Computational docking methods are used to screen various possible compounds, searching for new compounds with specific binding properties, or testing a range of modifications of an existing compound. Due to the rapid rise in the amount of molecular biological data available, the computer-aided analysis of molecular interactions becomes more realistic in addition to which as of now the computer prediction of the interaction between proteins and small molecules has advanced to the point that it allows accurate prediction of bound conformations and affinity.
Likewise, the binding of small molecule majorly organic compounds which are ligands to large protein targets is significant to both understanding biological processes and designing drugs . As many proteins regulate biological functions by interacting with small molecules, these receptor proteins are often the prime targets for therapeutic agents. Therefore, a detailed understanding of interactions between small molecules and proteins may form the basis for a rational drug-design strategy which is attractive in drug development concept due to two reasons: it may facilitate the development of more selective therapeutic agents with fewer undesirable side effects and will offer some hopes for reduction of the enormous costs and time required in traditional random screening protocols for drug discovery. Hence, by assuming the receptor structure is available in the PDB database, a major challenge in lead discovery and optimization is to predict both ligand orientation as well as binding affinity which could often be referred to as “molecular docking” [2,3].
Molecular docking has become an increasingly important tool for drug discovery and is the most widely employed technique whose goal is to predict the position and orientation of a ligand (a small molecule) when it is bound to a protein receptor or enzyme. The completion of the human genome project has resulted in broadening the scope of new therapeutic targets in drug design and discovery. Accordingly, the advancement in strategies such as excessive high-throughput protein purification, crystallography, and nuclear magnetic resonance (NMR) spectroscopy has been providing structural information of protein–ligand and protein complexes. This leads to the advancement which resulted in the development of computer-aided drug design, also known as molecular docking [4-5]. Molecular docking is a key tool in structural molecular biology and computer-assisted drug design which tries to predict the structure of the intermolecular complex formed between two or more constituent molecules, further trying to predict the position and orientation of a ligand when it is bound to a protein to know the predominant binding modes of a ligand with a protein of known three-dimensional structure. Simply this can be mentioned that docking is a method that predicts the preferred orientation of one molecule to a second when bound to each other to form a stable complex. Usually, these binding partners are biological macromolecules (e.g., protein, DNA/RNA, and peptide) or small molecules (e.g., endogenous ligands and drugs) and their preparations for the docking is just as important as the docking itself [6,7]. The computational approaches are currently being used for screening large databases of compounds to identify potential lead drug molecules. Hence, it can be mentioned that its main application lies in structure-based virtual screening for the identification of new active compounds towards a particular target protein . It can also be stated that for a selected set of structures of a protein and a ligand, the ultimate goal of all docking methods is to predict the structure of the resulting complex and the biological activity of a given ligand.
In this study, molecular docking is performed between receptor i.e. protein molecule and ligand i.e. the novel thiazolidin-4-one derivatives which were already synthesized by the authors. They are the novel thiazolidine-4-one derivatives of 3-ethyl-2-(2,4,5-trifluoro-phenylimino)-thiazolidin-4-onewhich belong to an important group of heterocyclic compounds containing sulphur, nitrogen, and carbonyl group in the 4th position in a five-member ring [9,10]. They are an important class of bioactive molecules with diverse biological activities, so it is often called “wonder nucleus”. Furthermore, thiazolidinone gives out various derivatives which attracted great attention due to the diversity of their biological effects  such as antidiarrheal , antimicrobial , antidiabetic [14,15], antiarrhythmic activity, anticancer [17-26], anti-HIV , Ca2+ channel blocker , cardioprotective , anti-ischemic , cyclooxygenasesinhibitory , and anti-platelet activating factor .
C-KIT, a receptor tyrosine kinase, is intricate in intracellular signalling, and the mutated form of C-KIT has important role in existence of some cancers. The role of C-KIT has directed to the thought that inhibiting c-Kit kinase activity can be a goal for cancer therapy . The encouraging results of inhibition of c-Kit for treatment of cancers have been detected in some cancers like gastrointestinal stromal tumour, acute myeloid leukemia, melanoma, and other tumours, and these results have stimulated attempts toward improvement of using c-Kit as a capable target for cancer therapy . The main procedure of handling the cancers is chemotherapy, in which anti-tumour compounds are administered to patients. This treatment is thought to be effective, particularly in the early stages of the disease, but it does not permanently cure the patient or totally extinguish cancer. Many factors are associated to the treatment catastrophe, among which we can remark the stage of the disease, the battle of tumour cells to the drugs, and the side effects of the action as the drugs used kill both the cancer cells and the normal cells, often becoming resistant to treatment . It is therefore important to develop effective anti-cancer therapeutic agents with well-defined pharmacokinetic properties.
Therefore, concerning the potentiality of thiazolidinone compounds and CKIT as potential target for cancer theory, we decided to conduct molecular docking against C-KIT Tyrosine kinase target protein (1T46) of the novel thiazolidine-4-one derivatives of 3-ethyl-2-(2,4,5-trifluoro-phenylimino)-thiazolidin-4-onewithvarious benzilidine groups attached to the five-membered imino-thiazolidinone ring.
In this study, the affinity and binding modes of the examined molecules against the target protein were determined. First, the water molecules were removed from the crystal structures of target proteins, retaining only main-chain amino acids which are essential for binding. The co-crystallized ligands were used as the reference ligands to predict the binding pockets (Figure 1) and later ligand was removed. Then, the polar hydrogen atoms were added to protein structures to protonate them. The structures of the examined compounds were drawn by using ChemDraw Ultra 7.0 and BIOVIA Discovery Studio Visualizer 2021 which were later saved by using PDB formats. Next, the saved files were opened by using MGL AutoDock Tools software where the protein preparation was done and selected as macromolecule then saved in PDBQT format. The configuration file was created which contained receptor name, ligand name, output file name, X, Y, and Z coordinates of the grid box, and also the size X, Y, and Z of the grid box. Then, the ligand was prepared and any rotatable bonds if available were added. Thereafter, the Command Prompt was opened and AutoDock Vina software was used for running the docking process for each target receptor by ligand by entering necessary codes or commands. In each case, 9 docked structural poses, affinity, and RMSD data were generated by using the algorithm. The output from the Vina split software was further analysed and visualized by using BIOVIA Discovery Studio Visualizer 2021.
Figure 1 depicts the structure of the protein 1T46 on which molecular docking of all 18 earlier synthesized compounds have been performed.
Figure 1. Proteins used for molecular docking - 1T46, C-KIT Tyrosine Kinase target protein
ADME study had been performed by using the Swiss ADME site (SwissADME). Primarily the structures were created with the help of ChemDraw Ultra 7.0 software and later uploaded on the Swiss ADME website to generate Smiles. These Smiles were used to generate ADME analysis data.
Results and Discussion
To visualize the interactions their 2D diagram and 3D interactions (color of bond interaction is justified in the table) of H-bonds, i.e. donor and acceptor are shown.
Table 1. Molecules and their characteristics
Figure 2. Molecular docking 3D interaction output of 3-Ethyl-5-(4-trifluoromethyl-benzylidene)-2-(2,4,5-trifluoro-phenylimino)-thiazolidin-4-one, 7 against 1T46
Figure 3. Molecular docking 2D interaction output of 3-Ethyl-5-(4-trifluoromethyl-benzylidene)-2-(2,4,5-trifluoro-phenylimino)-thiazolidin-4-one, 7 against 1T46
Table 2. Total Number of Favourable Interactions: 20
The structure of 3-Ethyl-5-(4-trifluoromethyl-benzylidene)-2-(2, 4, 5-trifluoro-phenylimino)-thiazolidin-4-one as a ligand has been subjected to molecular docking with a protein molecule that would act as a receptor. Docking results observed 9 poses out of which pose having the lowest affinity (kcal/mol) was selected as the best docking pose and was considered for the ligand interaction. Here, 20 favorable interactions were observed where the ligand has bonded at the chosen pocket site in the selected pose. The given table demonstrates the information about the bonds between the ligand and amino acids which contains bond distance, types of bonds, from where the bond is forming and their types. The ligand formed two hydrogen bonds [conventional hydrogen bond with fluorine], five halogen bonds [with fluorine], one electrostaticbond [pi-cation] and twelve hydrophobic interactions [pi-sigma,pi-pi T-shaped, alkyl and pi-alkyl].
The results of ADME studies of the 18 compounds have been depicted (Figure 4). Molecules with the absorption potential through the intestine appear in the white portion, while the absorbed molecules with the potential to cross the BBB barrier appear in the yellow portion. The study shows that molecules 1, 2, 8, 10, 11, 12, 13, 14, 15, 16, 17, and 18 are capable of being absorbed through the human intestine (HIA). Out of these 12 molecules only molecule 1 is observed to be capable of crossing the BBB barrier. This molecule demonstrates the good permeability potential across the BBB and has no substituents on the phenyl ring attached to the thiazolidin-4-one ring. Likewise, this molecule is demonstrated to follow all five rules of Lipinski’s Rule, with no violations of any rule.
Molecule 8 indicates the good potential to be able to cross the BBB barrier, due to the presence of two methyl groups attached to the amine’s nitrogen. The presence of heterocycles furan and pyrrole (as in molecules 16 and 17) are close to the potential molecules that could cross the BBB barrier, while the thiophene presence (as in molecule 18) decreases its potential to do so, probably due to larger size of sulphur, as compared with oxygen and nitrogen. The molecules 10, 11, 12, 13, 14, and 15 having methoxy and hydroxyl groups are the good candidates that could be absorbed by the intestine.
Molecules 5, 6, and 7 possessing –CF3 functionalities, and molecule 9 possessing phenoxy group and fluoro groupson the phenyl ring attached to the thiazolidin-4-one ring, show no potential for absorption through the intestinal lining. The presence of halogen atoms –Br and –Cl is indicated to hamper its potential for intestinal absorption, as observed in molecules 3 and 4. However, if only the –F group is present on the ring, the intestinal absorption improves and demonstrates more potential to cross the BBB barrier, as observed in the case of molecule 2.
Figure 4. ADME Boiled egg Diagram
Table 3. Physicochemical Properties
Table 4. Lipophilicity
Table 5. Water Solubility
Table 6. Pharmacokinetics
Table 7. Druglikeness
Table 8. Medicinal Chemistry
The synthesized thiazolidin-4-one derivatives have revealed the good interactions with the C-KIT Tyrosine Kinase (1T46) target protein, which indicates the good anti-viral potential of the molecules. The ADME studies show that groups like fluoro, hydroxyl, methyl, and methoxy demonstrate the good human intestinal absorption, which is not the case if chloro, bromo, and trifluoromethyl groups are attached to the heterocyclic ring. The in-silico methods can illustrate which functional groups in the molecules could aid in absorption in the body. This could give a proper direction to the synthetic organic chemist for synthesizing bio-active derivatives of thiazolidin-4-one.
Deepak S. Kadam: https://www.orcid.org/0000-0002-2639-3506
Sudhakar G. Patil: https://www.orcid.org/0000-0002-8036-7683
Denni Mammen: https://www.orcid.org/0000-0002-8115-302X
Shreyash D. Kadam: https://www.orcid.org/0000-0003-4213-4165
Citation: D.S. Kadam*, S.G. Patil, D. Mammen, S.D. Kadam, V.S. More*. In Silico Molecular Docking Againstc-KIT Tyrosine Kinase and ADME Studies of 4-Thiazolidinone Derivatives. J. Appl. Organomet. Chem., 2023, 3(1), 13-27.