Rational design of small molecules that modulate the transcriptional function of the response regulator PhoP.

The response regulator PhoP, which is part of the PhoP/PhoQ two-component system, regulates the expression of multiple genes involved in controlling virulence in Salmonella enterica serovar Typhimurium and other species of Gram-negative bacteria. Modulating the phosphorylation-mediated dimerization in the receiver domain may interfere with the transcriptional function of PhoP. In this study, we analyzed the therapeutic potential of the PhoP receiver domain by exploring it as a potential target for drug design. The structural information was then applied to identify the first hit compounds from commercial chemical libraries by combining pharmacophore modelling and docking methods with a GFP (Green Fluorescent Protein)-based promoter-fusion bioassay. In total, one hundred and forty compounds were selected, purchased, and tested for biological activity. Several novel scaffolds showed acceptable potency to modulate the transcriptional function of PhoP, either by enhancing or inhibiting the expression of PhoP-dependent genes. These compounds may be used as the starting point for developing modulators that target the protein-protein interface of the PhoP protein as an alternative strategy against antibiotic resistance.

Retrieving novel C5aR antagonists using a hybrid ligand-based virtual screening protocol based on SVM classification and pharmacophore models.

C5aR antagonists have been thought as potential immune mediators in various inflammatory and autoimmune diseases, and discovery of C5aR antagonists has attracted much attention in recent years. The discovery of C5aR antagonists was usually achieved through high-throughput screening, which usually suffered a high cost and a low success rate. Currently, the fast developing computer-aided virtual screening (VS) methods provide economic and rapid approaches to the lead discovery. In this account, we proposed a hybrid ligand-based VS protocol that is based on support vector machine (SVM) classification and pharmacophore models for retrieving novel C5aR antagonists. Performance evaluation of this hybrid VS protocol in virtual screening against a large independent test set, T-CHEM, showed that the hybrid VS approach significantly increased the hit rate and enrichment factor compared with the individual SVM classification model-based VS and pharmacophore model-based VS, as well as molecular docking-based VS in that the receptor structure was created by homology modeling. The hybrid VS approach was then used to screen several large chemical libraries including PubChem, Specs, and Enamine. Finally, a total of 20 compounds were selected from the top ranking hits, and shifted to the subsequent in vitro and in vivo studies, which results will be reported in the near future.