Polypharmacology-Labeled Molecular Networking: An Analytical Technology Workflow for Accelerated Identification of Multiple Bioactive Constituents in Complex Extracts.

Discovery of sustainable and benign-by-design drugs to combat emerging health pandemics calls for new analytical technologies to explore the chemical and pharmacological properties of Nature's unique chemical space. Here, we present a new analytical technology workflow, polypharmacology-labeled molecular networking (PLMN), where merged positive and negative ionization tandem mass spectrometry-based molecular networking is linked with data from polypharmacological high-resolution inhibition profiling for easy and fast identification of individual bioactive constituents in complex extracts. The crude extract of Eremophila rugosa was subjected to PLMN analysis for the identification of antihyperglycemic and antibacterial constituents. Visually easy-interpretable polypharmacology scores and polypharmacology pie charts as well as microfractionation variation scores of each node in the molecular network provided direct information about each constituent's activity in the seven assays included in this proof-of-concept study. A total of 27 new non-canonical nerylneryl diphosphate-derived diterpenoids were identified. Serrulatane ferulate esters were shown to be associated with antihyperglycemic and antibacterial activities, including some showing synergistic activity with oxacillin in clinically relevant (epidemic) methicillin-resistant Staphylococcus aureus strains and some showing saddle-shaped binding to the active site of protein-tyrosine phosphatase 1B. PLMN is scalable in the number and types of assays included and thus holds potential for a paradigm shift toward polypharmacological natural-products-based drug discovery.

G protein- and agonist-bound serotonin 5-HT2A receptor model activated by steered molecular dynamics simulations.

A 5-HT(2A) receptor model was constructed by homology modeling based on the ß(2)-adrenergic receptor and the G protein-bound opsin crystal structures. The 5-HT(2A) receptor model was transferred into an active conformation by an agonist ligand and a G(αq) peptide in four subsequent steered molecular dynamics (MD) simulations. The driving force for the transformation was the addition of several known intermolecular and receptor interhelical hydrogen bonds enforcing the necessary helical and rotameric movements. Subsquent MD simulations without constraints confirmed the stability of the activated receptor model as well as revealed new information about stabilizing residues and bonds. The active 5-HT(2A) receptor model was further validated by retrospective ligand screening of more than 9400 compounds, whereof 182 were known ligands. The results show that the model can be used in drug discovery for virtual screening and structure-based ligand design as well as in GPCR activation studies.

Virtual screening and prediction of site of metabolism for cytochrome P450 1A2 ligands.

With the availability of an increasing number of high resolution 3D structures of human cytochrome P450 enzymes, structure-based modeling tools are more readily used. In this study we explore the possibilities of using docking and scoring experiments on cytochrome P450 1A2. Three different questions have been addressed: 1. Binding orientations and conformations were successfully predicted for various substrates. 2. A virtual screen was performed with satisfying enrichment rates. 3. A classification of individual compounds into active and inactive was performed. It was found that while docking can be used successfully to address the first two questions, it seems to be more difficult to perform the classification. Different scoring functions were included, and the well-characterized water molecule in the active site was included in various ways. Results are compared to experimental data and earlier classification data using machine learning methods. The possibilities and limitations of using structure-based drug design tools for cytochrome P450 1A2 come to light and are discussed.