ArticleNature communications2024
High-throughput prediction of protein conformational distributions with subsampled AlphaFold2.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 108 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
108 citing papers in PubMed.
- Biasing Conformational Sampling in AlphaFold 3 and Boltz-2 via Pair Representation Scaling.Journal of chemical information and modeling · 2026Article
- The partner gene modulates response to asciminib in ABL1-rearranged Acute Lymphoblastic Leukemia.Neoplasia (New York, N.Y.) · 2026Article
- Proteomic investigation of signaling dynamics: from static maps to network rewiring.Bioscience reports · 2026Review
- ESMDynamic: Fast and accurate prediction of protein dynamic contact maps from single sequences.Nature communications · 2026Article
- AFM-Fold: Rapid reconstruction of protein conformations from AFM images.Biophysical journal · 2026Article
- From physics-based intelligence to molecular design: linking mechanistic learning across scales.MedScience · 2026Article
- AlphaFold reveals but sometimes distorts an organizational principle of protein folding.bioRxiv : the preprint server for biology · 2026Article
- Rapid and energy-efficient ultra-large library screening for drug discovery on a SpiNNaker2 neuromorphic chip.Communications chemistry · 2026Article
- Exploring the GM-CSF histidine triad as a modulator of structure, molecular motion, and ligand binding.RSC chemical biology · 2026Article
- Insights into the Mechanism Underlying the Alkane Dehydrogenation Capability ofMicroorganisms · 2026Article
- AI-based methods for simulating, sampling, and predicting protein ensembles.Current opinion in structural biology · 2026Review
- Exploring the conformational landscape of adenylate kinase and beyond with protein folding models.Scientific reports · 2026Article
- Advances and challenges in multiscale biomolecular simulations: artificial intelligence-driven paradigm shift.Quantitative biology (Beijing, China) · 2026Article
- Improving AlphaFold2 Performance in Virtual Screens Targeting GPCRs by Enhancing Binding-Site Conformational Sampling.Journal of chemical information and modeling · 2026Article
- Bayesian-Steered Structure Prediction of Mechanical Biomolecules Using Twisted Diffusion.bioRxiv : the preprint server for biology · 2026Article
- ConforFold recovers alternative protein conformations beyond MSA subsampling.Protein science : a publication of the Protein Society · 2026Article
- Hidden structural states of proteins revealed by conformer selection.Nature communications · 2026Article
- AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network.Nature methods · 2026Article
- Advances in the application of computational toxicology in cosmetic safety assessment.Archives of toxicology · 2026Review
- IDPForge: Deep Learning of Proteins with Global and Local Regions of Disorder.bioRxiv : the preprint server for biology · 2026Article
48 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
This paper presents an innovative approach for predicting the relative populations of protein conformations using AlphaFold 2, an AI-powered method that has revolutionized biology by enabling the accurate prediction of protein structures. While AlphaFold 2 has shown exceptional accuracy and speed, it is designed to predict proteins' ground state conformations and is limited in its ability to predict conformational landscapes. Here, we demonstrate how AlphaFold 2 can directly predict the relative populations of different protein conformations by subsampling multiple sequence alignments. We tested our method against nuclear magnetic resonance experiments on two proteins with drastically different amounts of available sequence data, Abl1 kinase and the granulocyte-macrophage colony-stimulating factor, and predicted changes in their relative state populations with more than 80% accuracy. Our subsampling approach worked best when used to qualitatively predict the effects of mutations or evolution on the conformational landscape and well-populated states of proteins. It thus offers a fast and cost-effective way to predict the relative populations of protein conformations at even single-point mutation resolution, making it a useful tool for pharmacology, analysis of experimental results, and predicting evolution.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.