The present state and challenges of active learning in drug discovery
Highlights•Active learning is extensively used across various drug discovery stages.•Active
learning aids in solving multiple challenges in predicting compound–target …
learning aids in solving multiple challenges in predicting compound–target …
Allo-targeting of the kinase domain: Insights from in silico studies and comparison with experiments
The eukaryotic protein kinase domain has been a broadly explored target for drug discovery,
despite limitations imposed by its high sequence conservation as a shared modular domain …
despite limitations imposed by its high sequence conservation as a shared modular domain …
BINDTI: a bi-directional intention network for drug-target interaction identification based on attention mechanisms
L Peng, X Liu, L Yang, L Liu, Z Bai… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In
vitro experimental methods are expensive, laborious, and time-consuming. Deep learning …
vitro experimental methods are expensive, laborious, and time-consuming. Deep learning …
Scaling Crystal Structure Relaxation with a Universal Trustworthy Deep Generative Model
The evolution of AI and high-throughput technologies has boosted a rapid increase in the
number of new materials, challenging our computational ability to comprehensively analyze …
number of new materials, challenging our computational ability to comprehensively analyze …
Protein-ligand binding affinity prediction: Is 3D binding pose needed?
Accurate protein-ligand binding affinity prediction is crucial in drug discovery. Existing
methods are predominately docking-free, without explicitly considering atom-level …
methods are predominately docking-free, without explicitly considering atom-level …
Leveraging multiple data types for improved compound-kinase bioactivity prediction
Abstract Machine learning methods offer time-and cost-effective means for identifying novel
chemical matter as well as guiding experimental efforts to map enormous compound-kinase …
chemical matter as well as guiding experimental efforts to map enormous compound-kinase …
Protein-ligand binding affinity prediction: Is 3D binding pose needed?
Accurate protein-ligand binding affinity prediction is crucial in drug discovery. Existing
methods are predominately docking-free, without explicitly considering atom-level …
methods are predominately docking-free, without explicitly considering atom-level …
Attention-based method to predict drug-target interactions across seven protein classes
A Schulman - 2024 - aaltodoc.aalto.fi
Most approved drugs bind with proteins to modulate their activity for treating a diverse range
of diseases. Unfortunately, drug development is a long and costly process. Computational …
of diseases. Unfortunately, drug development is a long and costly process. Computational …
Machine learning for large and small data biomedical discovery
Y Luo - 2021 - ideals.illinois.edu
In modern biomedicine, the role of computation becomes more crucial in light of the ever-
increasing growth of biological data, which requires effective computational methods to …
increasing growth of biological data, which requires effective computational methods to …