2,4-Thiazolidinedione Derivatives - Design, In - Silico Studies and Characterization as Anti - Convulsant Agents

Epilepsy is a chronic neurological disorder characterized by recurrent seizures due to excessive electrical discharges in the brain. It affects approximately 50 million people worldwide, making it one of the most prevalent neurological conditions. The World Health Organization (WHO) defines epilepsy as a noncommunicable disease that can significantly impact quality of life, with seizures varying from brief lapses of attention to severe convulsions ^[1]. Trauma, strokes, infections, or tumors can lead to the development of epileptic circuits. Certain genetic mutations can predispose individuals to epilepsy. Conditions such as autism are associated with higher rates of epilepsy ^[2]. Thiazolidinedione is a special five-membered heteroaryl ring structure that has two carbonyl groups next to nitrogen and nitrogen and sulphur atoms at positions N3 and C5, giving it a variety of actions and reactions. The ring system 2,4-thiazolidinedione (TZD) is a five-membered ring heterocycle such as thiazole which is further non-aromatically adorned with two carbonyl groups at positions 2 and 4.

Figure. No. 1. Structure and 3D conformer of 2,4-thiazolidinedione

2,4-thiazolidinedione (TZD) is a valuable and often used scaffold for creating molecules with pharmacological activity. A wide variety of pharmacological effects are conferred by this adaptable pharmacophore, which contains sulphur ^[3]. Anticonvulsants, also known as antiepileptic drugs (AEDs), are a diverse group of pharmacological agents used primarily to prevent and control seizures in individuals with epilepsy. These medications work by normalizing the electrical activity in the brain, thereby reducing the frequency and severity of seizures ^[4]. Glutamate receptors, particularly AMPA (?-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptors, play a crucial role in the pathophysiology of epilepsy. These ionotropic receptors are responsible for mediating fast excitatory neurotransmission in the central nervous system and are integral to the generation and propagation of epileptic seizures. AMPA receptors are activated by glutamate, the primary excitatory neurotransmitter in the brain. Upon activation, these receptors allow the influx of sodium ions (Na⁺⁺) into the postsynaptic neuron, leading to depolarization and the generation of excitatory postsynaptic potentials (EPSPs). The summation of EPSPs across a network of neurons can lead to synchronized firing, which is a hallmark of seizure activity ^[5]. The present work aims to design, synthesize, characterize 2,4-thiazolidinedione derivatives with the objective of overcoming the epilepsy.

MATERIALS AND METHODS

Selection of Target

The protein selected for the present study were Glutamate AMPA receptor which is used to restore excitatory–inhibitory balance, thereby reducing seizure frequency and severity. To verify and fix any missing hydrogen atoms, residues, or heavy atoms, the selected protein is input into the Protein Repair and Analysis Server (PRAS; https://www.protein-scen ce.com/) ^[6]. The description of target for the treatment of epilepsy was listed in table 1. The 3D crystal structure of Glutamate AMPA receptor was depicted in figure 2.  Recent researchers suggested Glutamate AMPA as a therapeutic potential target to treat epilepsy, which made us select the Glutamate AMPA as the protein target in this study.

Table. No. 1 : Description about target

       
           
       
    Figure. No. 2. The 3D crystal structure of Glutamate AMPA receptor

Active Site Prediction

Cavities for the target active sites are predicted using the CB-DOCK2 online service, which clusters the solvent-accessible surface. It is a cavity prediction method based on structure.Grid boxes can be customised by adjusting them to the centre, size, and volume forecasts of the cavity. By optimising molecular docking simulations, this customisation raises the precision of ligand-receptor interactions predictions ^[7].

Pharmacophore Identification

Pharmacophore modelling was done using the Pharmit server (http:// pharm it. csb. pitt. edu/), which made it simpler to create pharmacophores and compare them to a number of sizable chemical compound repositories, such as Zinc database, CHEMBL, and PubChem. The RCSB PDB - ID: 3R7X is entered into the website to identify the pharmacophore ^[8]. When constructing the ligands, the pharmacophore is taken into account.

Designing of Ligands and its Novelty Check

Using the concepts of molecular hybridisation and pharmacophore modelling, five newly developed ligands were docked in order to identify potential leads. The Chemsketch program (ACD Labs, version 2023.1.0) is used to draw the ligands, and they are stored in the.mol format for subsequent computational work^[9]. A study of chemical databases, including the Zinc 20 database and PubChem, confirms the originality of the developed ligands ^{[10] [11]}.

ADMET Prediction

During the drug discovery stages of drug design, the qualitative idea of “drug-likeness” is employed to explain how “druglike” an element is in relation to factors like bioavailability. Verifying that Lipinski’s rule of five is adhered to is a recognised technique for evaluating drug similarity ^[12]. SwissADME makes it possible to compute physiochemical descriptors and forecast ADME parameters. There are numerous methods for determining log p, such as p-glycoprotein substrate, topological approaches, fragment approaches, CYP450 inhibitors for pharmacokinetic predictions, and Lipinski’s rule computation ^[13]. An online program called Osiris Property Explorer can be used to examine a molecule's toxicity profile. It looks for harmful consequences such as mutagenicity, tumorigenicity, irritability, and reproductive toxicity ^[14].

Energy Minimization

The MM2 Force field is applied using the Chem3D ultra extreme software module (Perkin Elmer Informatics), and iterations are carried out until the minimised conformation is achieved. It involves minimising the ligand’s energy ^[15].

Docking Studies and Visualization of Interactions

Molecular docking is employed to identify the orientation and interaction between proteins and ligands. The Autodock Tools 1.5.6 program was utilised in the current work to predict the binding energy of ligands with Glu : AMPA Receptor. The UCSF Chimaera version 1.17.3 software and Biovia Discovery Studio (Dassault Systems, V21.1.0.20298) are used to visualise the interactions between the receptor and ligand ^{[16] [17] [18]}.

Synthetic Scheme

For the synthesis, the ligands with the best docking score and appropriate pharmacokinetic characteristics such as YG1, YG2, YG3, YG4, and YG5 are chosen. The Autodock version 1.5.6 software is used for the rescoring process in order to verify that the ligands are effective against the targets. The synthesis of the selected leads was carried out by the following scheme which was given in the figure 3

Figure. No. 3 Outline representation of scheme for the synthesis of ligands

Synthetic Methodology

Step 1: General Procedure for Synthesis of Thiazolidinedione

A solution of Chloro acetic acid (5.64g, 0.06 mol) in 6 ml of water is mixed with a solution of thiourea (4.56g, 0.06 mol) in 6 ml of water in a 100 ml RBF. The mixture is stirred for 15 minutes when a white solid separates. To this solid, 6ml of concentrated HCl is added slowly from a dropping funnel. The flask is connected to a reflux condenser and heated gently to produce a complete solution after which the reaction mixture is stirred and refluxed for 8-10 hours at 100-110°C. On cooling the contents of the flask, the cluster of colourless crystalline products is separated. The product is filtered, washed with water to remove traces of HCl, and dried. It is purified and recrystallized by hot water or ethanol. Completion of the compound is confirmed using TLC using Benzene(8ml): Methanol (2) (2:0.5) as solvent system ^[19].

Step 2: General Procedure for 5-(substituted benzylidene)-2,4-thiazolidinediones (Intermediate ?)

Substituted benzaldehyde (0.1 mol) was added to 2,4- thiazolidinedione (117 g/mol) (0.1 mol) in toluene 10 ml in the presence of piperidine few drops and refluxed at 110 ?C for 6–7 h and then poured into ice-cooled water to precipitate out the corresponding TZD derivatives. TLC (ethyl acetate: n-hexane, 6:4) was used to verify the improvement of the process ^[20].

Step 3: General Procedure for the Synthesis of Mannich Base-Derived Thiazolidinediones

Solution of Substituted thiazolidinedione derivative (Intermediate ?) (0.1M) in DMF or ethanol (10 ml), formaldehyde (0.2M) is added with stirring. The reaction mixture is stirred at room temperature for 30 minutes to complete the reaction of formaldehyde. The solution of secondary amine (0.05 in DMF or ethanol is added dropwise and refluxed for several hours (5 to 8 hours) to complete the reaction. It is then poured into ice-cold water filtered off and washed with hot water. Finally, recrystallized from chloroform, and ethanol to give the final compounds ^[21].

Characterization

The TLC technique used either the iodine chamber method or the UV chamber method to visualise the chemical reaction and assess its completion by using the proper solvent system. The Guna^TM melting point equipment was used to measure the melting temperatures of artificial compounds in open capillary tubes. Characterization of the synthesized compounds is done by using the UV spectra which was recorded using the Shimadzu UV 1900i with the aid of the Lab solutions software.

RESULT AND DISCUSSION

Active Site Prediction

The active site prediction details of the protein, are available in the Table 2

Table. No. 2 : Active site dimensions of the target protein

Virtual Library of Ligands

The pharmacophoric features for the target include the hydrogen bond acceptor, hydrogen bond donor and aromatic group. Pharmacophore model generated through the Pharmit server consists of the features depicted as follows; Hydrogen Bond Donor (HBD) in white colour; Hydrogen bond Acceptor (HBA) in orange colour and Aromatic group (AG) in violet colour which was represented in the figure 4

Figure. No. 4 : Pharmacophoric features of the target

Docking

The Ramachandran plot analysis results indicate that the selected protein, predominantly (more than 90%) have their amino-acid residues situated within the most favored region as represented in the figure 5. The ligands designed were designated with ligand code YG-1 to YG-5 and found that they obey the Lipinski’s rule of five with absence of toxicity. The designed ligands were docked against the targets Glu : AMPA receptor and the results are tabulated in the table 3 along with its binding interaction and 3D view

Figure. No. 5 : Ramachandran plot of selected protein

Table. No. 3 : Synthesized compounds binding scores and interaction with its 3D docking view

Characterization

The chosen five planned and optimised leads were purified by recrystallisation after being synthesised in accordance with the proper protocols. To verify the purity, TLC and the melting point were used. Table 4 lists the ligand’s structure and IUPAC name that were synthesised, and Table 5 describes their physical characteristics. The UV spectra was recorded for the synthesiszed compounds which was given in the figures  6, 7, 8, 9, 10 and its interpretation are tabulated in the table 6

Table. No. 4 : List of the compounds synthesizeddione

 Table. No. 5 : Physical properties of the synthesized compounds

Table. No. 6 : UV interpretation of synthesized compounds