Yinhang Liu

Abstract Machine learning–guided virtual screening has the potential to accelerate early-stage drug discovery, but its practical utility is often limited by uncertain generalization to different chemical scaffolds and by insufficient prospective evaluation under realistic experimental constraints. To address these challenges, we conduct a target-driven virtual screening study using TAME-VS against aldo–keto reductase 1C3 (AKR1C3), an enzyme implicated in cancer progression and chemoresistance.

Get full access to this article View all available purchase options and get full access to this article. Data Availability Statement All data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request. Acknowledgments This work was supported by the Special Project of the Ministry of Housing and Urban-Rural Development of the People’s Republic of China (Grant No. ZLAQ(2019)AQ-4).

1. Introduction Prefabricated construction is emerging as a new trend in the construction industry, gaining widespread attention due to its efficient supply chain coordination and advanced construction techniques [1]. However, despite the extensive research on safety evaluation in traditional construction projects, studies on safety evaluation for prefabricated construction are relatively scarce. This highlights the urgency for in-depth research on safety evaluation for prefabricated construction.