A Strategy Combining Differential Low-Throughput Screening and Virtual Screening (DLS-VS) Accelerating the Discovery of new Modulators for the Orphan GPR34 Receptor.

The DLS-VS strategy was developed as an integrated method for identifying chemical modulators for orphan GPCRs. It combines differential low-throughput screening (DLS) and virtual screening (VS). The two cascaded techniques offer complementary advantages and allow the experimental testing of a minimal number of compounds. First, DLS identifies modulators specific for the considered receptor among a set of receptors, through the screening of a small library with diverse chemical compounds. Then, an active molecular model of the receptor is built by homology to a validated template, and it is progressively refined by rotamers modification for key side-chains, by VS of the already screened library, and by iterative selection of the model generating the best enrichment. The refined active model is finally used for the VS of a large chemical library and the selection of a small set of compounds for experimental testing. Applied to the orphan receptor GPR34, the DLS-VS strategy combined the experimental screening of 20 000 compounds and the virtual screening of 1 250 000 compounds. It identified one agonist and eight inverse agonists, showing a high chemical diversity. We describe the method. The strategy can be applied to other GPCRs.

High-resolution dose-response screening using droplet-based microfluidics.

A critical early step in drug discovery is the screening of a chemical library. Typically, promising compounds are identified in a primary screen and then more fully characterized in a dose-response analysis with 7-10 data points per compound. Here, we describe a robust microfluidic approach that increases the number of data points to approximately 10,000 per compound. The system exploits Taylor-Aris dispersion to create concentration gradients, which are then segmented into picoliter microreactors by droplet-based microfluidics. The large number of data points results in IC(50) values that are highly precise (± 2.40% at 95% confidence) and highly reproducible (CV = 2.45%, n = 16). In addition, the high resolution of the data reveals complex dose-response relationships unambiguously. We used this system to screen a chemical library of 704 compounds against protein tyrosine phosphatase 1B, a diabetes, obesity, and cancer target. We identified a number of novel inhibitors, the most potent being sodium cefsulodine, which has an IC(50) of 27 ± 0.83 µM.