Discovery of the First Selective Nanomolar Inhibitors of ERAP2 by Kinetic Target-Guided Synthesis.

Endoplasmic reticulum aminopeptidase 2 (ERAP2) is a key enzyme involved in the trimming of antigenic peptides presented by Major Histocompatibility Complex class I. It is a target of growing interest for the treatment of autoimmune diseases and in cancer immunotherapy. However, the discovery of potent and selective ERAP2 inhibitors is highly challenging. Herein, we have used kinetic target-guided synthesis (KTGS) to identify such inhibitors. Co-crystallization experiments revealed the binding mode of three different inhibitors with increasing potency and selectivity over related enzymes. Selected analogues engage ERAP2 in cells and inhibit antigen presentation in a cellular context. 4 d (BDM88951) displays favorable in vitro ADME properties and in vivo exposure. In summary, KTGS allowed the discovery of the first nanomolar and selective highly promising ERAP2 inhibitors that pave the way of the exploration of the biological roles of this enzyme and provide lead compounds for drug discovery efforts.

FastTargetPred: a program enabling the fast prediction of putative protein targets for input chemical databases.

SUMMARY: Several web-based tools predict the putative targets of a small molecule query compound by similarity to molecules with known bioactivity data using molecular fingerprints. In numerous situations, it would however be valuable to be able to run such computations on a local computer. We present FastTargetPred, a new program for the prediction of protein targets for small molecule queries. Structural similarity computations rely on a large collection of confirmed protein-ligand activities extracted from the curated ChEMBL 25 database. The program allows to annotate an input chemical library of ∼100k compounds within a few hours on a simple personal computer. AVAILABILITY AND IMPLEMENTATION: FastTargetPred is written in Python 3 (≥3.7) and C languages. Python code depends only on the Python Standard Library. The program can be run on Linux, MacOS and Windows operating systems. Pre-compiled versions are available at https://github.com/ludovicchaput/FastTargetPred. FastTargetPred is licensed under the GNU GPLv3. The program calls some scripts from the free chemistry toolkit MayaChemTools. CONTACT: bruno.villoutreix@inserm.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Identification of ebselen as a potent inhibitor of insulin degrading enzyme by a drug repurposing screening.

Insulin-degrading enzyme, IDE, is a metalloprotease implicated in the metabolism of key peptides such as insulin, glucagon, ß-amyloid peptide. Recent studies have pointed out its broader role in the cell physiology. In order to identify new drug-like inhibitors of IDE with optimal pharmacokinetic properties to probe its multiple roles, we ran a high-throughput drug repurposing screening. Ebselen, cefmetazole and rabeprazole were identified as reversible inhibitors of IDE. Ebselen is the most potent inhibitor (IC50(insulin) = 14 nM). The molecular mode of action of ebselen was investigated by biophysical methods. We show that ebselen induces the disorder of the IDE catalytic cleft, which significantly differs from the previously reported IDE inhibitors. IDE inhibition by ebselen can explain some of its reported activities in metabolism as well as in neuroprotection.