Docking Predictions of IMiDs on Cereblon

Assessments of prospective docking pockets and docking predictions for S enantiomeric forms of TFBP, TFNBP and thalidomide-like drugs on the structure of cereblon were investigated using automated software [49 (link)]. This was followed by a cavity-based blind drug docking prediction utility [50 (link)] to appraise the characteristics of the computed drug docking predictions of these IMiDs. The drug docking pockets and the binding differences between TFBP, TFNBP, thalidomide and pomalidomide in cereblon were determined for the best scoring attributes of these chemical agents. In short, the crystal structure of human cereblon in complex with DDB1 and lenalidomide (4TZ4: https://www.rcsb.org/structure/4TZ4) was downloaded in PDB format from the PDB database. The chain C (human cereblon) was separated from the remainder of the crystal structure complex and was utilized in docking predictions for the S enantiomeric forms of the study compounds. The S enantiomer was chosen as former x-ray crystallographic studies have reported that this enantiomer of thalidomide-like IMiDs better binds cereblon [51 (link)], notwithstanding that molecular modelling computational data does not necessarily simulate or fall in line with all experimental data from prior x-ray crystallographic studies [52 (link)]. Playmolecule, an automated server that employs a software DeepSite [48 (link), 49 (link)] to establish the core binding sites, was used to simulate potential interactions between TFBP, TFNBP or thalidomide-like compounds with human cereblon. An automated docking software [53 (link)] was used to investigate potential similarities and differences in the pharmacophore pocket engaged by the test drugs. Briefly, two files were uploaded that included the C-chain (human cereblon) of the PDB ID 4TZ4 without lenalidomide and damaged DNA binding protein 1 (DDB1) and the drugs individually in their PDB formats to the Docking server [53 (link)]. For docking pocket predictions, the results appear as the number of preferential pockets determined with their relevant scores. Results of docking were collected with individual Vina scores, cavity sizes, docking centers, poses and sizes of predicted cavities for the drugs noted above. The resulting drug-cereblon complexes were visualized using the drug discovery studio visualizer software BIOVIA [49 (link)].