Structure-based optimization of non-peptidic Cathepsin D inhibitors.

Bioorg Med Chem Lett

Merck KGaA, Merck Serono Research, Small Molecule Platform, Frankfurter Str. 250, 64293 Darmstadt, Germany.

Published: September 2014


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

We discovered a novel series of non-peptidic acylguanidine inhibitors of Cathepsin D as target for osteoarthritis. The initial HTS-hits were optimized by structure-based design using CatD X-ray structures resulting in single digit nanomolar potency in the biochemical CatD assay. However, the most potent analogues showed only micromolar activities in an ex vivo glycosaminoglycan (GAG) release assay in bovine cartilage together with low cellular permeability and suboptimal microsomal stability. This new scaffold can serve as a starting point for further optimization towards in vivo efficacy.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.bmcl.2014.07.054DOI Listing

Publication Analysis

Top Keywords

structure-based optimization
4
optimization non-peptidic
4
non-peptidic cathepsin
4
cathepsin inhibitors
4
inhibitors discovered
4
discovered novel
4
novel series
4
series non-peptidic
4
non-peptidic acylguanidine
4
acylguanidine inhibitors
4

Similar Publications

This review meticulously examines the development, design, and pharmacological assessment of both well known antiviral and antihypertensive medications all time employing new chemical techniques and structure-based drug design to design and synthesize vital therapeutic entities such as aliskiren (renin inhibitor), captopril (a2-ACE-Inhibitor), dorzolamide (inhibitor of carbonic anhydrase) the review demonstrates initial steps regarding the significance of stereoselective synthesis, metal chelating pharmacophores, and rational molecular properties. More importantly, protease inhibitors (i.e.

View Article and Find Full Text PDF

Triggering receptor expressed on myeloid cells 2 (TREM2) is a microglia-specific receptor whose activation promotes phagocytosis and neuroprotection in Alzheimer's disease (AD) and related neurodegenerative disorders. While therapeutic efforts have largely focused on antibodies, small molecule TREM2 modulators remain limited. Here, we applied a structure- based virtual screening workflow targeting a putative allosteric site on TREM2, guided by PyRod-derived pharmacophores from molecular dynamics simulations.

View Article and Find Full Text PDF

The delta opioid receptor (DOR) is a promising target for developing analgesics with fewer side effects compared to mu opioid receptor (MOR) agonists. However, non-peptidyl DOR-selective agonists remain limited. Using the "message-address" concept in opioid ligand design, we designed and synthesized a series of para-substituted N-cyclopropylmethyl-7α-phenyl-6,14-endoetheno-tetrahydronorthebaines to explore their binding affinity and selectivity for DOR over MOR and kappa opioid receptor (KOR).

View Article and Find Full Text PDF

The arginine-phenylalanine-amide neuropeptide receptor family: Physiological effects, drug development, and structural insights.

Neural Regen Res

September 2025

Kobilka Institute of Innovative Drug Discovery, Shenzhen Key Laboratory of Steroid Drug Discovery and Development, School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong Province, China.

The arginine-phenylalanine-amide neuropeptide receptor family comprises a subclass within the G protein-coupled receptor superfamily with crucial roles in physiological regulation. These receptors recognize and bind neuropeptides with an arginine-phenylalanine-amide motif, thereby participating in a variety of biological processes such as energy metabolism, pain perception, and reproductive functions. In this review, we explore the physiological and pathological processes involving these receptors and delve into the structure-activity relationships of their ligand peptides, clarifying the key structural motifs within these neuropeptides that determine their biological activity, pharmacological potency, and receptor selectivity.

View Article and Find Full Text PDF

DDI-CYP: Metabolism ensemble models for drug-drug interaction predictions.

Drug Metab Dispos

July 2025

Collaborations Pharmaceuticals, Inc, Raleigh, North Carolina. Electronic address:

Cytochrome P450 (P450)-mediated drug-drug interactions (DDIs) are responsible for most adverse drug interactions, and occur when 2 concurrently administered drugs inhibit, upregulate, or are substrates of the same target enzyme. A machine learning approach enables the detection of DDIs with rarely used drugs, as well as newly approved drugs. To facilitate this, we present a framework for predicting DDIs by first predicting P450 interactions for both drugs, generating a fingerprint based on the predictions in addition to the molecular structures of the drugs, and training a machine learning model to predict the overall interaction.

View Article and Find Full Text PDF