Molecular docking studies

To identify the predicted protein–ligand interactions of the synthetic compounds within the binding site, molecular docking studies were carried out using glide standard-precision mode (Glide score SP) Maestro 12.1 (Schrödinger, New York, NY, USA) running on a Windows 10 operating system (Kumar et al. 2021). Docking simulations were also utilized to realize the possible best binding poses of the docked molecules, so they could be used to explain the reported results and to distinguish the promising leads. Molecular docking studies usually follow a general procedure that starts with the selection and preparation of an appropriate protein, grid generation, and ligand preparation, followed by analyzing docking outcomes and investigating the ligand–receptor interaction patterns. The X-ray crystal-structure data applied for docking studies were taken from the Brookhaven protein data bank (PDB; http://www.rcsb.org/pdb. The human COX-1 (PDB ID 3KK6) and human COX-2 (PDB ID 5KIR) were selected based on their relevant binding orientations and high resolution (e.g., resolutions were 2.75 A˚ and 2.70 A˚, respectively) for molecular docking studies regarding cyclooxygenase enzymes, which were previously applied in our previous work (Assali et al. 2020).

Also, the biological assay of antimicrobial activity of molecules was supported by conducting molecular docking studies within critical bacterial target enzymes present in Gram-negative bacteria like P. aeruginosa elastase B protein (PDB ID 1U4G) and K. pneumonia KPC-2 carbapenemase protein (PDB ID 2OV5) (Magpantay et al. 2021). P. aeruginosa elastase B (pseudolysin), the main peptidase found in pseudomonal secretions, plays multi-functional roles in different aspects of the pathogen–host interaction starting from the invasiveness stage through breaking the basolateral intercellular junctions present in the host tissues to the post-invasiveness stage via hydrolyzing of many immunologically relevant molecules like complement components and antibodies (Galdino et al. 2019; Bommagani et al. 2021). K. pneumonia carbapenemases (KPC) are hydrolysis enzymes that are suggested to be the main reason for inactivation B -lactam antibiotics (including Carbapenems) and imipenem results in drug-resistance generating (Malathi et al. 2019; Sharma et al. 2021). Thus, P. aeruginosa elastase B and K. pneumoniae carbapenemase become highly attractive targets to defeat antibiotic-refractory infections as a recently urgent issue caused by P. aeruginosa and K. pneumonia.

Additionally, molecular docking studies were performed within the administrative fungal enzyme cytochrome P450 14-α-sterol demethylase (Cyp51), which is found in a complex with fluconazole (PDB1 ID 1EA1), and it is a representative critical protein in C. albicans (Ghabbour et al. 2014). The final score was presented as a Glide score based on the energy-minimized poses. The lowest Glide score value related to the best-docked pose for each ligand was recorded (Friesner et al. 2004). Using the Graphical User Interface of Maestro 12.1 (Zervou et al. 2021), the ligands were drawn, followed by ligand preparation, including parameterizing the atom types and protonation states at target pH (7.0 ± 2.0) with the OPLS2005 force field using LigPrep (Assali et al. 2020; Panwar and Singh 2021). The crystal structures were prepared using the Protein Preparation Wizard (Schrödinger 2016), which started with preprocessing that involved: filling in missing side chains using prime, creating zero-order bonds to metals, adding hydrogens, creating disulfide bonds, deleting water molecules beyond 5 Å from the hit group, and removing waters with less than 3 H-bonds to non-waters. The preprocessing step was followed by optimizing the protein structure’s hydrogen bonds, followed by minimizing to a root-mean-square deviation of 0.3 Å. The receptor grids were generated using the prepared proteins; the default setup was conserved. The PLIP server was applied to evaluate the binding modes (Adasme et al. 2021). The final results were visualized with PyMOL 2.5.2 (Elokely and Doerksen 2013). In order to validate the docking method concerning each prepared protein, the native ligand was drawn, prepared, and re-docked into the binding pockets. Then, the native ligand was superimposed with the best pose of the re-docked ligand, followed by calculating the root mean square deviation (RMSD). Getting an RMSD value less than 2.0 Å indicates that the protein crystal structures and ligands were appropriately prepared and the docking method precisely works (Bell and Zhang 2019).