Computational Design and Anti-Inflammatory Assessment of Novel 1,3,4-Oxadiazole Derivatives

Drug discovery aims at identifying a compound therapeutically useful in treating and curing a disease. Normally the drug discovery process starts with a biological target that has been shown to play a role in the development of the disease or begins from a molecule with interesting biological activities. The drug discovery process involves the identification of candidates, synthesis, characterization, screening, and assays for therapeutic efficacy. Once a compound has shown its value in these tests, it will begin the process of drug development prior to clinical trials. Drug discovery involves the combination of many disciplines and interests starting from a simple process of identifying an active compound.

Fig.1. General process of drug discovery

Fig.2. 2D Structure Of 1,3,4-Oxadiazole

When cells are damaged, the body's defense mechanism, inflammation, causes immune cells to proliferate in an attempt to eradicate the stimulus. Prolonged inflammation, however, is harmful and can result in a variety of pathological conditions, including cancer, atherosclerosis, arthritis, and neurological diseases. Phospholipase A2 activation initiates the inflammatory response by causing the lipid bilayer of the cell membrane to release arachidonic acid (AA). Cyclooxygenase enzymes (COX-1 and COX-2) quickly break down AA into prostaglandin H2 (PGH2), which is then transformed into eicosanoids like prostaglandin (PG), prostacyclin (PGI2), and thromboxanes (TXA2). These eicosanoids control the production of inflammatory cytokines and the emergence of common inflammation symptoms like fever, redness, swelling, and pain. 1,3,4- oxadiazole have been found to exhibit potential anti-inflammatory activity. So novel drugs needs to be developed to overcome the treatment failures.^{[9][10][11][12][13]} In this study, we have designed and evaluated a series of new 1,3,4-Oxadiazole derivatives of  3-[(substituted)methyl]-5- [(1H- imidazole-1-yl)4-methyl] -1,3,4-oxadiazole -2(3H)- thione ,in search of potent anti-inflammatory agents through In-silico studies.

Scheme Of Work ^[14]

MATERIALS AND METHODS

ACD Lab Chemsketch

ACD/ChemSketch is a molecular modeling application that allows users to create and edit chemical structure images. It also has capabilities like molecular property calculations (e.g., molecular weight, density, molar refractivity, etc.), cleaning and viewing of 2D and 3D structures, naming structures (less than 50 atoms and 3 rings), and logP prediction. Using ACD Labs Chemsketch version 12.0, the compounds' chemical structures and SMILES notations were acquired.^[16]

ACD/ChemSketch has the following major capabilities:  

· Structure Mode for drawing chemical structures and calculating their properties.

· Draw Mode for text and graphics processing.

· Molecular Properties calculations for automatic estimation of formula weight, percentage composition, molar refractivity, molar volume, parachor, surface tension, density, dielectric constant, polarizability

Molinspiration

Molinspiration is an independent research organization focused on development and application of modern cheminformatics techniques, especially in connection with the internet. It offers broad range of cheminformatics software tools supporting molecule manipulation and processing, including SMILES and SD file conversion, normalization of molecules, generation of tautomers, molecule fragmentation, calculation of various molecular properties needed in QSAR, molecular modelling and drug design, high quality molecule depiction, molecular database tools supporting substructure search or similarity and pharmacophore similarity search. SMILES notations of the selected derivatives were fed in the online Molinspiration software (https://www.molinspiration.com/) to predict the drug likeness properties. Lipinski’s rule of five is used in drug design and development to predict oral bioavailability of potential lead or drug molecules. Lipinski rule is also known as Pfizers rule of five / Lipinski’s rule of 5. The rule was formulated by the scientist Christopher A Lipinski. The Lipinski rule of five states that an orally active drug should obey the following criteria: 1. Not more than five hydrogen bond donors 2. Not more than 10 hydrogen bond acceptors 3. Molecular weight less than 500 Daltons 4. An octanol-water partition coefficient log P not greater than 5 5. Not more than 5 rotatable bonds.^[17]

PASS (Prediction of Activity Spectra for Substances)

 PASS is a program used for calculating sample sizes or determining the statistical power of a test or confidence interval in research studies. NCSS LLC is the company that produces PASS. It is a comprehensive software package with over 290 documented sample size and power procedures. It’s widely recognized as the leading tool for determining sample sizes in various fields such as clinical trials, pharmaceuticals, and medical research. Inputting the structural formula of a drug-like substance into specialized software can provide an estimated biological activity profile as an output.

Protein Data Bank

The Protein Data Bank (PDB) is a online database that stores three-dimensional structural data of large biological molecules, including proteins and nucleic acid. This data is gathered using techniques like X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy.  Scientists worldwide contribute to the database, and the information is freely accessible through member organization websites like PDBe, PDBj, RCSB and BMRB. The Protein Data Bank (PDB)is overseen by the Worldwide Protein Bank(wwPDB), an organization responsible for managing and maintaining the database. The PDB plays a crucial role in structural biology, particularly in areas like structural genomics. Many top scientific journals and funding agencies now mandate scientists to submit their structural data to the Protein Data Bank (PDB).^[18][19][20]

Protein preparation

The typical structure file from the PDB may require preprocessing before it can be readily utilized in molecular modelling calculations. It consists of only heavy atoms and may include a co-crystallized ligand, water molecules, metal ions, activators, cofactors and several protein subunits. According to the requirement protein is pre-processed, optimized and minimized with forcefield. Optimization involves water removal and minimization. The protein structure was refined. The ionization structure and most stable were chosen.

Ligand preparation

Ligand preparation involved energy of the ligands. Ligprep [Schriinger, 2010] facilitated this process by adding hydrogen, converting 2D structures to 3D, generating stereoisomers, and optionally neutralizing charged structures or determining the most probable ionization state at a user-defined PH. All the structures were ionized at a neutral pH of 7. Conformers for each ligand were generated using Conf Gen, applying the OPLS-2005 force field method.

Docking

Molecular docking is a structure-based computational method that generates the binding mode and affinity between ligands and targets by predicting their interactions [18, 19]. There are several docking tools used for this purpose. AutoDock, AutoDock Vina, GOLD, Glide, MOE, ICM, and FlexX are amongst the popular software in use. Molecular docking has various applications in the drug discovery and design process. In the early years of its application, it was mainly used to investigate the molecular interactions between ligands and targets. ^[21][22]

AutoDock

AutoDock comprises 3 C programs, AutoTors, responsible for refining ligand input, AutoGrid, which calculates interaction energies using macromolecular coordinates, and AutoDock itself, tasked with the actual docking process. AutoDock effectively reproduces ligand positions by considering six spatial degrees of freedom-rotation and translation. It accurately captures crystallographically determined positions for ligands with up to eight torsional degrees of freedom. It’s simulated annealing search may struggle to adequately explore conformational space for molecules with a high number of degrees of freedom, potentially limiting its applicability in certain cases. ^[23][24]

RESULT AND DISCUSSION

Fifty analogues of 1,3,4-Oxadiazole derivatives were designed using ACD Lab Chemsketch 12.0. Initially the designed fifty analogues were subjected to Lipinski rule analysis using molinspiration software.

Theoretical determination of drug-likeness properties

We predicted the drug likeliness profile of the compounds through analysis of pharmacokinetic properties of the compounds by using molinspiration online software. Based on the results obtained from molinspiration it was observed that all of the proposed compounds obeyed Lipinski rule of five. According to the Lipinski’s rule of five new molecule designed for oral route should have a MW < 500, log P o/w < 5, No more than 5 hydrogen bond donors and No more than 10 hydrogen bond acceptor. From the Lipinski rule analysis, all the 50 compounds were selected for further studies, since the compound did not show any violations from the Lipinski rule of five. Structure of proposed 1,3,4- oxadiazole derivatives of 3-[(substituted)methyl]-5- [(1H- imidazole-1-yl)4-methyl] -1,3,4-oxadiazole -2(3H)- thione is shown in Figure 3.

Figure 3: Designed Ligand

The results of Lipinski rule analysis of first 50 compounds are shown in the table 1.

Table 1: Lipinski Rule Analysis of Proposed Derivatives

The PASS software predicts the biological activity of proposed derivatives where Pa indicates probability to be active and Pi indicates probability to be inactive. The PASS value of proposed derivatives were shown in table 2.

Table 2: PASS of designed 50 compounds

From the docking result of 50 derivatives 25 derivatives which shows high and similar docking score than standard drug is shown in the table.

Protein: cox-2

Figure 7: 3D Struture of cox-2

ompound a₁

Among the 25 derivatives docked images of 13 derivatives were shown below.

Table 4: Docked images of 13 compounds showing high score

SUMMARY AND CONCLUSION