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 …
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 …
Deep learning enables rapid identification of potent DDR1 kinase inhibitors
We have developed a deep generative model, generative tensorial reinforcement learning
(GENTRL), for de novo small-molecule design. GENTRL optimizes synthetic feasibility …
(GENTRL), for de novo small-molecule design. GENTRL optimizes synthetic feasibility …
Rethinking drug design in the artificial intelligence era
P Schneider, WP Walters, AT Plowright… - Nature reviews drug …, 2020 - nature.com
Artificial intelligence (AI) tools are increasingly being applied in drug discovery. While some
protagonists point to vast opportunities potentially offered by such tools, others remain …
protagonists point to vast opportunities potentially offered by such tools, others remain …
Concepts of artificial intelligence for computer-assisted drug discovery
X Yang, Y Wang, R Byrne, G Schneider… - Chemical …, 2019 - ACS Publications
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …
opportunities for the discovery and development of innovative drugs. Various machine …
Ethnobotany and the role of plant natural products in antibiotic drug discovery
The crisis of antibiotic resistance necessitates creative and innovative approaches, from
chemical identification and analysis to the assessment of bioactivity. Plant natural products …
chemical identification and analysis to the assessment of bioactivity. Plant natural products …
GuacaMol: benchmarking models for de novo molecular design
N Brown, M Fiscato, MHS Segler… - Journal of chemical …, 2019 - ACS Publications
De novo design seeks to generate molecules with required property profiles by virtual
design-make-test cycles. With the emergence of deep learning and neural generative …
design-make-test cycles. With the emergence of deep learning and neural generative …
Deep learning for molecular design—a review of the state of the art
In the space of only a few years, deep generative modeling has revolutionized how we think
of artificial creativity, yielding autonomous systems which produce original images, music …
of artificial creativity, yielding autonomous systems which produce original images, music …
Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …
However, developing drugs for central nervous system (CNS) disorders remains the most …
Generative models for de novo drug design
Artificial intelligence (AI) is booming. Among various AI approaches, generative models
have received much attention in recent years. Inspired by these successes, researchers are …
have received much attention in recent years. Inspired by these successes, researchers are …