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Protein Structure Prediction

Image credit: FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours

Papers

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Showing 1–50 of 188 papers

TitleStatusHype
OpenProteinSet: Training data for structural biology at scaleCode4
Galactica: A Large Language Model for ScienceCode4
Highly accurate protein structure prediction with AlphaFoldCode3
Robust deep learning based protein sequence design using ProteinMPNNCode3
ProteinBERT: a universal deep-learning model of protein sequence and functionCode2
Training on test proteins improves fitness, structure, and function predictionCode2
State-specific protein-ligand complex structure prediction with a multi-scale deep generative modelCode2
Protein Large Language Models: A Comprehensive SurveyCode2
MotifBench: A standardized protein design benchmark for motif-scaffolding problemsCode2
PyMOLfold: Interactive Protein and Ligand Structure Prediction in PyMOLCode2
SE(3) diffusion model with application to protein backbone generationCode2
Distribution-Free, Risk-Controlling Prediction SetsCode2
MegaFold: System-Level Optimizations for Accelerating Protein Structure Prediction ModelsCode2
FastFold: Reducing AlphaFold Training Time from 11 Days to 67 HoursCode2
Protein structure generation via folding diffusionCode2
SidechainNet: An All-Atom Protein Structure Dataset for Machine LearningCode1
Towards Interpretable Protein Structure Prediction with Sparse AutoencodersCode1
ProteinNet: a standardized data set for machine learning of protein structureCode1
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence UnderstandingCode1
Accurate Protein Structure Prediction by Embeddings and Deep Learning RepresentationsCode1
PolyFold: an interactive visual simulator for distance-based protein foldingCode1
A Graph Neural Network Approach to Automated Model Building in Cryo-EM MapsCode1
Iterative SE(3)-TransformersCode1
Protein Language Models and Structure Prediction: Connection and ProgressionCode1
MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-TrainingCode1
Highly accurate and efficient deep learning paradigm for full-atom protein loop modeling with KarmaLoopCode1
Generative diffusion model with inverse renormalization group flowsCode1
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic SystemsCode1
RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA DesignCode1
FoldMark: Protecting Protein Generative Models with WatermarkingCode1
ExplainableFold: Understanding AlphaFold Prediction with Explainable AICode1
Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue CloudsCode1
DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain PackingCode1
Deep Learning of Proteins with Local and Global Regions of DisorderCode1
Energy-based models for atomic-resolution protein conformationsCode1
Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment GenerationCode1
AtomSurf : Surface Representation for Learning on Protein StructuresCode1
DeepProtein: Deep Learning Library and Benchmark for Protein Sequence LearningCode1
EigenFold: Generative Protein Structure Prediction with Diffusion ModelsCode1
Generative De Novo Protein Design with Global ContextCode1
Conformation-Aware Structure Prediction of Antigen-Recognizing Immune ProteinsCode1
Geometry-Complete Perceptron Networks for 3D Molecular GraphsCode1
Accurate and efficient protein embedding using multi-teacher distillation learningCode1
CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learningCode1
Pareto Dominance Archive and Coordinated Selection Strategy-Based Many-Objective Optimizer for Protein Structure PredictionCode1
A Survey of Deep Learning Methods in Protein Bioinformatics and its Impact on Protein Design—0
Artificial intelligence-aided protein engineering: from topological data analysis to deep protein language models—0
AIS-INMACA: A Novel Integrated MACA Based Clonal Classifier for Protein Coding and Promoter Region Prediction—0
A Protein Structure Prediction Approach Leveraging Transformer and CNN Integration—0
AI in Pharma for Personalized Sequential Decision-Making: Methods, Applications and Opportunities—0
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All datasetsCASPSeqCASPSimSeqPaenSeqUniProtSeq

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GAL 125MValidation perplexity20.62—Unverified
2GAL 1.3BValidation perplexity17.58—Unverified
3GAL 6.7BValidation perplexity17.29—Unverified
4GAL 30BValidation perplexity17.27—Unverified
5GAL 120BValidation perplexity17.26—Unverified
#ModelMetricClaimedVerifiedStatus
1GAL 125MValidation perplexity19.18—Unverified
2GAL 1.3BValidation perplexity17.04—Unverified
3GAL 6.7BValidation perplexity16.35—Unverified
4GAL 30BValidation perplexity15.42—Unverified
5GAL 120BValidation perplexity12.77—Unverified
#ModelMetricClaimedVerifiedStatus
1GAL 125MValidation perplexity16.35—Unverified
2GAL 1.3BValidation perplexity12.53—Unverified
3GAL 6.7BValidation perplexity7.76—Unverified
4GAL 30BValidation perplexity4.28—Unverified
5GAL 120BValidation perplexity3.14—Unverified
#ModelMetricClaimedVerifiedStatus
1GAL 125MValidation perplexity19.05—Unverified
2GAL 1.3BValidation perplexity15.82—Unverified
3GAL 6.7BValidation perplexity11.58—Unverified
4GAL 30BValidation perplexity8.23—Unverified
5GAL 120BValidation perplexity5.54—Unverified