In silico study to predict potential precursors of human dipeptidyl peptidase-IV inhibitors from hazelnut.

Chinese hazelnut was chosen to become a probable precursor of biological active peptides via computer simulations in this article. There were a large number of bioactive peptides in Chinese hazelnut sequences according to analytical results from the BIOPEP database. The most prominent of these was the inhibitory peptide for dipeptidyl peptidase-IV (DPP-IV; EC 3.4.14.5), which can be used to treat type 2 diabetes, so the theoretical method to obtain DPP-IV inhibitory peptides by hydrolysis with a single or combination of enzymes was studied. Cytotoxicity analysis performed by ToxinPred showed that all of the DPP-IV inhibitory peptides generated from protein hydrolysis were not cytotoxic. Structural interaction fingerprint analysis revealed that Asp663 and Phe357 may be important residues for ligand binding. In order to further understand the inhibitory mechanism of peptide, VR with lowest half maximum inhibitory concentration (IC50) and IPI (inhibitors have been reported) were selected as ligand of DPP-IV to perform steered molecular dynamics simulations and PMF calculations. The results showed that P1 is the preferred (un)binding tunnel for the inhibitors obtained. Our findings help in the development of new DPP-IV inhibitors which were derived from common food.Communicated by Ramaswamy H. Sarma.

Random acceleration and steered molecular dynamics simulations reveal the (un)binding tunnels in adenosine deaminase and critical residues in tunnels.

Adenosine deaminase (ADA) is an important enzyme related to purine nucleoside metabolism in human serum and various tissues. Abnormal ADA levels are related to a wide variety of diseases such as rheumatoid arthritis, AIDS, anemia, lymphoma, and leukemia and ADA is considered as a useful target for various diseases. Currently, ADA can be divided into open conformation and closed conformation according to the inhibitors of binding. As a consequence, we chose two inhibitors, namely, 6-hydroxy-1,6-dihydro purine nucleoside (PRH) and N-[4,5-bis(4-hydroxyphenyl)-1,3-thiazol-2-yl]hexanamide (FRK) to bind to ADA in the closed conformation or open conformation respectively. In this study, we performed the random acceleration molecular dynamics (RAMD) method, steered molecular dynamics (SMD) simulations and adaptive basing force (ABF) simulation to explore the unbinding tunnels and tunnel characteristics of the two inhibitors in ADA. Our results showed that PRH and FRK escaped from ADA using three main tunnels (namely, T1, T2, and T3). Inhibitors (PRH and FRK) escape through T3 more frequently and more easily. The results from ABF simulations confirm that the free energy barrier in T1 or T2 is larger than that in T3 when inhibitors dissociate from the ADA and have potential mean of force (PMF) depth. Moreover, in the complexes (ADA-PRH, ADA-FRK), we also found that the most active residue that remarkably contributed to the binding affinity is W117 in T3, and the residue played an important role in the unbinding tunnel for inhibitor leaving. Our theoretical study provided insight into the ADA inhibitor passway mechanism and may be a clue for potent ADA inhibitor design.