Accurate structure prediction of biomolecular interactions with AlphaFold 3

Nature, Journal Year: 2024, Volume and Issue: 630(8016), P. 493 - 500

Published: May 8, 2024

Abstract The introduction of AlphaFold 2 1 has spurred a revolution in modelling the structure proteins and their interactions, enabling huge range applications protein design 2–6 . Here we describe our 3 model with substantially updated diffusion-based architecture that is capable predicting joint complexes including proteins, nucleic acids, small molecules, ions modified residues. new demonstrates improved accuracy over many previous specialized tools: far greater for protein–ligand interactions compared state-of-the-art docking tools, much higher protein–nucleic acid nucleic-acid-specific predictors antibody–antigen prediction AlphaFold-Multimer v.2.3 7,8 Together, these results show high-accuracy across biomolecular space possible within single unified deep-learning framework.

Language: Английский

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UCSF ChimeraX: Tools for structure building and analysis

Protein Science, Journal Year: 2023, Volume and Issue: 32(11)

Published: Sept. 29, 2023

Advances in computational tools for atomic model building are leading to accurate models of large molecular assemblies seen electron microscopy, often at challenging resolutions 3-4 Å. We describe new methods the UCSF ChimeraX modeling package that take advantage machine-learning structure predictions, provide likelihood-based fitting maps, and compute per-residue scores identify errors. Additional model-building assist analysis mutations, post-translational modifications, interactions with ligands. present latest capabilities, including several community-developed extensions. is available free charge noncommercial use https://www.rbvi.ucsf.edu/chimerax.

Language: Английский

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Fast and accurate protein structure search with Foldseek

Nature Biotechnology, Journal Year: 2023, Volume and Issue: 42(2), P. 243 - 246

Published: May 8, 2023

Abstract As structure prediction methods are generating millions of publicly available protein structures, searching these databases is becoming a bottleneck. Foldseek aligns the query against database by describing tertiary amino acid interactions within proteins as sequences over structural alphabet. decreases computation times four to five orders magnitude with 86%, 88% and 133% sensitivities Dali, TM-align CE, respectively.

Language: Английский

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Accurate proteome-wide missense variant effect prediction with AlphaMissense

Science, Journal Year: 2023, Volume and Issue: 381(6664)

Published: Sept. 19, 2023

The vast majority of missense variants observed in the human genome are unknown clinical significance. We present AlphaMissense, an adaptation AlphaFold fine-tuned on and primate variant population frequency databases to predict pathogenicity. By combining structural context evolutionary conservation, our model achieves state-of-the-art results across a wide range genetic experimental benchmarks, all without explicitly training such data. average pathogenicity score genes is also predictive for their cell essentiality, capable identifying short essential that existing statistical approaches underpowered detect. As resource community, we provide database predictions possible single amino acid substitutions classify 89% as either likely benign or pathogenic.

Language: Английский

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De novo design of protein structure and function with RFdiffusion

Nature, Journal Year: 2023, Volume and Issue: 620(7976), P. 1089 - 1100

Published: July 11, 2023

Abstract There has been considerable recent progress in designing new proteins using deep-learning methods 1–9 . Despite this progress, a general framework for protein design that enables solution of wide range challenges, including de novo binder and higher-order symmetric architectures, yet to be described. Diffusion models 10,11 have had success image language generative modelling but limited when applied modelling, probably due the complexity backbone geometry sequence–structure relationships. Here we show by fine-tuning RoseTTAFold structure prediction network on denoising tasks, obtain model backbones achieves outstanding performance unconditional topology-constrained monomer design, oligomer enzyme active site scaffolding motif therapeutic metal-binding design. We demonstrate power generality method, called diffusion (RFdiffusion), experimentally characterizing structures functions hundreds designed assemblies, binders. The accuracy RFdiffusion is confirmed cryogenic electron microscopy complex with influenza haemagglutinin nearly identical model. In manner analogous networks produce images from user-specified inputs, diverse functional simple molecular specifications.

Language: Английский

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AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences

Nucleic Acids Research, Journal Year: 2023, Volume and Issue: 52(D1), P. D368 - D375

Published: Nov. 2, 2023

The AlphaFold Database Protein Structure (AlphaFold DB, https://alphafold.ebi.ac.uk) has significantly impacted structural biology by amassing over 214 million predicted protein structures, expanding from the initial 300k structures released in 2021. Enabled groundbreaking AlphaFold2 artificial intelligence (AI) system, predictions archived DB have been integrated into primary data resources such as PDB, UniProt, Ensembl, InterPro and MobiDB. Our manuscript details subsequent enhancements archiving, covering successive releases encompassing model organisms, global health proteomes, Swiss-Prot integration, a host of curated datasets. We detail access mechanisms direct file via FTP to advanced queries using Google Cloud Public Datasets programmatic endpoints database. also discuss improvements services added since its release, including Predicted Aligned Error viewer, customisation options for 3D search engine DB.

Language: Английский

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Generalized biomolecular modeling and design with RoseTTAFold All-Atom

Science, Journal Year: 2024, Volume and Issue: 384(6693)

Published: March 7, 2024

Deep-learning methods have revolutionized protein structure prediction and design but are presently limited to protein-only systems. We describe RoseTTAFold All-Atom (RFAA), which combines a residue-based representation of amino acids DNA bases with an atomic all other groups model assemblies that contain proteins, nucleic acids, small molecules, metals, covalent modifications, given their sequences chemical structures. By fine-tuning on denoising tasks, we developed RFdiffusion (RFdiffusionAA), builds structures around molecules. Starting from random distributions acid residues surrounding target designed experimentally validated, through crystallography binding measurements, proteins bind the cardiac disease therapeutic digoxigenin, enzymatic cofactor heme, light-harvesting molecule bilin.

Language: Английский

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Autonomous chemical research with large language models

Nature, Journal Year: 2023, Volume and Issue: 624(7992), P. 570 - 578

Published: Dec. 20, 2023

Transformer-based large language models are making significant strides in various fields, such as natural processing

Language: Английский

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AlphaFold2 and its applications in the fields of biology and medicine

Signal Transduction and Targeted Therapy, Journal Year: 2023, Volume and Issue: 8(1)

Published: March 14, 2023

Abstract AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind that can predict three-dimensional (3D) structures of proteins from amino acid sequences with atomic-level accuracy. Protein structure prediction one the most challenging problems in computational biology and chemistry, has puzzled scientists for 50 years. The advent AF2 presents unprecedented progress protein attracted much attention. Subsequent release more than 200 million predicted further aroused great enthusiasm science community, especially fields medicine. thought to have a significant impact on structural research areas need information, such as drug discovery, design, function, et al. Though time not long since was developed, there are already quite few application studies medicine, many them having preliminarily proved potential AF2. To better understand promote its applications, we will this article summarize principle architecture well recipe success, particularly focus reviewing applications Limitations current also be discussed.

Language: Английский

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Automated model building and protein identification in cryo-EM maps

Nature, Journal Year: 2024, Volume and Issue: 628(8007), P. 450 - 457

Published: Feb. 26, 2024

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs

Language: Английский

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