Cover Image

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Min, Yaosen, Wei, Ye, Wang, Peizhuo, Wang, Xiaoting, Li, Han, Wu, Nian, Bauer, Stefan, Zheng, Shuxin, Shi, Yu, Wang, Yingheng, Wu, Ji, Zhao, Dan, Zeng, Jianyang
Format:	Preprint
Published:	2022
Subjects:	Biomolecules Machine Learning Chemical Physics Quantitative Methods
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph‐Based Deep Learning
by: Yaosen Min, et al.
Published: (2024)

Designing the Haystack: Programmable Chemical Space for Generative Molecular Discovery
by: Zhu, Yuchen, et al.
Published: (2026)

ProtSCAPE: Mapping the landscape of protein conformations in molecular dynamics
by: Viswanath, Siddharth, et al.
Published: (2024)

QSAR-Guided Generative Framework for the Discovery of Synthetically Viable Odorants
by: Pearce, Tim C., et al.
Published: (2025)

Marginal Girsanov Reweighting: Stable Variance Reduction for Long-Timescale Dynamics from Biased Simulation
by: Wang, Yan, et al.
Published: (2025)

HelixVS: Deep Learning-Enhanced Structure-Based Platform for Screening and Design
by: Zhang, Shanzhuo, et al.
Published: (2025)

LICO: Large Language Models for In-Context Molecular Optimization
by: Nguyen, Tung, et al.
Published: (2024)

Molecular dynamics simulations with grand-canonical reweighting suggest cooperativity effects in RNA structure probing experiments
by: Calonaci, Nicola, et al.
Published: (2022)

On Machine Learning Approaches for Protein-Ligand Binding Affinity Prediction
by: Schapin, Nikolai, et al.
Published: (2024)

UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection
by: Fan, Jigang, et al.
Published: (2025)

Improving Paratope and Epitope Prediction by Multi-Modal Contrastive Learning and Interaction Informativeness Estimation
by: Wang, Zhiwei, et al.
Published: (2024)

Investigating Knowledge Distillation Through Neural Networks for Protein Binding Affinity Prediction
by: Abbasi, Wajid Arshad, et al.
Published: (2026)

Interpretable Multimodal Learning for Tumor Protein-Metal Binding: Progress, Challenges, and Perspectives
by: Liu, Xiaokun, et al.
Published: (2025)

General Binding Affinity Guidance for Diffusion Models in Structure-Based Drug Design
by: Jian, Yue, et al.
Published: (2024)

AntiFold: Improved antibody structure-based design using inverse folding
by: Høie, Magnus Haraldson, et al.
Published: (2024)

Explainable Machine Learning and Deep Learning Models for Predicting TAS2R-Bitter Molecule Interactions
by: Ferri, Francesco, et al.
Published: (2024)

End-to-End Reaction Field Energy Modeling via Deep Learning based Voxel-to-voxel Transform
by: Wu, Yongxian, et al.
Published: (2024)

VARIANT: Web Server for Decoding and Analyzing Viral Mutations at Genome and Protein Levels
by: Wang, Rui, et al.
Published: (2026)

A Principal Submanifold-based Approach for Clustering and Multiscale RNA Correction
by: Wu, Menghao, et al.
Published: (2025)

LAFA: A Framework for Reproducible Longitudinal Assessment of Protein Function Annotation Models
by: Phan, An, et al.
Published: (2026)

Co-Evolution-Based Metal-Binding Residue Prediction with Graph Neural Networks
by: Rastegari, Sayedmohammadreza, et al.
Published: (2025)

Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation
by: Zhang, Odin, et al.
Published: (2024)

Improving Antibody Design with Force-Guided Sampling in Diffusion Models
by: Kulytė, Paulina, et al.
Published: (2024)

AbBiBench: A Benchmark for Antibody Binding Affinity Maturation and Design
by: Zhao, Xinyan, et al.
Published: (2025)

ToxBench: A Binding Affinity Prediction Benchmark with AB-FEP-Calculated Labels for Human Estrogen Receptor Alpha
by: Liu, Meng, et al.
Published: (2025)

AMPCliff: quantitative definition and benchmarking of activity cliffs in antimicrobial peptides
by: Li, Kewei, et al.
Published: (2024)

Protein folding classes -- High-dimensional geometry of amino acid composition space revisited
by: Mao, Boryeu
Published: (2025)

GoForth: Language Models for RNA Design under Structure, Sequence, and Coding Constraints
by: Lindsey, Michael
Published: (2026)

Benchmarking structure-based three-dimensional molecular generative models using GenBench3D: ligand conformation quality matters
by: Baillif, Benoit, et al.
Published: (2024)

Canonicalization of the E value from BLAST similarity search -- dissimilarity measure and distance function for a metric space of protein sequences
by: Mao, Boryeu
Published: (2025)

Frequency-Space Mechanics: A Sequence and Coordinate-Free Representation for Protein Function Prediction
by: Reilly, Charles B
Published: (2026)

EscalNet: Learn isotropic representation space for biomolecular dynamics based on effective energy
by: Zuo, Guanghong
Published: (2025)

Network Pharmacology Framework Characterizes Polypharmacological Properties of Dietary Flavonoids: Integration of Computational, Experimental, and Epidemiological Evidence
by: Fujisaki, Koyo, et al.
Published: (2026)

Persistent Sheaf Laplacian Analysis of Protein Flexibility
by: Hayes, Nicole, et al.
Published: (2025)

Raman Spectroscopy Reveals Photobiomodulation-Induced α-Helix to β-Sheet Transition in Tubulins: Potential Implications for Alzheimer's and Other Neurodegenerative Diseases
by: Di Gregorio, Elisabetta, et al.
Published: (2023)

mRNA Folding Algorithms for Structure and Codon Optimization
by: Ward, Max, et al.
Published: (2025)

Two for the Price of One: Integrating Large Language Models to Learn Biophysical Interactions
by: Clark, Joseph D., et al.
Published: (2025)

Quantifying the uncertainty of molecular dynamics simulations : Good-Turing statistics revisited
by: Tsampazi, Vasiliki, et al.
Published: (2026)

Predicting Protein-Nucleic Acid Flexibility Using Persistent Sheaf Laplacians
by: Hayes, Nicole, et al.
Published: (2025)

Quantification of protein homodimer affinity using native mass spectrometry
by: Schulte, Jonathan, et al.
Published: (2025)