HydraScreen: a generalizable structure-based deep learning approach to drug discovery
A Prat, H Abdel Aty, O Bastas… - Journal of Chemical …, 2024 - ACS Publications
We propose HydraScreen, a deep-learning framework for safe and robust accelerated drug
discovery. HydraScreen utilizes a state-of-the-art 3D convolutional neural network designed …
discovery. HydraScreen utilizes a state-of-the-art 3D convolutional neural network designed …
Artificial Intelligence in Drug Identification and Validation: A Scoping Review
The end-to-end process in the discovery of drugs involves therapeutic candidate
identification, validation of identified targets, identification of hit compound series, lead …
identification, validation of identified targets, identification of hit compound series, lead …
High-Throughput Preclinical Models and Pharmacoproteomics
V Prajapati, M Verma, GS Kumar, J Patel - … : Recent Trends and …, 2024 - Springer
In the relentless pursuit of groundbreaking therapies, high-throughput screening (HTS),
preclinical modeling, and pharmacoproteomics have risen as essential pillars within drug …
preclinical modeling, and pharmacoproteomics have risen as essential pillars within drug …
SE (3) Equivariant Topologies for Structure-based Drug Discovery
A Prat, HA Aty, A Pabrinkis, O Bastas, T Paquet… - 2024 - chemrxiv.org
Modeling protein-ligand interactions is a challenging task that has been approached
through an array of perspectives. From physics-based computational approaches to vast …
through an array of perspectives. From physics-based computational approaches to vast …