Cover Image

SimpleFold: Folding Proteins is Simpler than You Think

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Yuyang, Lu, Jiarui, Jaitly, Navdeep, Susskind, Josh, Bautista, Miguel Angel
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Quantitative Methods
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Protein Fold Classification at Scale: Benchmarking and Pretraining
by: Chen, Dexiong, et al.
Published: (2026)

PRISM: Enhancing Protein Inverse Folding through Fine-Grained Retrieval on Structure-Sequence Multimodal Representations
by: Mahbub, Sazan, et al.
Published: (2025)

Lightweight MSA Design Advances Protein Folding From Evolutionary Embeddings
by: Cao, Hanqun, et al.
Published: (2025)

CodonMPNN for Organism Specific and Codon Optimal Inverse Folding
by: Stark, Hannes, et al.
Published: (2024)

Differentiable Folding for Nearest Neighbor Model Optimization
by: Krueger, Ryan K., et al.
Published: (2025)

UniIF: Unified Molecule Inverse Folding
by: Gao, Zhangyang, et al.
Published: (2024)

Deep Learning Framework for RNA Inverse Folding with Geometric Structure Potentials
by: Yao, Annabelle
Published: (2025)

Beyond Current Boundaries: Integrating Deep Learning and AlphaFold for Enhanced Protein Structure Prediction from Low-Resolution Cryo-EM Maps
by: Xin, et al.
Published: (2024)

FoldSAE: Learning to Steer Protein Folding Through Sparse Representations
by: Zarzecki, Wojciech, et al.
Published: (2025)

Protein Folding with Neural Ordinary Differential Equations
by: Sanford, Arielle, et al.
Published: (2025)

Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling
by: Lu, Jiarui, et al.
Published: (2023)

Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations
by: Lu, Jiarui, et al.
Published: (2024)

ScaleFold: Reducing AlphaFold Initial Training Time to 10 Hours
by: Zhu, Feiwen, et al.
Published: (2024)

Fold-CP: A Context Parallelism Framework for Biomolecular Modeling
by: Lin, Dejun, et al.
Published: (2026)

LaGDif: Latent Graph Diffusion Model for Efficient Protein Inverse Folding with Self-Ensemble
by: Wu, Taoyu, et al.
Published: (2024)

Hallucinations in AlphaFold3 for Intrinsically Disordered Proteins with disorder in Biological Process Residues
by: Gopalan, Shreya, et al.
Published: (2025)

ProteinZero: Self-Improving Protein Generation via Online Reinforcement Learning
by: Wang, Ziwen, et al.
Published: (2025)

Characterizing the Conformational States of G Protein Coupled Receptors Generated with AlphaFold
by: Chib, Garima, et al.
Published: (2025)

Protein-Mamba: Biological Mamba Models for Protein Function Prediction
by: Xu, Bohao, et al.
Published: (2024)

A Text-guided Protein Design Framework
by: Liu, Shengchao, et al.
Published: (2023)

SBSM-Pro: Support Bio-sequence Machine for Proteins
by: Wang, Yizheng, et al.
Published: (2023)

ProteinRPN: Towards Accurate Protein Function Prediction with Graph-Based Region Proposals
by: Mitra, Shania, et al.
Published: (2024)

RadDiff: Retrieval-Augmented Denoising Diffusion for Protein Inverse Folding
by: Han, Jin, et al.
Published: (2025)

Learning the Language of Protein Structure
by: Gaujac, Benoit, et al.
Published: (2024)

Molecular Embedding-Based Algorithm Selection in Protein-Ligand Docking
by: Wang, Jiabao Brad, et al.
Published: (2025)

DPLM-2: A Multimodal Diffusion Protein Language Model
by: Wang, Xinyou, et al.
Published: (2024)

Is Sequence Information All You Need for Bayesian Optimization of Antibodies?
by: Ober, Sebastian W., et al.
Published: (2025)

Triangle Multiplication Is All You Need For Biomolecular Structure Representations
by: Ouyang-Zhang, Jeffrey, et al.
Published: (2025)

Can Molecular Foundation Models Know What They Don't Know? A Simple Remedy with Preference Optimization
by: He, Langzhou, et al.
Published: (2025)

PoseX: AI Defeats Physics Approaches on Protein-Ligand Cross Docking
by: Jiang, Yize, et al.
Published: (2025)

PGraphDTA: Improving Drug Target Interaction Prediction using Protein Language Models and Contact Maps
by: Bal, Rakesh, et al.
Published: (2023)

Molecular Topological Profile (MOLTOP) -- Simple and Strong Baseline for Molecular Graph Classification
by: Adamczyk, Jakub, et al.
Published: (2024)

Driving Accurate Allergen Prediction with Protein Language Models and Generalization-Focused Evaluation
by: Wong, Brian Shing-Hei, et al.
Published: (2025)

Low-N Protein Activity Optimization with FolDE
by: Roberts, Jacob B., et al.
Published: (2025)

Protein Circuit Tracing via Cross-layer Transcoders
by: Tsui, Darin, et al.
Published: (2026)

Better Protein Function Prediction by Modeling Survivorship Bias
by: Chao, Zhongmou, et al.
Published: (2026)

Sparse Autoencoders for Low-$N$ Protein Function Prediction and Design
by: Tsui, Darin, et al.
Published: (2025)

A Diffusion Model to Shrink Proteins While Maintaining Their Function
by: Baron, Ethan, et al.
Published: (2025)

Data-Dependent Smoothing for Protein Discovery with Walk-Jump Sampling
by: Anumasa, Srinivas, et al.
Published: (2025)

Prot2Token: A Unified Framework for Protein Modeling via Next-Token Prediction
by: Pourmirzaei, Mahdi, et al.
Published: (2025)