In-silico Structure Modeling and Docking Studies Using Dipeptidyl Peptidase 4 (DPP4) Inhibitors against Diabetes Type-2

Abstract

Recently recognized class of oral hypoglycemic, dipeptidyl peptidase (DPP4) inhibitors could block the dipeptidyl peptidase 4 (DPP4) enzymes. DPP4 is an intrinsic membrane glycoprotein and a serine exopeptidase that plays a major role in glucose metabolism and responsible for the degradation of incretins such as GLP-1, therefore providing a useful treatment to diabetes mellitus type 2. The present work focused on the study of the structural homology modeling of dipeptidyl peptidase 4 [Homo sapiens] (NP_001926). The Ramachandran plot of DPP4 (NP_001926.2) has 88.9% residues in the most favoured region while template 2QT9 has 96.1% residues in the most favoured region. The model was validated by using protein structure tools RAMPAGE and Prochek for reliability. Docking studies were further performed to analyze the interaction mode between selected DPP4 inhibitor anagliptin derivative SKK and receptor DPP4 by using Hex 8.0.0. The in-silico analysis was useful to identify the novel inhibitor that illustrates better activity than the other reported inhibitors.

iDPPIV-SCM: A Sequence-Based Predictor for Identifying and Analyzing Dipeptidyl Peptidase IV (DPP-IV) Inhibitory Peptides Using a Scoring Card Method

“…Construction of a high-quality benchmark data set is the foundation for the development of a robust and reliable predictor. − In this study, the experimentally validated DPP-IV inhibitory peptides were extracted from the literature − ,, and publically available databases (i.e., BIOPEP-UWM), and these peptides were unique and considered as the positive data sets. Since there are very few experimentally proven non-DPP-IV inhibitory peptides, we employed random unique peptides without DPP-IV inhibitory activity and an equal number of positive data set from various literatures. ,, Here, we assigned these random peptides as the negative data sets.…”

“…Their results demonstrated that the physicochemical properties (i.e., molecular weight, bulkiness, and an increasing number of carbon and hydrogen atoms of amino acids forming the sequences) of the peptides play crucial roles in the bitterness of the peptides. Until now, several QSAR studies and methods have been made on this aspect. − ,, …”

“…Until now, several QSAR studies and methods have been made on this aspect. [11][12][13][14]17,18 To the best of the authors' knowledge, there exists no sequence-based ML predictor for predicting and analyzing the DPP-IV inhibitory peptides. In the present study, we propose a simple and easily interpretable sequence-based predictor for predicting and analyzing the DPP-IV inhibitory activities of the peptides using the scoring card method (SCM) that serves as the basis of the iDPPIV-SCM approach proposed herein.…”

Combined Effect of Vitamin C and E Dose on Type 2 Diabetes Patients

“…Pandit and Pandey [1]; Awasthi et al [2] proposed that diabetes mellitus is a multi-factorial metabolic disorder and forthcoming epidemic all over the globe that caused due to ineffective secretion of insulin. Prajapat and Bhattacharya [3]; Zhaolan et al [4] proposed that diabetic patient numbers will possibly rise up to 300 million by 2025 in India. Seyed Hosseini et al [5] and Rahman Hassan et al [6] also estimated that 346 million diabetic patients will be increase up to 439 million in 2030 worldwide.…”

Effect of Vitamin E and C Supplementation on Oxidative Stress in Diabetic Patients

“…Diabetes mellitus is metabolic epidemic that occur due to ineffective secretion of insulin from pancreas [1,2] and the possibly the worldwide number of diabetic patient will be rise up to 439 million by 2030 [3,4]. Vitamin E supplementation could improve glycemic control in diabetes patients [5,6].Vitamin C supplementation is effective in prevention of non-enzymatic glycosylation of proteins [7] and it also serves as therapeutic agent for diseases that protects body from damage caused by free radicals [8].…”