Accurate prediction of protein structures and interactions using a three-track neural network

Science, Journal Year: 2021, Volume and Issue: 373(6557), P. 871 - 876

Published: July 15, 2021

Deep learning takes on protein folding In 1972, Anfinsen won a Nobel prize for demonstrating connection between protein’s amino acid sequence and its three-dimensional structure. Since 1994, scientists have competed in the biannual Critical Assessment of Structure Prediction (CASP) protein-folding challenge. methods took center stage at CASP14, with DeepMind’s Alphafold2 achieving remarkable accuracy. Baek et al . explored network architectures based DeepMind framework. They used three-track to process sequence, distance, coordinate information simultaneously achieved accuracies approaching those DeepMind. The method, RoseTTA fold, can solve challenging x-ray crystallography cryo–electron microscopy modeling problems generate accurate models protein-protein complexes. —VV

Language: Английский

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Improved prediction of protein-protein interactions using AlphaFold2

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: March 10, 2022

Abstract Predicting the structure of interacting protein chains is a fundamental step towards understanding function. Unfortunately, no computational method can produce accurate structures complexes. AlphaFold2, has shown unprecedented levels accuracy in modelling single chain structures. Here, we apply AlphaFold2 for prediction heterodimeric We find that protocol together with optimised multiple sequence alignments, generate models acceptable quality (DockQ ≥ 0.23) 63% dimers. From predicted interfaces create simple function to predict DockQ score which distinguishes from incorrect as well non-interacting proteins state-of-art accuracy. that, using scores, identify 51% all pairs at 1% FPR.

Language: Английский

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Computed structures of core eukaryotic protein complexes

Science, Journal Year: 2021, Volume and Issue: 374(6573)

Published: Nov. 11, 2021

Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there likely not yet identified. We take advantage advances proteome-wide amino acid coevolution analysis deep-learning–based structure modeling to systematically identify build accurate models core within

Language: Английский

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Accurate prediction of protein structures and interactions using a three-track neural network

Yearbook of pediatric endocrinology, Journal Year: 2022, Volume and Issue: unknown

Published: Sept. 12, 2022

Brief summary: This study reveals a Deep Learning method, 'RoseTTA fold', based on DeepMind's Alphafold2 framework, to predict 3-dimensional protein structures from 1-dimensional sequence information and generate models of protein–protein complexes with high accuracy.

Language: Английский

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cGAS-like receptors sense RNA and control 3′2′-cGAMP signalling in Drosophila

Nature, Journal Year: 2021, Volume and Issue: 597(7874), P. 109 - 113

Published: July 14, 2021

Abstract Cyclic GMP–AMP synthase (cGAS) is a cytosolic DNA sensor that produces the second messenger cG[2′–5′]pA[3′–5′]p (2′3′-cGAMP) and controls activation of innate immunity in mammalian cells 1–5 . Animal genomes typically encode multiple proteins with predicted homology to cGAS 6–10 , but function these uncharacterized enzymes unknown. Here we show cGAS-like receptors (cGLRs) are immune sensors capable recognizing divergent molecular patterns catalysing synthesis distinct nucleotide signals. Crystal structures human insect cGLRs reveal nucleotidyltransferase signalling core shared diversified primary ligand-binding surface modified notable insertions deletions. We demonstrate remodelling enables altered ligand specificity used forward biochemical screen identify cGLR1 as double-stranded RNA model organism Drosophila melanogaster recognition activates synthesize novel product cG[3′–5′]pA[2′–5′]p (3′2′-cGAMP). A crystal structure stimulator interferon genes (dSTING) complex 3′2′-cGAMP explains selective isomer recognition, induces an enhanced antiviral state vivo protects from viral infection. Similar radiation Toll-like pathogen immunity, our results establish diverse family metazoan pattern receptors.

Language: Английский

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Multiple phage resistance systems inhibit infection via SIR2-dependent NAD+ depletion

Nature Microbiology, Journal Year: 2022, Volume and Issue: 7(11), P. 1849 - 1856

Published: Oct. 3, 2022

Language: Английский

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Recent advances in green synthesized nanoparticles: from production to application

Materials Today Sustainability, Journal Year: 2023, Volume and Issue: 24, P. 100500 - 100500

Published: Aug. 19, 2023

With the increasing concern over environmental impact of conventional chemical methods, environmentally friendly processes, commonly known as green chemistry, for synthesis nanoparticles have gained growing interest in field nanobiotechnology. This review focuses on metallic (NPs) based chemistry and their applications new drug delivery system anticancer antimicrobial treatment. The encompasses a survey production characterization synthetic NPs, along with an examination physico-chemical properties biological activities. Notably, this goes beyond previous reports by providing extensive analysis recent studies that utilize silico design computational modeling to gain deeper insights into interactions between these NPs targets. simulation helps not only comprehending mechanism but also predicting any potential bioactivities. By offering broad perspective novel ideas, attempts shed light future development smart medicine modern generation cancer therapy other disease treatments.

Language: Английский

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Uncovering new families and folds in the natural protein universe

Nature, Journal Year: 2023, Volume and Issue: 622(7983), P. 646 - 653

Published: Sept. 13, 2023

We are now entering a new era in protein sequence and structure annotation, with hundreds of millions predicted structures made available through the AlphaFold database1. These models cover nearly all proteins that known, including those challenging to annotate for function or putative biological role using standard homology-based approaches. In this study, we examine extent which database has structurally illuminated 'dark matter' natural universe at high accuracy. further describe diversity these as an annotated interactive similarity network, accessible https://uniprot3d.org/atlas/AFDB90v4 . By searching novelties from sequence, semantic perspectives, uncovered β-flower fold, added several families Pfam database2 experimentally demonstrated one belongs superfamily translation-targeting toxin-antitoxin systems, TumE-TumA. This work underscores value large-scale efforts identifying, annotating prioritizing families. leveraging recent deep learning revolution bioinformatics, can shed light into uncharted areas unprecedented scale, paving way innovations life sciences biotechnology.

Language: Английский

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A novel superfamily of bridge-like lipid transfer proteins

Trends in Cell Biology, Journal Year: 2022, Volume and Issue: 32(11), P. 962 - 974

Published: April 28, 2022

Language: Английский

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Mirusviruses link herpesviruses to giant viruses

Nature, Journal Year: 2023, Volume and Issue: 616(7958), P. 783 - 789

Published: April 19, 2023

DNA viruses have a major influence on the ecology and evolution of cellular organisms

Language: Английский

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