Chemical space exploration with Molpher: Generating and assessing a glucocorticoid receptor ligand library

Small Molecule Libraries Receptors, Glucocorticoid chemical space glucocorticoid receptor molecular generation de novo design Humans 102004 Bioinformatik 102004 Bioinformatics Ligands 301207 Pharmazeutische Chemie 301207 Pharmaceutical chemistry
DOI: 10.1002/minf.202300316 Publication Date: 2024-07-09T11:24:00Z
ABSTRACT
AbstractComputational exploration of chemical space is crucial in modern cheminformatics research for accelerating the discovery of new biologically active compounds. In this study, we present a detailed analysis of the chemical library of potential glucocorticoid receptor (GR) ligands generated by the molecular generator, Molpher. To generate the targeted GR library and construct the classification models, structures from the ChEMBL database as well as from the internal IMG library, which was experimentally screened for biological activity in the primary luciferase reporter cell assay, were utilized. The composition of the targeted GR ligand library was compared with a reference library that randomly samples chemical space. A random forest model was used to determine the biological activity of ligands, incorporating its applicability domain using conformal prediction. It was demonstrated that the GR library is significantly enriched with GR ligands compared to the random library. Furthermore, a prospective analysis demonstrated that Molpher successfully designed compounds, which were subsequently experimentally confirmed to be active on the GR. A collection of 34 potential new GR ligands was also identified. Moreover, an important contribution of this study is the establishment of a comprehensive workflow for evaluating computationally generated ligands, particularly those with potential activity against targets that are challenging to dock.
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