In-silico approach towards thiophene incorporated 1,3-oxazepine using 5-HTT and 5-HT2AR receptors for antidepressant activity

Depression is a medical condition that affects a person’s mood and can be serious if it persists for a long time and is accompanied by other symptoms. The serotonin receptor family includes Serotonin transporter (or 5-HTT) and 5-HT2A, which are involved in the transportation of serotonin across the synaptic cleft. Schrödinger software was used to study how well novel thiophene-incorporated oxazepines could bind to these receptors. The ligand molecules TOB3, TOB13, and TOA13 had better docking scores against the protein 5-HTT than the standard Imipramine, while the docking scores of other compounds varied. The ligand TOA11 also had a good score against the 5-HT2AR protein. The results were validated using binding free energy analysis, pharmacophore modeling, and molecular dynamic simulation studies used to identify potent molecules for further study. Absorption, distribution, metabolism, excretion, and toxicity and physicochemical parameters were also predicted, and drug-likeness was evaluated. This study could aid in the development of potent inhibitors of 5-HTT and 5-HT2AR for the treatment of depression

Using ChemDraw 20.1.1 application, the 2D structures as given in Table 10 and Canonical SMILES of the ligand compounds were obtained which were converted into 3D images using the Ligprep module on the Schrödinger.The imported ligands were energy minimized.The proteins 5-HT2AR (PDB ID: 6WGT) and 5-HTT (PDB ID: 7LIA) obtained from the protein data bank (https://www.rcsb.org/)were preprocessed, refined, optimized, and minimized using the protein preparation wizard of Schrödinger.The protein's active site was identified and a grid was generated using the Grid Generation module.Finally, using Glide extra precision scoring tools, the protein and ligands were docked.The docking scores were compared with a standard antidepressant drug Imipramine (Dwivedi et al., 2021;Kalirajan et al., 2019;Mathew et al., 2014).

Prime molecular mechanics-generalized born surface area (MM-GBSA) binding free energy
The MM-GBSA method was employed to calculate the binding energy of the receptor-ligand complex.By taking into account the solvation model for polar and non-polar solvation as well as molecular mechanics energies, Schrodinger's Prime module determined the ΔGbind in kcal/mol (Genheden and Ryde, 2015;Wang et al., 2019).

Pharmacophore modeling
Using the phase module of Schrödinger, pharmacophore models of top-score compounds were generated.Multiple ligand method was used for the same.In reference to virtual screening on huge chemical databases, the term "pharmacophore" refers to a collection of steric and electronic characteristics that validate the best supramolecular interactions.It describes the 3D configurations of functional groups necessary for biological action.It is a more effective and potent method for finding compounds that may be used to either stimulate or inhibit macromolecular activity.

Absorption, distribution, metabolism, excretion, and toxicity (ADMET) and physicochemical properties
Using the QikProp module of Schrödinger, the ADMET and physicochemical parameters of the ligand molecules were predicted.Validation of the rule of five was also carried out using the QikProp module (Duffy and Jorgensen, 2000;QikProp User Manual, n.d.).Absorption, distribution, metabolism, and excretion (ADME) of the administered molecule play an important role in the bioactivity of a molecule.Lipinski's rule of five helps in predicting the oral bioavailability of any molecule.

Molecular dynamic (MD) simulation
The MD Simulations were conducted using Gromacs version 2023.1.To prepare the protein topology, the charmm27 all-atom forcefield was employed with the pdb2gmx module of Gromacs.The proteins were immersed in a dodecahedron box with dimensions of 1 nm in all directions, using a 3-point water model for solvation.Sodium (Na + ) and Chloride (Cl − ) ions were added as counter ions to neutralize the system.The sexual functionality, drug interactions, and drug-induced QT prolongation.Due to the frequent dose schedule, it is also discovered that drug adherence is a significant issue.This encourages the development of novel therapeutics with reduced toxicity and enhanced activity (Cascade et al., 2009;Kelly et al., 2008).
Serotonin reuptake is the process by which the neurotransmitter serotonin is transported from the synaptic cleft back to the presynaptic neuron by the serotonin transporter (SERT or 5-HTT), which stops the action of serotonin and recycles it in a sodium-dependent manner.Many SSRIs and tricyclic antidepressants, and other antidepressants reduce serotonin reuptake via binding to SERT (Bank, n.d.;Owens and Nemeroff, 1994;Squire, 2008).5-HT 2A is another such receptor belonging to the serotonin receptor family which is known to be involved in the action of several antipsychotic medicines mainly in the management of bipolar disorders and mood stabilization.Patients who attempted suicide or were depressed had elevated 5-HT2A receptors than healthy individuals.These findings imply that the pathophysiology of depression involves post-synaptic 5-HT2A over-density.SSRIs and atypical antipsychotics are known to follow the mechanism that causes chronic downregulation of the post-synaptic 5-HT2A receptor (Bank, n.d.;Eison and Mullins, 1995;Martin et al., 1998).
Naturally occurring heterocyclic compounds are actively being researched for their potential role in the development of innovative therapeutic agents in the current era of developing diseases.Among a large group of these heterocyclic compounds, thiophene and oxazepines are the classes of molecules that caught the attention of medicinal chemists, leading to the development of their vast therapeutic value as an anti-inflammatory, antipsychotic, analgesic, and antimicrobial agents.(Berrade et al., 2011;Gibbs et al., 1976;Shah and Verma, 2018;Sharma et al., 2008;Wardakhan et al., 2008) resulting in encouraging findings that spur the creation of new therapeutic compounds.
Many tricyclic antidepressant medications, including Amoxapine, Sintamil, and others, contain the heterocyclic nucleus oxazepine, and Duloxetine, an SSNRI used to treat depression and anxiety, contains a thiophene nucleus, demonstrating the possibility of the same being an effective treatment for depression and anxiety.Several studies present the possible activity of the thiophene molecule as an antidepressant agent which sparked the notion of creating a single hybrid molecule containing both of these moieties and evaluating their biological activity.

In silico platform
Using Maestro 12.3 version programmed on DELL Inc.27" workstation on Intel Core i7-7700 CPU@ 3.60 GHz ×8 processor with 1,000 GB hard disk and 8 GB RAM, all the in-silico analysis was performed.The operating system used was Linux -×86_64.(Schrödinger | Schrödinger is the scientific leader in developing state-of-the-art chemical simulation software for use in pharmaceutical, biotechnology, and materials research., n.d.) energy minimization process utilized the steepest descent integrator and a verlet cutoff scheme for a maximum of 50,000 steps, aiming to achieve the lowest energy confirmation.The system was then equilibrated for 100 picoseconds using Canonical [constant number (N), constant volume (V), and constant temperature (T)] and Isobaric [constant number (N), constant pressure (P), constant temperature (T)] ensembles.The thermostat V-rescale was employed to maintain a constant temperature of 300 K, while the C-rescale pressure-coupling algorithm was used to maintain a constant pressure of 1 bar.For long-range electrostatics, coulomb, and van der Waals calculations, the Particle Mesh Ewald method was applied with a cutoff of 1.2 nm.The LINCS algorithm was utilized to constrain bond lengths.The MD run was conducted for 100 ns, with coordinates and energies saved at every 10 picoseconds.The resulting trajectories were analyzed using the built-in utilities provided by Gromacs.After the MD run, various parameters including root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (RoG), and solvent accessible surface area (SASA) were evaluated.Additionally, the University of California, San Francisco Chimera Visualizer was employed to visualize the complex at the beginning and end of the MD run (Dwivedi et al., 2021;Kalirajan et al., 2019;Mathew et al., 2014).

Molecular docking
The ligand molecules TOB3, TOB13, and TOA13 with docking scores −5.381, −4.944, and −4.883 kcal/mol, respectively, docked against the protein 5-HTT exhibited better scores than the standard Imipramine (−4.721 kcal/mol).The docking scores of other compounds ranged from −2.00 to −4.383.On the other hand, the 5-HT2AR inhibitory activity of the ligands extended from −1.696 to −4.051.The compound TOA11 exhibited an appreciable score (−4.051 kcal/mol) compared to the standard Imipramine (−4.199 kcal/mol).The van der Waals energy, coulomb energy, docking energy, and the interactions of each ligand with functional residues of the proteins are given in Tables 1-4 and Figures 1-4.

Binding free energy calculation
The docking results were validated using binding free energy analysis of the protein-ligand complexes.The ΔGbind of the protein 7LIA complexed with different ligands was in the range of −11.58 to −56.39 kcal/mol, whereas the complexes with the protein 6WGT ranged from −31.06 to −57.75 kcal/mol (Tables 5 and 6).

Pharmacophore modeling
To identify the chemical features of the bestinteracted molecules TOB3 (with the protein 7LIA) and TOA11 (with the protein 6WGT) that are responsible for the interaction with the active site of the protein, pharmacophore modeling was employed (Fig. 5).Acceptors (A4, A2, A5), aromatic ring (R11), and hydrophobic interactions (H8) were found to contribute to the interaction in the case of molecule TOB3.Whereas acceptor (A3), donor (D6), aromatic rings (R8, R9), and hydrophobic interaction (H7) were the attributes and negative interactions, respectively, while docked against the 5-HTT protein.The ligand TOB13 was observed to exhibit hydrophobic interactions with Ile108, Ala331, Phe335, Pro499, Phe556, Leu563, Pro561, polar interactions with Gln332, Thr497, Ser555, Ser559, Gln562; positive and negative interactions with     have a high percentage of human oral absorption.The predicted apparent Caco-2 cell permeability of the compounds was found to be moderate ranging from 42.011 (TOB2) to 477.045 nm/ second (TOB3).It was also observed that the molecules could moderately bind to the protein human serum albumin.The compounds' predicted brain/blood partition coefficient was also within the recommended range of −3 to 1.2.The compounds TOA1, TOA2, TOA11, TOA12, TOA13, TOB1, TOB2, TOB10, TOB11, TOB12, and TOB13 were predicted to be CNS inactive whereas the molecules TOA6, TOA7, TOB3, TOB4, TOB5, TOB6, and TOB7 were found to be moderately active.
The predicted number of likely metabolic reactions of all the compounds was also found to be within the prescribed range (Table 7).

Predicted solvent-accessible surface area
A biomolecule's surface area accessible to the solvent is termed SASA and has a recommended range from 300 to 1,000.All the ligand molecules involved in the study were found to be within the prescribed limit.The molecules were also checked for FOSA (Hydrophobic component of SASA with a recommended range of 0-750), FISA (Hydrophilic component of SASA having a recommended range of 7.0-330), PISA (Pi component of SASA with a recommended range of 0-450), and total solvent-accessible volume in cubic angstroms using a probe with a 1.4 Å radius (Recommended range: 500-2000).It was observed that the compounds were within the suggested range (Table 8).

Table 1 .
Molecular docking scores of in silico potential compounds with protein 7LIA.

Table 2 .
Molecular docking scores of in silico potential compounds with protein 6WGT.

Table 3 .
Molecular docking interactions of in silico potential compounds with the protein 7LIA.

Table 4 .
Molecular docking interactions of in silico potential compounds with the protein 6WGT.

Table 5 .
Binding free energy calculation of in silico potential compounds with protein 7LIA.

Table 6 .
Binding free energy calculation of in silico potential compounds with protein 6WGT.