Ligandability and druggability assessment via machine learning
Drug discovery is a daunting and failure‐prone task. A critical process in this research field
is represented by the biological target and pocket identification steps as they heavily …
is represented by the biological target and pocket identification steps as they heavily …
A comprehensive survey on protein-ligand binding site prediction
Y Xia, X Pan, HB Shen - Current Opinion in Structural Biology, 2024 - Elsevier
Protein-ligand binding site prediction is critical for protein function annotation and drug
discovery. Biological experiments are time-consuming and require significant equipment …
discovery. Biological experiments are time-consuming and require significant equipment …
Explainable Graph Neural Networks with Data Augmentation for Predicting pKa of C–H Acids
The p K a of C–H acids is an important parameter in the fields of organic synthesis, drug
discovery, and materials science. However, the prediction of p K a is still a great challenge …
discovery, and materials science. However, the prediction of p K a is still a great challenge …
Equipocket: an e (3)-equivariant geometric graph neural network for ligand binding site prediction
Predicting the binding sites of target proteins plays a fundamental role in drug discovery.
Most existing deep-learning methods consider a protein as a 3D image by spatially …
Most existing deep-learning methods consider a protein as a 3D image by spatially …
Comparative evaluation of methods for the prediction of protein–ligand binding sites
The accurate identification of protein–ligand binding sites is of critical importance in
understanding and modulating protein function. Accordingly, ligand binding site prediction …
understanding and modulating protein function. Accordingly, ligand binding site prediction …
AF2BIND: predicting ligand-binding sites using the pair representation of AlphaFold2
Predicting ligand-binding sites, particularly in the absence of previously resolved
homologous structures, presents a significant challenge in structural biology. Here, we …
homologous structures, presents a significant challenge in structural biology. Here, we …
[HTML][HTML] A Point Cloud Graph Neural Network for Protein–Ligand Binding Site Prediction
Y Zhao, S He, Y Xing, M Li, Y Cao, X Wang… - International Journal of …, 2024 - mdpi.com
Predicting protein–ligand binding sites is an integral part of structural biology and drug
design. A comprehensive understanding of these binding sites is essential for advancing …
design. A comprehensive understanding of these binding sites is essential for advancing …
Unraveling viral drug targets: a deep learning-based approach for the identification of potential binding sites
Abstract The coronavirus disease 2019 (COVID-19) pandemic has spurred a wide range of
approaches to control and combat the disease. However, selecting an effective antiviral drug …
approaches to control and combat the disease. However, selecting an effective antiviral drug …
Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning
X Zeng, GP Su, SJ Li, SQ Lv, ML Wen, Y Li - BMC bioinformatics, 2024 - Springer
Background Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding
sites (DTS) is crucial for drug screening, repositioning, and design, as well as for …
sites (DTS) is crucial for drug screening, repositioning, and design, as well as for …
Hybrid protein-ligand binding residue prediction with protein language models: Does the structure matter?
Predicting protein-ligand binding sites is crucial in studying protein interactions with
applications in biotechnology and drug discovery. Two distinct paradigms have emerged for …
applications in biotechnology and drug discovery. Two distinct paradigms have emerged for …