Papers Protein Structure Prediction
“Protein Structure Prediction” 태그가 달린 논문 210편 · 필터 해제
Does Learning Protein Folding Generalize to Broader Reasoning?
Large language models rely heavily on human text, which often conveys surface answers rather than the spatial and structural logic behind them. Protein folding is a natural testbed, because one solved structure yields th…
Protein Structure PredictionProtein Structure Prediction: From Evolutionary Constraints to Generative Modeling
Accurate protein structure prediction is fundamental to structural biology because protein structure underlies molecular function and provides a basis for mechanistic interpretation. Recent advances in deep learning have…
Protein Structure PredictionMultiple Sequence AlignmentProtein DesignAtom-level Protein Representation Learning Improves Protein Structure Prediction
Recent advances in generative modeling show that pretrained representations can improve generation as conditioning features or alignment targets. Motivated by this, we study protein representations for predicting structu…
Protein Structure PredictionRepresentation LearningDCFold: Efficient Protein Structure Generation with Single Forward Pass
AlphaFold3 introduces a diffusion-based architecture that elevates protein structure prediction to all-atom resolution with improved accuracy. This state-of-the-art performance has established AlphaFold3 as a foundation …
Protein Structure PredictionProtein DesignThe Biosecurity Blind Spot: Systematic Dual-use Detection in Open Science Infrastructure
AI is transforming life sciences research at unprecedented speed, accelerating discovery across protein structure prediction, genome modeling, and drug development (Jumper et al., 2021; Mak et al., 2024). Yet this rapid …
Protein Structure PredictionSampling at intermediate temperatures is optimal for training large language models in protein structure prediction
We investigate the parameter space of transformer models trained on protein sequence data using a statistical mechanics framework, sampling the loss landscape at varying temperatures by Langevin dynamics to characterize …
Protein Structure PredictionProbing the Geometry of Diffusion Models with the String Method
Understanding the geometry of learned distributions is fundamental to improving and interpreting diffusion models, yet systematic tools for exploring their landscape remain limited. Standard latent-space interpolations f…
Protein Structure PredictionTwo Stages of Folding: Convergent Mechanisms in AI Protein Folding Trunks
How do protein structure prediction models fold proteins? We investigate this question through causal interventions on the folding trunks of ESMFold, OpenFold, and Boltz-1. Across all three models, we find a shared two-s…
Protein Structure PredictionContext-aware Graph Causality Inference for Few-Shot Molecular Property Prediction
Molecular property prediction is becoming one of the major applications of graph learning in Web-based services, e.g., online protein structure prediction and drug discovery. A key challenge arises in few-shot scenarios,…
Molecular Property PredictionProtein Structure PredictionCausal InferenceGraph LearningHD-Prot: A Protein Language Model for Joint Sequence-Structure Modeling with Continuous Structure Tokens
Proteins inherently possess a consistent sequence-structure duality. The abundance of protein sequence data, which can be readily represented as discrete tokens, has driven fruitful developments in protein language model…
Protein Structure PredictionProtein Language ModelClassifying Metamorphic versus Single-Fold Proteins with Statistical Learning and AlphaFold2
The remarkable success of AlphaFold2 in providing accurate atomic-level prediction of protein structures from their amino acid sequence has transformed approaches to the protein folding problem. However, its core paradig…
Protein Structure PredictionMultiple Sequence AlignmentQuantifying the Role of OpenFold Components in Protein Structure Prediction
Models such as AlphaFold2 and OpenFold have transformed protein structure prediction, yet their inner workings remain poorly understood. We present a methodology to systematically evaluate the contribution of individual …
Protein Structure PredictionFractional Diffusion Bridge Models
We present Fractional Diffusion Bridge Models (FDBM), a novel generative diffusion bridge framework driven by an approximation of the rich and non-Markovian fractional Brownian motion (fBM). Real stochastic processes exh…
Protein Structure PredictionTriangle Multiplication Is All You Need For Biomolecular Structure Representations
AlphaFold has transformed protein structure prediction, but emerging applications such as virtual ligand screening, proteome-wide folding, and de novo binder design demand predictions at a massive scale, where runtime an…
Protein Structure PredictionComputational EfficiencyProtein Folding with Neural Ordinary Differential Equations
Recent advances in protein structure prediction, such as AlphaFold, have demonstrated the power of deep neural architectures like the Evoformer for capturing complex spatial and evolutionary constraints on protein confor…
Protein Structure PredictionLet Physics Guide Your Protein Flows: Topology-aware Unfolding and Generation
Protein structure prediction and folding are fundamental to understanding biology, with recent deep learning advances reshaping the field. Diffusion-based generative models have revolutionized protein design, enabling th…
Protein Structure PredictionProtein DesignGeneral Synthetic-Powered Inference
The rapid proliferation of high-quality synthetic data -- generated by advanced AI models or collected as auxiliary data from related tasks -- presents both opportunities and challenges for statistical inference. This pa…
Protein Structure PredictionProFusion: 3D Reconstruction of Protein Complex Structures from Multi-view AFM Images
AI-based in silico methods have improved protein structure prediction but often struggle with large protein complexes (PCs) involving multiple interacting proteins due to missing 3D spatial cues. Experimental techniques …
Protein Structure Prediction3D ReconstructionFeature-Space Planes Searcher: A Universal Domain Adaptation Framework for Interpretability and Computational Efficiency
Domain shift, characterized by degraded model performance during transition from labeled source domains to unlabeled target domains, poses a persistent challenge for deploying deep learning systems. Current unsupervised …
Unsupervised Domain AdaptationProtein Structure PredictionUniversal Domain AdaptationComputational EfficiencyFrom Prediction to Simulation: AlphaFold 3 as a Differentiable Framework for Structural Biology
AlphaFold 3 represents a transformative advancement in computational biology, enhancing protein structure prediction through novel multi-scale transformer architectures, biologically informed cross-attention mechanisms, …
Protein Structure Prediction