ArticleNature communications2024
An end-to-end framework for the prediction of protein structure and fitness from single sequence.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Applications and limitations of AI tools in enzyme design.Protein science : a publication of the Protein Society · 2026Review
- Bridging Algorithms and Biocatalysis: Perspectives on AI-Supported Enzyme Engineering.Molecules (Basel, Switzerland) · 2026Review
- A graph retrieval-augmented generation pipeline for systematic drug target discovery: validation and application to ocular neovascularization.Briefings in bioinformatics · 2026Article
- Decoding variants of uncertain significance in systemic autoinflammatory diseases.Nature reviews. Rheumatology · 2026Review
- Bridging structure and function: artificial intelligence-based modelling of kidney proteins.Nature reviews. Nephrology · 2026Review
- Automatically Defining Protein Words for Diverse Functional Predictions Based on Attention Analysis of a Protein Language Model.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- JanusDDG: a physics-informed neural network for sequence-based protein stability via two-fronts attention.Communications biology · 2026Article
- DeepFold-PLM: accelerating protein structure prediction via efficient homology search using protein language models.Bioinformatics (Oxford, England) · 2025Article
- BridgeNet: a high-efficiency framework integrating sequence and structure for protein and enzyme function prediction.Briefings in bioinformatics · 2025Article
- Genomic Insights Into Convergent Evolution: Adaptation to Rocky Habitats in Rock-Inhabiting Fungi.Molecular biology and evolution · 2025Article
- The Role of AI-Driven De Novo Protein Design in the Exploration of the Protein Functional Universe.Biology · 2025Review
- Biophysics-based protein language models for protein engineering.Nature methods · 2025Article
- Data-efficient protein mutational effect prediction with weak supervision by molecular simulation and protein language models.Briefings in bioinformatics · 2025Article
- Chemosensory Receptors in Vertebrates: Structure and Computational Modeling Insights.International journal of molecular sciences · 2025Review
- AFToolkit: a framework for molecular modeling of proteins with AlphaFold-derived representations.Briefings in bioinformatics · 2025Article
- Predicting protein stability changes upon mutations with dual-view ensemble learning from single sequence.Briefings in bioinformatics · 2025Article
- Biophysics-based protein language models for protein engineering.bioRxiv : the preprint server for biology · 2025Article
- ProCeSa: Contrast-Enhanced Structure-Aware Network for Thermostability Prediction with Protein Language Models.Journal of chemical information and modeling · 2025Article
- Decoding the effects of mutation on protein interactions using machine learning.Biophysics reviews · 2025Review
- GDFold2: A fast and parallelizable protein folding environment with freely defined objective functions.Protein science : a publication of the Protein Society · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Significant research progress has been made in the field of protein structure and fitness prediction. Particularly, single-sequence-based structure prediction methods like ESMFold and OmegaFold achieve a balance between inference speed and prediction accuracy, showing promise for many downstream prediction tasks. Here, we propose SPIRED, a single-sequence-based structure prediction model that exhibits comparable performance to the state-of-the-art methods but with approximately 5-fold acceleration in inference and at least one order of magnitude reduction in training consumption. By integrating SPIRED with downstream neural networks, we compose an end-to-end framework named SPIRED-Fitness for the rapid prediction of both protein structure and fitness from single sequence with satisfactory accuracy. Moreover, SPIRED-Stab, the derivative of SPIRED-Fitness, achieves state-of-the-art performance in predicting the mutational effects on protein stability.
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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.