Generative machine learning for de novo drug discovery: A systematic review
DD Martinelli - Computers in Biology and Medicine, 2022 - Elsevier
Recent research on artificial intelligence indicates that machine learning algorithms can
auto-generate novel drug-like molecules. Generative models have revolutionized de novo …
auto-generate novel drug-like molecules. Generative models have revolutionized de novo …
[HTML][HTML] Integrating structure-based approaches in generative molecular design
Generative molecular design for drug discovery and development has seen a recent
resurgence promising to improve the efficiency of the design-make-test-analyse cycle; by …
resurgence promising to improve the efficiency of the design-make-test-analyse cycle; by …
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 …
Structure-based drug design with equivariant diffusion models
Abstract Structure-based drug design (SBDD) aims to design small-molecule ligands that
bind with high affinity and specificity to pre-determined protein targets. Generative SBDD …
bind with high affinity and specificity to pre-determined protein targets. Generative SBDD …
Zero-shot 3d drug design by sketching and generating
Drug design is a crucial step in the drug discovery cycle. Recently, various deep learning-
based methods design drugs by generating novel molecules from scratch, avoiding …
based methods design drugs by generating novel molecules from scratch, avoiding …
[HTML][HTML] Deep generative models for 3D molecular structure
Deep generative models have gained recent popularity for chemical design. Many of these
models have historically operated in 2D space; however, more recently explicit 3D …
models have historically operated in 2D space; however, more recently explicit 3D …
Generative models should at least be able to design molecules that dock well: A new benchmark
Designing compounds with desired properties is a key element of the drug discovery
process. However, measuring progress in the field has been challenging due to the lack of …
process. However, measuring progress in the field has been challenging due to the lack of …
Efficient and enhanced sampling of drug‐like chemical space for virtual screening and molecular design using modern machine learning methods
Drug design involves the process of identifying and designing novel molecules that have
desirable properties and bind well to a given target receptor. Typically, such molecules are …
desirable properties and bind well to a given target receptor. Typically, such molecules are …
Fragment-based ligand generation guided by geometric deep learning on protein-ligand structure
Computationally-aided design of novel molecules has the potential to accelerate drug
discovery. Several recent generative models aimed to create new molecules for specific …
discovery. Several recent generative models aimed to create new molecules for specific …
A high-quality data set of protein–ligand binding interactions via comparative complex structure modeling
X Li, C Shen, H Zhu, Y Yang, Q Wang… - Journal of Chemical …, 2024 - ACS Publications
High-quality protein–ligand complex structures provide the basis for understanding the
nature of noncovalent binding interactions at the atomic level and enable structure-based …
nature of noncovalent binding interactions at the atomic level and enable structure-based …