Exploiting PubChem for virtual screening

Areas covered in this review: This review builds on recent PubChem-related computational chemistry research reported by other authors while providing readers with an overview of the PubChem database, focusing on its increasing role in cheminformatics, virtual screening and toxicity prediction modeling. What the reader will gain: These publicly available data sets in PubChem provide great opportunities for scientists to perform cheminformatics and virtual screening research for computer-aided drug design. However, the high volume and complexity of the data sets, in particular the bioassay-associated false positives/negatives and highly imbalanced data sets in PubChem, also create major challenges. Several approaches regarding the modeling of PubChem data sets and development of virtual screening models for bioactivity and toxicity predictions are also reviewed. Take home message: Novel data-mining cheminformatics tools and virtual screening algorithms are being developed and used to retrieve, annotate and analyze the large-scale and highly complex PubChem biological screening data for drug design.