ArticleMolecular diversity2026
Identification of novel serotonin transporter (SERT) inhibitors via large-scale machine learning-based virtual screening and molecular dynamics simulations.
Article in Molecular diversity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
3 authors.
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Abstract
The serotonin transporter (SERT) plays a pivotal role in inflammatory responses and is a central therapeutic target for depression. Consequently, identifying potent SERT inhibitors remains a high priority in early-stage drug discovery. In this study, we evaluated twelve regression models, among which LightGBM, Random Forest, and XGBoost exhibited superior predictive performance, yielding R
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Registered trials
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