformed the structural modeling of proteins and protein complexes by reaching accuracy similar to…

For over 50 years, scientists were stuck on the protein-folding problem. It’s like trying to figure out how a complex origami structure folds up. But then, in 2020, DeepMind’s AlphaFold cracked the code. It aced a big contest by predicting how proteins fold with an amazing 90% accuracy. Jump ahead…

Proteins, the workhorses of biology, are encoded by DNA sequences and are responsible for vital functions within cells. Since the first experimental measurement of a protein structure was made by John Kendrew in the 1950s, protein’s ability to fold into complex three-dimensional structures has long been a subject of scientific…

Preprint Review Version 1 This version is not peer-reviewed Version 1 : Received: 22 November 2023 / Approved: 23 November 2023 / Online: 23 November 2023 (10:53:39 CET) El Badaoui, L.; Barr, A.J. Analysis of Receptor-type Protein Tyrosine Phosphatase Extracellular Regions with Insights from AlphaFold. Preprints 2023, 2023111503. doi.org/10.20944/preprints202311.1503.v1 El…

journal contribution posted on 2023-11-23, 11:51 authored by Marc F Lensink, Guillaume Brysbaert, Nessim Raouraoua, Paul A Bates, Marco Giulini, Rodrigo V Honorato, Charlotte van Noort, Joao MC Teixeira, Alexandre MJJ Bonvin, Ren Kong, Hang Shi, Xufeng Lu, Shan Chang, Jian Liu, Zhiye Guo, Xiao Chen, Alex Morehead, Raj S…

Bacterial strains and growth conditions Veillonella parvula SKV38 was grown in SK medium (10 g/L tryptone [Difco], 10 g/L yeast extract [Difco], 0.4 g/L disodium phosphate, 2 g/L sodium chloride, and 10 ml/L 60% [wt/vol] sodium DL-lactate; described in ref. 51. Cultures were incubated at 37 °C in anaerobic conditions, either in anaerobic bags (GENbag anaero;…

Figure 1. A: Overlaid wild-type (grey) and mutant (color), experimental (orange), and predicted (blue) structures of H-NOX protein. B: Wild-type protein with residues colored by strain (a measure of structural deformation), Si; the location of the mutation (residue 71 is mutated from alanine (A) to glycine (G)) is indicated. C:…

Nowadays, computer vision or machine vision, represented especially by deep convolutional neural networks (DCNNs), has achieved great success in many vision tasks. Compared to biological vision, however, computer vision is still lagging far behind in both performances and variety of capabilities. For instance, DCNNs, which mainly mimic the feedforward and…

how many amino acids are there in casein 5 answers how many genes in the human have a kinase domain? 5 answers How does trypsin and ciclodextrin interact? 5 answers What is symmetry in architecture? 4 answers What are the different methods for microbial pyruvate kinase activity assays? 3 answers…

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…

In the world of science and medicine, there’s always a quest for the next big breakthrough. One such revolutionary development is AlphaFold, an artificial intelligence program developed by DeepMind that’s transforming our understanding of protein structures. This technology is not just a scientific advancement; it represents a fusion of human…

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…

Cohesin is a trimeric complex containing a pair of SMC proteins (Smc1 and Smc3) whose ATPase domains at the end of long coiled coils (CC) are interconnected by Scc1. During interphase, it organizes chromosomal DNA topology by extruding loops in a manner dependent on Scc1’s association with two large hook-shaped…

After reading through papers and the code, I’m still not clear if AlphaFold and the likes do actually calculate the 3d structure. My current feeling they are more like information retrieval engines. They find statistical ‘similarity’ features between the primary structures of the query protein and a database protein (or…

If ATP-dependent dissociation of Scc1’s NTD from the Smc3 neck is a feature intrinsic to Smc-kleisin trimers, then how might Wapl enhance this process? To address this, we used AF to explore how Wapl is first recruited to cohesin and second what effect it has on the configuration of cohesin’s…

Your Profile: Requirements Ph.D. in Immunology, Biophysics, Protein Engineering, Microbiology, Systems/Computational Biology or related discipline, along with experience and interest in humoral immunology in infectious disease and immunogen design. Ability to work independently, as well as in a collaborative environment to meet project goals Excellent written and oral communication skills…

The work and excellence of EMBL researchers have been recognised with multiple awards and honours during the past six months. Three EMBL predocs, Constantin Ahlmann-Eltze in the Huber Group at EMBL Heidelberg, Charlie Barker in the Petsalaki Group at EMBL-EBI, and Sora Matsumoto in the Saka Group at EMBL Heidelberg…

Long before OpenAI was wowing the world with ChatGPT, there was DeepMind.  Founded in 2010 in London, it built a team of researchers plucked from the UK’s top universities, who have since pioneered some of the world’s most high-profile breakthroughs in AI, including the protein structure prediction system AlphaFold in…

Whether you’ve been stung by an insect or suffer from allergies, most people have experienced itchy skin, which usually can be relieved with time or simple remedies. However, for certain patients with liver disease, an intense itching sensation, known as cholestatic pruritis — the medical term for itch — often…

Good morning. A big thank you to Milltown Partners, too, and everyone involved in the AI Fringe, for putting on such an exciting range of events…of course, not just here in London but right across the UK – in Oxford, Cambridge, Bristol, Edinburgh and beyond. AI has the potential to…

Google’s AI Empire: A Closer Look at the Technologies Owned by the Tech Giant In the ever-evolving landscape of artificial intelligence (AI), Google has emerged as a dominant force, harnessing cutting-edge technologies to revolutionize various industries. With a vast array of AI-powered products and services, it’s no wonder that Google…