ArticlePLoS computational biology2022
SPEACH_AF: Sampling protein ensembles and conformational heterogeneity with Alphafold2.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 130 papers.
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Who cites it
130 citing papers in PubMed, 241 citations in OpenAlex.
- Spectral tuning and signaling of diverse and far red-sensitive rhodopsins in mantis shrimp eyes.Science advances · 2026Article
- A light-triggered Time-Resolved X-ray Solution Scattering (TR-XSS) workflow with application to protein conformational dynamics.FEBS open bio · 2026Article
- The Advantages of AI for Computational Protein Studies and Looking Ahead at the Next Challenges: Single Structures Are Not Enough.Journal of molecular biology · 2026Review
- Enhanced Sampling of Protein Conformations in AlphaFold3 with Repulsive Bias in the Diffusion Generative Model.JACS Au · 2026Article
- Biasing Conformational Sampling in AlphaFold 3 and Boltz-2 via Pair Representation Scaling.Journal of chemical information and modeling · 2026Article
- Explainable AI reveals the allosteric blind spot in protein-ligand binding predictions.Cell reports. Physical science · 2026Article
- PETIMOT: a novel framework for inferring protein motions from sparse data using SE(3)-equivariant graph neural networks.Acta crystallographica. Section D, Structural biology · 2026Article
- Benchmarking AI Protein Structure Predictors Reveals a Persistent Bias in Multi-State Proteins.bioRxiv : the preprint server for biology · 2026Article
- AI-Physics-Experiment Trinity for Integrated Protein Dynamics Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- DeepPath: overcoming data scarcity for protein transition pathway prediction using physics-based deep learning.Chemical science · 2026Article
- Exploring the conformational landscape of adenylate kinase and beyond with protein folding models.Scientific reports · 2026Article
- AI-based methods for simulating, sampling, and predicting protein ensembles.Current opinion in structural biology · 2026Review
- Advances and challenges in multiscale biomolecular simulations: artificial intelligence-driven paradigm shift.Quantitative biology (Beijing, China) · 2026Article
- Distance-Restraint-Guided Diffusion Models for Sampling Protein Conformational Changes and Ligand Dissociation Pathways.Journal of chemical theory and computation · 2026Article
- Improving AlphaFold2 Performance in Virtual Screens Targeting GPCRs by Enhancing Binding-Site Conformational Sampling.Journal of chemical information and modeling · 2026Article
- ConforFold recovers alternative protein conformations beyond MSA subsampling.Protein science : a publication of the Protein Society · 2026Article
- Conformational Dynamics of NaJournal of chemical information and modeling · 2026Article
- Hidden structural states of proteins revealed by conformer selection.Nature communications · 2026Article
- Article
- AlphaFold as a prior: experimental structure determination conditioned on a pretrained neural network.Nature methods · 2026Article
70 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The unprecedented performance of Deepmind's Alphafold2 in predicting protein structure in CASP XIV and the creation of a database of structures for multiple proteomes and protein sequence repositories is reshaping structural biology. However, because this database returns a single structure, it brought into question Alphafold's ability to capture the intrinsic conformational flexibility of proteins. Here we present a general approach to drive Alphafold2 to model alternate protein conformations through simple manipulation of the multiple sequence alignment via in silico mutagenesis. The approach is grounded in the hypothesis that the multiple sequence alignment must also encode for protein structural heterogeneity, thus its rational manipulation will enable Alphafold2 to sample alternate conformations. A systematic modeling pipeline is benchmarked against canonical examples of protein conformational flexibility and applied to interrogate the conformational landscape of membrane proteins. This work broadens the applicability of Alphafold2 by generating multiple protein conformations to be tested biologically, biochemically, biophysically, and for use in structure-based drug design.
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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.