Imagen de Portada

A hybrid quantum-classical fusion neural network to improve protein-ligand binding affinity predictions for drug discovery

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Domingo, L., Chehimi, M., Banerjee, S., Yuxun, S. He, Konakanchi, S., Ogunfowora, L., Roy, S., Selvaras, S., Djukic, M., Johnson, C.
Formato:	Preprint
Publicado:	2023
Materias:	Quantum Physics Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Enhancing protein‐ligand binding affinity prediction through sequential fusion of graph and convolutional neural networks
por: Yimin Yang, et al.
Publicado: (2024)

Mayer-homology learning prediction of protein-ligand binding affinities
por: Feng, Hongsong, et al.
Publicado: (2024)

Improved prediction of ligand-protein binding affinities by meta-modeling
por: Lee, Ho-Joon, et al.
Publicado: (2023)

Persistent local Laplacian prediction of protein-ligand binding affinities
por: Liu, Jian, et al.
Publicado: (2026)

Accurate and generalizable protein-ligand binding affinity prediction with geometric deep learning
por: Li, Krinos, et al.
Publicado: (2025)

HCAF-DTA: drug-target binding affinity prediction with cross-attention fused hypergraph neural networks
por: Li, Jiannuo, et al.
Publicado: (2025)

CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction
por: Feng, Hongsong, et al.
Publicado: (2025)

Solvation free energy in governing equations for DNA hybridization, protein–ligand binding, and protein folding
por: Caroline Harmon, et al.
Publicado: (2024)

Systematic evaluation of computational tools to predict the effects of mutations on protein-ligand binding affinity in the absence of experimental structures
por: Pan, Qisheng
Publicado: (2025)

Systematic evaluation of computational tools to predict the effects of mutations on protein-ligand binding affinity in the absence of experimental structures
por: Pan, Qisheng
Publicado: (2025)

ERL‐ProLiGraph: Enhanced representation learning on protein‐ligand graph structured data for binding affinity prediction
por: Gloria Geine Paendong, et al.
Publicado: (2024)

Simultaneous Labeling and Binding affinity prediction for protein-ligand structures
por: Ranganath, Aditya, et al.
Publicado: (2025)

Quantum-enhanced unsupervised image segmentation for medical images analysis
por: Domingo, Laia, et al.
Publicado: (2024)

SG‐ML‐PLAP: A structure‐guided machine learning–based scoring function for protein–ligand binding affinity prediction
por: Sapna Pal, et al.
Publicado: (2024)

Improving protein-ligand binding prediction for shallow binding sites by incorporating interfacial water molecules
por: Bayarsaikhan, Bayartsetseg, et al.
Publicado: (2026)

Modern machine‐learning for binding affinity estimation of protein–ligand complexes: Progress, opportunities, and challenges
por: Tobias Harren, et al.
Publicado: (2024)

Incorporating graph neural network into route choice model
por: Ma, Yuxun, et al.
Publicado: (2025)

Sequence-based protein-protein interaction prediction and its applications in drug discovery
por: Charih, François, et al.
Publicado: (2025)

Can AI-predicted complexes teach machine learning to compute drug binding affinity?
por: Hsu, Wei-Tse, et al.
Publicado: (2025)

Uncertainty quantification of receptor ligand binding sites prediction
por: Chen, Nanjie, et al.
Publicado: (2024)

Unlocking GPCR–ligand interactions: Measuring binding affinities with thermal shift assay
por: Dmitrii Dashevskii, et al.
Publicado: (2025)

CovAngelo: A hybrid quantum-classical computing platform for accurate and scalable drug discovery
por: Evenseth, Linn, et al.
Publicado: (2026)

Structural insights into the fusion of annexin A5 and fluorescent proteins generating hundredfold differentiated binding affinities to phosphatidylserine
por: Mengyue Gao, et al.
Publicado: (2025)

Functional thermodynamics govern the ligand binding to human cytosolic transport proteins
por: Sebastian Michler, et al.
Publicado: (2026)

PepGB: Facilitating peptide drug discovery via graph neural networks
por: Lei, Yipin, et al.
Publicado: (2024)

Practical protein-pocket hydration-site prediction for drug discovery on a quantum computer
por: Loco, Daniele, et al.
Publicado: (2025)

Pi-SAGE: Permutation-invariant surface-aware graph encoder for binding affinity prediction
por: Banerjee, Sharmi, et al.
Publicado: (2025)

Generation of pharmacophores and classification of drugs using protein-ligand complexes
por: Eliana P. Velásquez
Publicado: (2012)

Lean classical-quantum hybrid neural network model for image classification
por: Liu, Ao, et al.
Publicado: (2024)

A rigorous hybridization of variational quantum eigensolver and classical neural network
por: Kim, Minwoo, et al.
Publicado: (2026)

QGAN-based data augmentation for hybrid quantum-classical neural networks
por: He, Run-Ze, et al.
Publicado: (2025)

DDI‐Transform: A neural network for predicting drug‐drug interaction events
por: Jiaming Su, et al.
Publicado: (2024)

Optimal normalization in quantum-classical hybrid models for anti-cancer drug response prediction
por: Ito, Takafumi, et al.
Publicado: (2025)

Assessing interaction recovery of predicted protein-ligand poses
por: Errington, David, et al.
Publicado: (2024)

Emergent Synaptic Plasticity from Tunable Dynamics of Probabilistic Bits
por: Banerjee, Sagnik, et al.
Publicado: (2025)

Phosphorylation of cytosolic hPGK1 affects protein stability and ligand binding: implications for its subcellular targeting in cancer
por: Juan Luis Pacheco‐García, et al.
Publicado: (2024)

Enhanced image classification via hybridizing quantum dynamics with classical neural networks
por: Zhou, Ruiyang, et al.
Publicado: (2025)

Development and large-scale benchmarks of a protein--ligand absolute binding free energy toolkit
por: Liu, Yu, et al.
Publicado: (2026)

Learnability of a hybrid quantum-classical neural network for graph-structured quantum data
por: Liang, Yanying, et al.
Publicado: (2024)

On fine-tuning Boltz-2 for protein-protein affinity prediction
por: King, James, et al.
Publicado: (2025)