Structure-based drug design with geometric deep learning
Abstract Structure-based drug design uses three-dimensional geometric information of
macromolecules, such as proteins or nucleic acids, to identify suitable ligands. Geometric …
macromolecules, such as proteins or nucleic acids, to identify suitable ligands. Geometric …
Geometric deep learning for structure-based ligand design
A pervasive challenge in drug design is determining how to expand a ligand─ a small
molecule that binds to a target biomolecule─ in order to improve various properties of the …
molecule that binds to a target biomolecule─ in order to improve various properties of the …
A geometric deep learning approach to predict binding conformations of bioactive molecules
O Méndez-Lucio, M Ahmad… - Nature Machine …, 2021 - nature.com
Understanding the interactions formed between a ligand and its molecular target is key to
guiding the optimization of molecules. Different experimental and computational methods …
guiding the optimization of molecules. Different experimental and computational methods …
Geometric deep learning on molecular representations
Geometric deep learning (GDL) is based on neural network architectures that incorporate
and process symmetry information. GDL bears promise for molecular modelling applications …
and process symmetry information. GDL bears promise for molecular modelling applications …
Equibind: Geometric deep learning for drug binding structure prediction
Predicting how a drug-like molecule binds to a specific protein target is a core problem in
drug discovery. An extremely fast computational binding method would enable key …
drug discovery. An extremely fast computational binding method would enable key …
DG‐GL: Differential geometry‐based geometric learning of molecular datasets
Motivation: Despite its great success in various physical modeling, differential geometry
(DG) has rarely been devised as a versatile tool for analyzing large, diverse, and complex …
(DG) has rarely been devised as a versatile tool for analyzing large, diverse, and complex …
Calibrated geometric deep learning improves kinase–drug binding predictions
Protein kinases regulate various cellular functions and hold significant pharmacological
promise in cancer and other diseases. Although kinase inhibitors are one of the largest …
promise in cancer and other diseases. Although kinase inhibitors are one of the largest …
Structure‐Based Drug Discovery with Deep Learning
Artificial intelligence (AI) in the form of deep learning has promise for drug discovery and
chemical biology, for example, to predict protein structure and molecular bioactivity, plan …
chemical biology, for example, to predict protein structure and molecular bioactivity, plan …
Molecule generation for target protein binding with structural motifs
Z Zhang, Y Min, S Zheng, Q Liu - The Eleventh International …, 2023 - openreview.net
Designing ligand molecules that bind to specific protein binding sites is a fundamental
problem in structure-based drug design. Although deep generative models and geometric …
problem in structure-based drug design. Although deep generative models and geometric …
Enhanced Deep‐Learning Prediction of Molecular Properties via Augmentation of Bond Topology
H Cho, IS Choi - ChemMedChem, 2019 - Wiley Online Library
Deep learning has made great strides in tackling chemical problems, but still lacks full‐
fledged representations for three‐dimensional (3D) molecular structures for its inner …
fledged representations for three‐dimensional (3D) molecular structures for its inner …