A systematic survey in geometric deep learning for structure-based drug design
Structure-based drug design (SBDD) utilizes the three-dimensional geometry of proteins to
identify potential drug candidates. Traditional methods, grounded in physicochemical …
identify potential drug candidates. Traditional methods, grounded in physicochemical …
Current strategies to address data scarcity in artificial intelligence-based drug discovery: A comprehensive review
A Gangwal, A Ansari, I Ahmad, AK Azad… - Computers in Biology …, 2024 - Elsevier
Artificial intelligence (AI) has played a vital role in computer-aided drug design (CADD). This
development has been further accelerated with the increasing use of machine learning (ML) …
development has been further accelerated with the increasing use of machine learning (ML) …
Machine learning for predicting protein properties: A comprehensive review
Y Wang, Y Zhang, X Zhan, Y He, Y Yang, L Cheng… - Neurocomputing, 2024 - Elsevier
In the field of protein engineering, the function and structure of proteins are key to
understanding cellular mechanisms, biological evolution, and biodiversity. With the …
understanding cellular mechanisms, biological evolution, and biodiversity. With the …
General-purpose Pre-trained Model Towards Cross-domain Molecule Learning
Y Zhu, M Li, J Ye, J Liu, K Fu, J Wu, Z Wang - openreview.net
Self-supervised pre-training on biomolecules has achieved remarkable success in various
biochemical applications, such as drug discovery and protein design. However, in most …
biochemical applications, such as drug discovery and protein design. However, in most …