Unavailability of experimental 3D structural data on protein folding dynamics and necessity for a new generation of structure prediction methods in this context
Fuente:
arXiv
Saved in:
| Main Authors: | Wells, Aydin, Newaz, Khalique, Morones, Jennifer, Cheng, Jianlin, Milenković, Tijana |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Proteins with alternative folds reveal blind spots in AlphaFold-based protein structure prediction
by: Chakravarty, Devlina, et al.
Published: (2024)
by: Chakravarty, Devlina, et al.
Published: (2024)
Predicting protein folding dynamics using sequence information
by: Galpern, Ezequiel A., et al.
Published: (2025)
by: Galpern, Ezequiel A., et al.
Published: (2025)
The effect of stereochemical constraints on the structural properties of folded proteins
by: Logan, Jack A., et al.
Published: (2025)
by: Logan, Jack A., et al.
Published: (2025)
PSBench: a large-scale benchmark for estimating the accuracy of protein complex structural models
by: Neupane, Pawan, et al.
Published: (2025)
by: Neupane, Pawan, et al.
Published: (2025)
Traditional machine learning vs. deep learning from dynamic graph representations of proteins' 3D folds in the task of protein structure classification
by: Wells, Aydin, et al.
Published: (2026)
by: Wells, Aydin, et al.
Published: (2026)
Towards deep learning sequence-structure co-generation for protein design
by: Wang, Chentong, et al.
Published: (2024)
by: Wang, Chentong, et al.
Published: (2024)
From sequence to protein structure and conformational dynamics with AI/ML
by: Ille, Alexander M., et al.
Published: (2025)
by: Ille, Alexander M., et al.
Published: (2025)
Evaluating representation learning on the protein structure universe
by: Jamasb, Arian R., et al.
Published: (2024)
by: Jamasb, Arian R., et al.
Published: (2024)
Multiscale guidance of protein structure prediction with heterogeneous cryo-EM data
by: Raghu, Rishwanth, et al.
Published: (2025)
by: Raghu, Rishwanth, et al.
Published: (2025)
AlphaFold2 for protein structure prediction: Best practices and critical analyses
by: Radjasandirane, Ragousandirane, et al.
Published: (2024)
by: Radjasandirane, Ragousandirane, et al.
Published: (2024)
Integrating experimental data with molecular simulations to investigate RNA structural dynamics
by: Bernetti, Mattia, et al.
Published: (2022)
by: Bernetti, Mattia, et al.
Published: (2022)
Frontiers in integrative structural biology: modeling disordered proteins and utilizing in situ data
by: Majila, Kartik, et al.
Published: (2024)
by: Majila, Kartik, et al.
Published: (2024)
Inferring protein folding mechanisms from natural sequence diversity
by: Galpern, Ezequiel A., et al.
Published: (2024)
by: Galpern, Ezequiel A., et al.
Published: (2024)
Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications
by: Yang, Shu, et al.
Published: (2025)
by: Yang, Shu, et al.
Published: (2025)
FoldToken2: Learning compact, invariant and generative protein structure language
by: Gao, Zhangyang, et al.
Published: (2024)
by: Gao, Zhangyang, et al.
Published: (2024)
Yeti: A compact protein structure tokenizer for reconstruction and multi-modal generation
by: Giri, Nabin, et al.
Published: (2026)
by: Giri, Nabin, et al.
Published: (2026)
The standard coil or globule phases cannot describe the denatured state of structured proteins and intrinsically disordered proteins
by: Righini, F., et al.
Published: (2025)
by: Righini, F., et al.
Published: (2025)
The curious case of A31P, a topology-switching mutant of the Repressor of Primer protein : A molecular dynamics study of its folding and misfolding
by: Vouzina, Olympia-Dialekti, et al.
Published: (2024)
by: Vouzina, Olympia-Dialekti, et al.
Published: (2024)
Co-folding model guided by structural proteomics
by: Shtrikman, Alon, et al.
Published: (2026)
by: Shtrikman, Alon, et al.
Published: (2026)
Exploring zero-shot structure-based protein fitness prediction
by: Sharma, Arnav, et al.
Published: (2025)
by: Sharma, Arnav, et al.
Published: (2025)
AntiFold: Improved antibody structure-based design using inverse folding
by: Høie, Magnus Haraldson, et al.
Published: (2024)
by: Høie, Magnus Haraldson, et al.
Published: (2024)
ApexGen: Simultaneous design of peptide binder sequence and structure for target proteins
by: Xia, Xiaoqiong, et al.
Published: (2025)
by: Xia, Xiaoqiong, et al.
Published: (2025)
Towards better structural models from cryo-electron microscopy data with physics-based methods
by: Selcuk, Hande Boyaci, et al.
Published: (2025)
by: Selcuk, Hande Boyaci, et al.
Published: (2025)
AutoLoop: a novel autoregressive deep learning method for protein loop prediction with high accuracy
by: Wang, Tianyue, et al.
Published: (2025)
by: Wang, Tianyue, et al.
Published: (2025)
Predicting mutational effects on protein binding from folding energy
by: Deng, Arthur, et al.
Published: (2025)
by: Deng, Arthur, et al.
Published: (2025)
Resolving structural dynamics in situ through cryogenic electron tomography
by: Carrion, Jackson, et al.
Published: (2025)
by: Carrion, Jackson, et al.
Published: (2025)
Towards protein folding pathways by reconstructing protein residue networks with a policy-driven model
by: Khor, Susan
Published: (2026)
by: Khor, Susan
Published: (2026)
State-aware protein-ligand complex prediction using AlphaFold3 with purified sequences
by: Xing, Enming, et al.
Published: (2025)
by: Xing, Enming, et al.
Published: (2025)
BeeRNA: tertiary structure-based RNA inverse folding using Artificial Bee Colony
by: Mlaweh, Mehyar, et al.
Published: (2025)
by: Mlaweh, Mehyar, et al.
Published: (2025)
Solvation enhances folding cooperativity and the topology dependence of folding rates in a lattice protein model
by: Nguyen, Nhung T. T., et al.
Published: (2025)
by: Nguyen, Nhung T. T., et al.
Published: (2025)
Zero-shot protein stability prediction by inverse folding models: a free energy interpretation
by: Frellsen, Jes, et al.
Published: (2025)
by: Frellsen, Jes, et al.
Published: (2025)
All-atom inverse protein folding through discrete flow matching
by: Yi, Kai, et al.
Published: (2025)
by: Yi, Kai, et al.
Published: (2025)
Mask prior-guided denoising diffusion improves inverse protein folding
by: Bai, Peizhen, et al.
Published: (2024)
by: Bai, Peizhen, et al.
Published: (2024)
Aptamer-protein interaction prediction model based on transformer
by: Yan, Zhichao, et al.
Published: (2025)
by: Yan, Zhichao, et al.
Published: (2025)
FLOWR.root: A flow matching based foundation model for joint multi-purpose structure-aware 3D ligand generation and affinity prediction
by: Cremer, Julian, et al.
Published: (2025)
by: Cremer, Julian, et al.
Published: (2025)
StaPep: an open-source tool for the structure prediction and feature extraction of hydrocarbon-stapled peptides
by: Wang, Zhe, et al.
Published: (2024)
by: Wang, Zhe, et al.
Published: (2024)
TopoQA: a topological deep learning-based approach for protein complex structure interface quality assessment
by: Han, Bingqing, et al.
Published: (2024)
by: Han, Bingqing, et al.
Published: (2024)
GenShin:geometry-enhanced structural graph embodies binding pose can better predicting compound-protein interaction affinity
by: Zhu, Pingfei, et al.
Published: (2025)
by: Zhu, Pingfei, et al.
Published: (2025)
Paraplume: A fast and accurate paratope prediction method provides insights into repertoire-scale binding dynamics
by: Athènes, Gabriel, et al.
Published: (2025)
by: Athènes, Gabriel, et al.
Published: (2025)
Fold-switching proteins push the boundaries of conformational ensemble prediction
by: Lee, Myeongsang, et al.
Published: (2026)
by: Lee, Myeongsang, et al.
Published: (2026)
Similar Items
-
Proteins with alternative folds reveal blind spots in AlphaFold-based protein structure prediction
by: Chakravarty, Devlina, et al.
Published: (2024) -
Predicting protein folding dynamics using sequence information
by: Galpern, Ezequiel A., et al.
Published: (2025) -
The effect of stereochemical constraints on the structural properties of folded proteins
by: Logan, Jack A., et al.
Published: (2025) -
PSBench: a large-scale benchmark for estimating the accuracy of protein complex structural models
by: Neupane, Pawan, et al.
Published: (2025) -
Traditional machine learning vs. deep learning from dynamic graph representations of proteins' 3D folds in the task of protein structure classification
by: Wells, Aydin, et al.
Published: (2026)