Degenerative retinal diseases associated with photoreceptor loss are a leading cause of visual impairment worldwide, with limited treatment options. Phenotypic profiling coupled with medicinal chemistry were used to develop a small molecule with proliferative effects on retinal stem/progenitor cells, as assessed in vitro in a neurosphere assay and in vivo by measuring Msx1-positive ciliary body cell proliferation. The compound was identified as having kinase inhibitory activity and was subjected to cellular pathway analysis in non-retinal human primary cell systems. When tested in a disease-relevant murine model of adult retinal degeneration (MNU-induced retinal degeneration), we observed that four repeat intravitreal injections of the compound improved the thickness of the outer nuclear layer along with the regeneration of the visual function, as measured with ERG, visual acuity, and contrast sensitivity tests. This serves as a proof of concept for the use of a small molecule to promote endogenous regeneration in the eye.
Retinal Degeneration , Humans , Mice , Animals , Retinal Degeneration/metabolism , Methylnitrosourea , Retina/metabolism , Photoreceptor Cells , Regeneration , Disease Models, Animal , Mammals
In a novel series of DPP-IV inhibitors, a large increase of inhibitory activity was achieved by optimisation of aromatic substituents and conformational restriction.
Amines/chemistry , Dipeptidyl Peptidase 4/drug effects , Enzyme Inhibitors/chemical synthesis , Pyridines/chemical synthesis , Cells, Cultured , Diabetes Mellitus, Type 2/drug therapy , Dipeptidyl Peptidase 4/metabolism , Enzyme Inhibitors/metabolism , Enzyme Inhibitors/pharmacology , Hydrocarbons, Aromatic/chemistry , Hydrocarbons, Aromatic/pharmacology , Inhibitory Concentration 50 , Pyridines/metabolism , Pyridines/pharmacology , Structure-Activity Relationship
The goal of our work was to differentiate between patterns, which are responsible for the activity of small molecular ligands binding to G-protein coupled receptors (GPCRs) and molecules, which are pharmacologically active on other target classes. Second the aim was to go one step further and analyze the chemical space occupied by GPCR active ligands itself, to distinguish between the actives of different subclasses or even cluster ligands for single receptors. To achieve these objectives, we have built a database of small, organic molecules, which bind to GPCRs. Once this crucial foundation for pattern recognition has been laid, we needed to find a descriptor, which is able to detect the compulsory features responsible for activity within a molecule. In this matter we found that the well accepted pharmacophore descriptor served us well. Finally we needed to find a method to display the clustering or separation of the specific ligands. We found that self-organizing maps (SOMs) perform excellently in this task. We herein present the analysis of the chemical space of active compounds, depending on their biological target, the GPCRs. We will also discuss the techniques used to create the chemical spaces. The findings can be applied and have an impact at various stages of the drug discovery process.
Receptors, G-Protein-Coupled/chemistry , Ligands , Pattern Recognition, Automated
