A First Attempt to Identify Repurposable Drugs for Type 2 Diabetes: 3D-Similarity Search and Molecular Docking

: Drug repositioning involves the investigation of existing drugs for new therapeutic pur-poses, such as type 2 diabetes. This disease affects the health and quality of life for individuals around the world. Sitagliptin, a highly selective dipeptidyl peptidase-4 (DPP-4) inhibitor, is used to treat type 2 diabetes mellitus by effective fasting and improved glycemic control. Despite this ad-vantage, serious hypersensitivity reactions have been acknowledged for patients receiving sitagliptin. In this context, it is necessary to develop new drugs with enhanced profiles and targeting DPP-4. a query in a 3D-similarity search on the approved DrugBank. Based on the TanimotoCombo parameter, the first 10 approved DrugBank drugs were docked in the 4FFW active site to identify effective antidiabetic effects for possible repurposable drugs marketed with other indications.


Introduction
Diabetes mellitus type 2 (T2DM) is a progressive chronic disease that affects more than 425 million people worldwide [1]. Of the two types of diabetes, T2DM accounts for around 90% of cases. T2DM is characterized by persistent hyperglycemia derived from insulin deficiency and insulin resistance [2]. Chronic hyperglycemia is associated with harmful microvascular and macrovascular difficulties, such as retinopathy, nephropathy, and coronary artery illness [3].
The dipeptidyl peptidase 4 (DPP-4) proteolytic enzyme related to the pathophysiology of T2DM is expressed on the surface of most cell types, and is connected with signal transduction, immune regulation, and apoptosis. Moreover, it is responsible for the degradation of two incretins hormones-glucagon-like peptide 1 (GLP-1) and glucose-dependent-insulinotropic polypeptide (GIP) [4,5]. These two hormones are culpable for improving insulin production and release. DPP-4 catalyzes the N-terminal dipeptides of glucagon-like peptide 1 (GLP-1), which plays a pivotal role in blood glucose level regulation. In this context, the inhibition of DPP-4 and the design of appropriate DPP-4 inhibitors have been considered an essential strategy for T2DM treatment [6,7]. The newly launched DPP-4 inhibitors, in addition to the recognized antihyperglycemic and pancreatic effects, showed new cardiovascular protections and anti-inflammatory effects.
Our work aims to identify new repurposable drugs, from the approved DrugBank database, as DPP-4 inhibitors with potential antidiabetic activity. To reach this goal, Rapid Overlay of Chemical Structures (ROCS), together with molecular docking, has been applied. Sitagliptin was used as a query in a 3D-similarity search on the approved Drug-Bank, resulting in the prioritization of ten compounds with a TanimotoCombo score between 0.995-1.2. Further, the relationship between binding interactions of the top ten prioritized ROCS compounds with key amino acids of DPP-4 active site and their inhibitory capacities were investigated.

Dataset
The 2454 compounds downloaded from the approved DrugBank database [11] were prepared for ROCS analysis and docking simulation with the aid of LigPrep [12] by generating their ionization states and tautomers at pH = 7.2 ± 0.2. The conformers of each ligand and Sitagliptin were generated with Omega, OpenEye, Sanata Fe, NM, USA [13][14][15] using default settings. The generated Omega conformers were used as input for ROCS analysis and molecular docking. Drug Sitagliptin ( Figure 1) was employed as a reference molecule for both processes.

Protein Preparation
The X-ray structure of the DPP-4 receptor, co-crystallized with Sitagliptin (PDB ID: 4FFW) [16] and downloaded from PDB, was prepared for docking by generating the active site box of 5956 Å 3 and two inner/outer contours of 81 Å 3 /557 Å 3 , respectively, using the MakeReceptor facility, OpenEye [17]. The water molecules that exceeded 5 Å from the co-crystallized ligand were deleted and only the significant ones were kept. In the absence of any constraints, the default parameters were engaged.

Molecular Docking
Docking analysis of ten prioritized compounds into the active site of the DPP-4 receptor was achieved by Fast Rigid Exhaustive Docking (FRED), Openeye [21]. During the docking process, the ligands and the receptor were treated as rigid structures. Furthermore, ten docking poses were retained for each ligand. The Chemgauss 4 (CG4) score [22][23][24] was used to score ligand poses biding into the 4FFW active site. The best ligand binding conformations were picked based on binding orientation, interactions with key binding site residues, and CG4 score values. To evaluate docking performance, the co-crystallized ligand Sitagliptin was redocked into the DPP-4 active site and the RMSD (root-mean-square deviation) was measured between docked conformations and its pose in X-ray crystal.

Pharmacokinetic Profile
The pharmacokinetics (absorption, distribution, metabolism, and excretion) properties of the prioritized DrugBank drugs were estimated using a free web-tool, SwissAdme (http://www.swissadme.ch) (accesed on 2 September 2020) [25]. Also, the BOILED-Egg, iLOGP, and Bioavailability Radar are available to be estimated with SwissAdme. The BOILED-Egg model predicts two key parameters of a molecule-passive human gastrointestinal absorption (HIA) and blood-brain barrier (BBB) permeation.

Results and Discussion
Molecular similarity is a fundamental concept widely used in the early stages of drug development to design new molecules. 3D-shape similarity is a method of choice in virtual screening campaigns, and a crucial factor for small molecules activity. In this regard, the 3D-shape similarity between query Sitagliptin and DrugBank database molecules was realized. The similarity between these shape representations was estimated by computing various similarity metrics. Analysis in Figure 2 indicates that the top ten prioritized approved drugs arrange more systematically on the query molecule, showing slight structural variability concentrated on the triazolopyrazine unit of Sitagliptin. 3D-similarity coefficients based on shape, color, and a combination of these two are listed in Table 1. One (TanimotoCombo) out of six coefficients were used to assist the prioritization of the approved DrugBank drugs (Figure 3). Approved drugs with coefficient values greater than 1 for TanimotoCombo were discussed in detail (Table 1, Figure 3).
The interactions performed by these four inhibitors are consistent with the features required by a DPP-4 inhibitor.
These four DrugBank compounds selected after the docking process include drugs used to treat several health issues, which are as follows: (i) DB09195 (Lorpiprazole) is used for major depressive disorder treatment; (ii) DB09089 (Trimebutine) is marketed for irritable bowel syndrome (IBS) and lower gastrointestinal tract motility disorders treatments; (iii) DB00298 (Dapiprazole) is used to decrease the size of pupils after an eye examination; and iv) DB13858 (Dimazole) is an antifungal used to treat tinea infections.
Analyzing the SwissADME properties [25], passive gastrointestinal absorption (HIA) and brain permeability (BBB) indicate that all four approved drugs passively permeate the BBB (yellow region), while only one compound, DB13858, cannot be effluated from the CNS (red dot) (Figure 7).  The four molecules (DB09195, DB09089, DB00298, and DB13858) plotted in the yellow ellipse have a high probability of a good BBB crossing, while the other four molecules (DB00447, DB00567, DB01333, and DB00833) situated in the white ellipse have a high probability of good HIA. The blue dots suggest molecules predicted as a substrate of Pglycoprotein (PGP+), while the red dots show molecules predicted as a non-substrate of P-glycoprotein (PGP−). In the yellow ellipse, DB09195 and DB09089 drugs are placed closely to reference molecule Sitagliptin. Two compounds, DB01150 and DB01060, are located in the grey area, and are predicted to be unabsorbed by GI and BBB non-permeable.

Conclusions
The present work successfully applied 3D-similarity search, molecular docking, and pharmacokinetics estimation approaches to identify and optimize old drugs for new uses, such as T2DM therapy. The ten approved drugs prioritized by similarity search were docked in the active site of the DPP4 receptor. The SwissADME parameters, passive gastrointestinal absorption (HIA), and brain permeability (BBB) indicate that approved drugs passively permeate the BBB (yellow region-DB09195, DB09089, DB00298, DB13858), while only DB13858 cannot be effluated from the CNS (red dot). Four out of ten approved DrugBank compounds, DB09195, DB09089, DB00298, and DB13858, showed excellent pharmacokinetic profiles and specific interactions with the DPP-4 binding site, which recommends them as possible DPP-4 inhibitors and candidates in the treatment of diabetes.
Author Contributions: D.I. and A.B. designed the computational framework of the study, analyzed resulted data, and edited the manuscript; L.C. performed the computational studies and edited the manuscript. All authors discussed the outcomes, contributed to the writing of the paper, and commented on the paper. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.