GENERA: a combined genetic/deep-learning algorithm for multiobjective target-oriented de novo design
This study introduces a new de novo design algorithm called GENERA that combines the
capabilities of a deep-learning algorithm for automated drug-like analogue design, called …
capabilities of a deep-learning algorithm for automated drug-like analogue design, called …
Deep learning-based bioactive therapeutic peptide generation and screening
Many bioactive peptides demonstrated therapeutic effects over complicated diseases, such
as antiviral, antibacterial, anticancer, etc. It is possible to generate a large number of …
as antiviral, antibacterial, anticancer, etc. It is possible to generate a large number of …
Endocannabinoid degradation enzyme inhibitors as potential antipsychotics: A medicinal chemistry perspective
The endocannabinoid system (ECS) plays a very important role in numerous physiological
and pharmacological processes, such as those related to the central nervous system (CNS) …
and pharmacological processes, such as those related to the central nervous system (CNS) …
Efficient dynamic weighted set sampling and its extension
Given a weighted set S of n elements, weighted set sampling (WSS) samples an element in
S so that each element ai; is sampled with a probability proportional to its weight w (ai). The …
S so that each element ai; is sampled with a probability proportional to its weight w (ai). The …
State-of-the-art review of neural network applications in pharmaceutical manufacturing: current state and future directions
E Gholipour, A Bastas - Journal of Intelligent Manufacturing, 2024 - Springer
Neural network applications, as an emerging machine learning technology, are increasingly
being integrated into pharmaceutical manufacturing technologies, offering significant …
being integrated into pharmaceutical manufacturing technologies, offering significant …
UnCorrupt SMILES: a novel approach to de novo design
Generative deep learning models have emerged as a powerful approach for de novo drug
design as they aid researchers in finding new molecules with desired properties. Despite …
design as they aid researchers in finding new molecules with desired properties. Despite …
Development of N-(1-Adamantyl)benzamides as Novel Anti-Inflammatory Multitarget Agents Acting as Dual Modulators of the Cannabinoid CB2 Receptor and Fatty …
F Intranuovo, L Brunetti, P DelRe… - Journal of Medicinal …, 2022 - ACS Publications
Cannabinoid type 2 receptor (CB2R), belonging to the endocannabinoid system, is
overexpressed in pathologies characterized by inflammation, and its activation counteracts …
overexpressed in pathologies characterized by inflammation, and its activation counteracts …
Application of machine learning to the design of energetic materials: preliminary experience and comparison with alternative techniques
C Wespiser, D Mathieu - Propellants, Explosives, Pyrotechnics, 2023 - Wiley Online Library
The last few years have seen a steep rise in the use of data‐driven methods in different
scientific fields historically relying on theoretical or empirical approaches. Chemistry is at the …
scientific fields historically relying on theoretical or empirical approaches. Chemistry is at the …
[HTML][HTML] ALPACA: A machine Learning Platform for Affinity and selectivity profiling of CAnnabinoids receptors modulators
The development of small molecules that selectively target the cannabinoid receptor
subtype 2 (CB2R) is emerging as an intriguing therapeutic strategy to treat …
subtype 2 (CB2R) is emerging as an intriguing therapeutic strategy to treat …
AMALPHI: A Machine Learning Platform for Predicting Drug-Induced PhospholIpidosis
Drug-induced phospholipidosis (PLD) involves the accumulation of phospholipids in cells of
multiple tissues, particularly within lysosomes, and it is associated with prolonged exposure …
multiple tissues, particularly within lysosomes, and it is associated with prolonged exposure …