Dan C. Fara

Lead-like, drug-like or ''Pub-like'': how different are they?

Academic and industrial research continues to be focused on discovering new classes of compounds based on HTS. Post-HTS analyses need to prioritize compounds that are progressed to chemical probe or lead status. We report trends in probe, lead and drug discovery by examining the following categories of compounds: 385 leads and the 541 drugs that emerged from them; “active” (152) and “inactive” (1488) compounds from the Molecular Libraries Initiative Small Molecule Repository (MLSMR) tested by HTS; “active” (46) and “inactive” (72) compounds from Nature Chemical Biology (NCB) tested by HTS; compounds in the drug development phase (I, II, III and launched), as indexed in MDDR; and medicinal chemistry compounds from WOMBAT, separated into high-activity (5,784 compounds with nanomolar activity or better) and low-activity (30,690 with micromolar activity or less). We examined Molecular weight (MW), molecular complexity, flexibility, the number of hydrogen bond donors and acceptors, LogP—the octanol/water partition coefficient estimated by ClogP and ALOGPS), LogSw (intrinsic water solubility, estimated by ALOGPS) and the number of Rule of five (Ro5) criteria violations. Based on the 50% and 90% distribution moments of the above properties, there were no significant difference between leads of known drugs and “actives” from MLSMR or NCB (chemical probes). “Inactives” from NCB and MLSMR were also found to exhibit similar properties. From these combined sets, we conclude that “Actives” (569 compounds) are less complex, less flexible, and more soluble than drugs (1,651 drugs), and significantly smaller, less complex, less hydrophobic and more soluble than the 5,784 high-activity WOMBAT compounds. These trends indicate that chemical probes are similar to leads with respect to some properties, e.g., complexity, solubility, and hydrophobicity.

Duplex High Throughput Flow Cytometry Screen Identifies Two Novel Formylpeptide Receptor Family Probes

Of recent, clinical interest have been two related human G‐protein coupled receptors: formylpeptide receptor (FPR), linked to antibacterial inflammation and malignant glioma cell metastasis; and FPR like‐1 (FPRL1), linked to chronic inflammation in systemic amyloidosis, Alzheimers disease, and prion diseases. In association with the National Institutes of Health (NIH) Molecular Library Screening Network, we implemented a flow‐cytometry‐based high‐throughput screening (HTS) approach for identifying selective small molecule FPR and FPRL1 ligands. The screening assay measured the ability of test compounds to competitively displace a high‐affinity, fluorescein‐ labeled peptide ligand from FPR, FPRL1, or both. U937 cells expressing FPR and rat basophil leukemia (RBL) cells expressing FPRL1 were tested together in a “duplex” format. The U937 cells were color coded with red‐fluorescent dye allowing their distinction during analysis. Compounds, cells, and fluorescent ligand were sequentially combined (no wash) in 15 μl assay volumes in 384‐well plates. Throughput averaged ∼11 min per plate to analyze ∼4,000 cells (∼2,000/receptor) in a 2 μl aspirate from each well. In primary single concentration HTS of 24,304 NIH Small Molecule Repository compounds, 253 resulted in inhibition >30% (181 for FPR, 72 for FPRL1) of which 40 had selective binding inhibition constants (Ki) ≤ 4 μM (34 for FPR and 6 for FPRL1). An additional 1,446 candidate compounds were selected by structure–activity‐relationship analysis of the hits and screened to identify novel ligands for FPR (3570‐0208, Ki = 95 ± 10 nM) and FPRL1 (BB‐V‐115, Ki = 270 ± 51 nM). Each was a selective antagonist in calcium response assays and the most potent small molecule antagonist reported for its respective receptor to date. The duplex assay format reduced assay time, minimized reagent requirements, and provided selectivity information at every screening stage, thus proving to be an efficient means to screen for selective receptor ligand probes.

Integration of virtual and physical screening

High-throughput screening (HTS) represents the dominant technique for the identification of new lead compounds in current drug discovery. It consists of physical screening (PS) of large libraries of chemicals against one or more specific biological targets. Virtual screening (VS) is a strategy for in silico evaluation of chemical libraries for a given target, and can be integrated to focus the PS process. The present work addresses the integration of both PS and VS, respectively. Section editors: Tudor Oprea – University of New Mexico School of Medicine, Albuquerque, USA Alex Tropsha – University of North Carolina, Chapel Hill, USA