Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes.

Human dual specificity mitogen-activated protein kinase kinase 4 (MAP2K4) is a direct activator of MAP kinases in response to various environmental stresses or mitogenic stimuli. Upon phosphorylation, MAP2K4 has been shown to activate MAPK8, MAPK9 and MAPK14/p38 but not MAPK1/ERK2 or MAPK3/ERK1. Over expression of MAP2K4 causes carcinogenic effects, such as ovarian cancer, colorectal cancer, prostate cancer and pancreatic cancer. Our present study was carried out to design a potent drug molecule against MAP2K4 to control over expression. As there is no experimentally determined structure for MAP2K4, the homology modeling technique of Modeller9v7 was implemented to generate a MAP2K4 3D model based on the co-crystal structure of MAP2K6 (PDB ID: 3FME) with staurosporine. Twenty such models obtained were accessed through DOPE score, PROCHECK, ProSA and the highly reliable model was further optimized for virtual screening in Maestro v9.0 applying OPLS2001 force field. MAP2K4 specific inhibitors such as staurosporine, genistein and cayanidin were selected and screened against one million entries of the Ligand.Info Meta-Database, to generate an in house library of 1151 analogs. LigPrep was used to generate multiple conformations of the in-house ligands. In an effort to ensure good ADMET properties of the selected ligands Lipinski filter and reactive filter was applied. The strategic computational docking using Glide v5.5 ranked 10 lead molecules with good binding affinity with MAP2K4. Among ten lead molecules Lead ‘1’, Lead ‘2’, Lead ‘3’ had higher binding affinity than the published inhibitors. The scores for Lead ‘1’ -8.75, Lead ‘2’ -8.54, Lead ‘3’ -7.96 and scores for published inhibitors are STAUROSPORINE: -6.55; GENISTEIN: -6.42 and CAYANIDINE: -6.24. So Lead ‘1’ with the lowest docking score (-8.75kcal/mol) is the best ligand for protein functional activity inhibition. Lead ‘1’ directly binds to the MAP2K4 protein by forming strong hydrogen bonds with LYS-131, LEU-180, LYS-231, ASP-229. So we can consider that the lead ‘1’ molecule can act as a potent inhibitor for MAP2K4.

Human CK2α2 is an enzyme that belongs to the Serine/Threonine protein kinase family which is involved in signal transduction. Over expression of CK2α2 causes kidney cancer therefore, human CK2α2 has been identified as a drug target for the development of potential antagonists against cancer therapy. The existing human CK2α2 inhibitors in clinical practice are having side effects like fatigue, diarrhea, nausea, anorexia and vomiting. High-throughput virtual screening is one of the most common method used to identify lead compounds was implemented in the present study to identify potential inhibitors of human CK2α2. The co-crystal structure of human CK2α2 was retrieved from the protein data bank. A 2D similarity search was performed for available five human CK2α2 inhibitors (Apigenin, VX680, Sunitinib, SUI4813 and CCK) taken from PDB and PubMed to acquire 1942 structural analogs. The 3D structural conversion and multiple confirmations for 1942 compounds were generated using LigPrep. The docking and scoring calculations were performed using Glide v5.7 which includes high throughput virtual screening (HTVS), Standard precision (SP) docking and extra precision (XP) docking. Obtained 39 leads were compared with docking scores of the existing inhibitors and proposed six leads having good binding affinity. The binding orientation of CK2α2-lead 1complex was correlating with native co-crystal structure. Hence, lead ‘1’ can be suggested as potent inhibitor against human CK2α2 involved in kidney cancer.

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