Hepatocellular carcinoma (HCC) ranks fourth in cancer-related mortality worldwide. This study aims to uncover the genes and pathways involved in HCC through network pharmacology (NP) and to discover potential drugs via machine learning (ML)-based lig...
The NLRP3 inflammasome, plays a critical role in the pathogenesis of rheumatoid arthritis (RA) by activating inflammatory cytokines such as IL1β and IL18. Targeting NLRP3 has emerged as a promising therapeutic strategy for RA. In this study, a multid...
This study illustrates the use of chemical fingerprints with machine learning for blood-brain barrier (BBB) permeability prediction. Employing the Blood Brain Barrier Database (B3DB) dataset for BBB permeability prediction, we extracted nine differen...
Traditional Chinese medicine (TCM) has been a cornerstone of health care for centuries, valued for its preventive and therapeutic properties. However, recent decades have revealed significant toxicological concerns associated with TCMs due to their c...
Glaucoma is an irreversible, progressive, degenerative eye disorder arising because of increased intraocular pressure, resulting in eventual vision loss if untreated. The QSPR relates, mathematically, by employing various algorithms, a specified prop...
Journal of chemical information and modeling
39844439
Essential oils (EOs) exhibit a broad spectrum of biological activities; however, their clinical application is hindered by challenges, such as variability in chemical composition and chemical/physical instability. A critical limitation is the lack of...
Human organic cation transporter 2 (hOCT2/SLC22A2) is a key drug transporter that facilitates the transport of endogenous and exogenous organic cations. Because hOCT2 is responsible for the development of adverse effects caused by platinum-based anti...
In recent years, machine learning has gained substantial attention for its ability to predict complex chemical and biological properties, including those of pharmaceutical compounds. This study proposes a machine learning-based quantitative structure...
In early-stage development of therapeutic monoclonal antibodies, assessment of the viability and ease of their purification typically requires extensive experimentation. However, the work required for upstream protein expression and downstream purifi...
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally ac...