In Silico Design of Human IMPDH Inhibitors Using Pharmacophore Mapping and Molecular Docking Approaches

Abstract

Inosine 5′-monophosphate dehydrogenase (IMPDH) is one of the crucial enzymes in the de novo biosynthesis of guanosine nucleotides. It has served as an attractive target in immunosuppressive, anticancer, antiviral, and antiparasitic therapeutic strategies. In this study, pharmacophore mapping and molecular docking approaches were employed to discover novel Homo sapiens IMPDH (hIMPDH) inhibitors. The Güner-Henry (GH) scoring method was used to evaluate the quality of generated pharmacophore hypotheses. One of the generated pharmacophore hypotheses was found to possess a GH score of 0.67. Ten potential compounds were selected from the ZINC database using a pharmacophore mapping approach and docked into the IMPDH active site. We find two hits (i.e., ZINC02090792 and ZINC00048033) that match well the optimal pharmacophore features used in this investigation, and it is found that they form interactions with key residues of IMPDH. We propose that these two hits are lead compounds for the development of novel hIMPDH inhibitors.

Novel glitazones as PPARγ agonists: molecular design, synthesis, glucose uptake activity and 3D QSAR studies

“…The built QUERY was searched against a dataset of rationally designed glitazones (2234 glitazones), designed from different possible substituent combinations, keeping common structural scaffold intact. For validation of built pharmacophore model, the Güner-Henry (GH) [23] scoring method was adopted, where a decoy set of 1724 molecules were also screened against the built QUERY. Finally, the statistical parameters such as, %AD, %AE, %Y, E and GH were calculated.…”

In silico study of subtilisin-like protease 1 (SUB1) from different Plasmodium species in complex with peptidyl-difluorostatones and characterization of potent pan-SUB1 inhibitors

“…Next, we performed a preliminary in silico validation of our SUB1-PHA using a pharmacophore validation method based on the generation of decoys set, a procedure largely used to assess the ability of pharmacophore models to discriminate between active or inactive molecules [48] , [49] , [50] , [51] , [52] , [53] , [54] , [55] , [56] , [57] , [58] . Starting from compounds 1 and 2 (superposed to the SUB1-PHA in Fig.…”

In Silico Exploration of Novel Tubulin Inhibitors: A Combination of Docking and Molecular Dynamics Simulations, Pharmacophore Modeling, and Virtual Screening

“…The Güner–Henry (GH) scoring method quantifies the importance of the generated model by retrieving the active compounds from a database containing known active and inactive molecules [ 23 , 32 ]. To evaluate the discriminating ability of the generated pharmacophore model a testing set database including 20 known tubulin inhibitors with experimental activity and 600 inactive molecules was searched by the pharmacophore model as a 3D structural search query.…”

“…To create the most descriptive features of the colchicine binding site of tubulin, the Pharmacophore Query Editor of MOE was employed. These features are indicated as spheres that characterize the important interaction points of the ligand with the active site of tubulin [18,29] The Güner-Henry (GH) scoring method quantifies the importance of the generated model by retrieving the active compounds from a database containing known active and inactive molecules [23,32]. To evaluate the discriminating ability of the generated pharmacophore model a testing set database including 20 known tubulin inhibitors with experimental activity and 600 inactive molecules was searched by the pharmacophore model as a 3D structural search query.…”