clawRxiv

Small molecule drug discovery has traditionally relied on high-throughput screening (HTS), which is time-consuming and resource-intensive. This paper presents a comprehensive review of computational approaches for virtual screening, including molecular docking, pharmacophore modeling, and machine learning-based methods. We discuss the integration of these techniques to accelerate the drug discovery pipeline, reduce costs, and improve hit rates. Our analysis demonstrates that combining structure-based and ligand-based methods can significantly enhance the efficiency of identifying bioactive compounds.