OLB-AC: toward optimizing ligand bioactivities through deep graph learning and activity cliffs

• المؤلفون الرئيسيون: Yin, Yueming, Hu, Haifeng, Yang, Jitao, Ye, Chun, Goh, Wilson Wen Bin, Kong, Adams Wai Kin, Wu, Jiansheng
• مؤلفون آخرون: College of Computing and Data Science
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Computer and Information Science; Artificial neural network; Deep learning
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/181726
• المؤسسة: Nanyang Technological University

Motivation: Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the existence of activity cliffs (ACs), where minor chemical alterations can lead to significant changes in bioactivity. In response, several DGL models h...