Introduction Inflammation is a fundamental response of the immune system during tissue damage or pathogen infection to protect and maintain tissue homeostasis. However, inflammation may lead to life-threatening conditions. The most common treatment of inflammation is non-steroidal anti-inflammatory drugs (NSAIDs). Nowadays, the development of safer new NSAIDs is critical as most of the existing NSAIDs have serious adverse effects, such as gastrointestinal (GI) toxicity and cardiotoxicity. In the present study, four compounds as Schiff base derivatives of 7-hydroxy-4-formyl coumarin and 7-methoxy-4-formyl coumarin were designed and synthesized aiming to develop a lead compound that exhibits anti-inflammatory activity and circumvents the side effects of NSAIDs, especially GI toxicity. Materials and Methods Lipinski’s rule of five was applied for each designed molecule to evaluate the drug-likeness properties. Molecular docking studies were performed using the ligands and the cyclooxygenase-2 (COX-2) protein to select the best-scored molecule using AutoDock 4.2.6. The molecules were then synthesized and characterized. An in vitro anti-inflammatory assay of the compounds against the COX-2 receptor was realized through a protein denaturation assay. Results and Discussion All four synthesized ligands passed Lipinski’s rule of five and exhibited higher binding free energy compared to the positive standard control (ibuprofen), and the K i values of compounds 5, 7, and 8 were in the nanomolar range. However, only compounds 6 and 7 obtained a higher percentage of inhibition of protein denaturation relative to ibuprofen. Conclusion The present study suggested that compound 7 may be a lead molecule because this ligand not only exhibited the best computational and experimental results but also exhibited the strongest correlation between the concentration and percentage of protein denaturation (R = 0.986 and R 2 = 0.972) with the lowest P-value (0.014).

New Delhi Metallo-β-lactamase enzyme (NDM-1) is an enzyme that hydrolyzes a wide range of β-lactam antibiotics, including most carbapenems, leading to antimicrobial resistance. The development of a novel NDM-1 inhibitor for use in combination with carbapenems may help to combat drug-resistant pathogens. Twenty compounds derived from naphthalene, thiazole, and sulfone derivatives were designed to inhibit bacterial NDM-1 and protect β-lactam antibiotics from enzyme attack. Two- and three-dimensional structures of the designed molecules were sketched using MarvinSketch, and a molecular docking protocol was used to identify potential inhibitor(s) of the NDM-1 target protein using AMDock v 1.5.2. The binding free energy of each compound against NDM-1 was determined and the drug-likeness properties of the designed molecules were assessed using SwissADME. Two compounds with the highest ΔGbinding results, T008 and T016, were selected for further investigation using molecular dynamic (MD) simulations with the GROMACS simulation package (GROMACS 2020.4). The duration of each MD simulation was 100 ns. Both compounds had a significantly higher binding free energy than the positive control and other designed molecules, their MD simulations remained stable, they passed Lipinski’s rule of five, and were shown to have favorable physicochemical properties. The study outcomes can be used to inform synthesis and in vitro testing of the selected molecules.

Carbapenems are considered as the most effective antibiotic against Acinetobacter baumannii infections, as the pathogen has a resistance to the most of the other beta-lactam antibiotics; however, recent studies proved that this pathogen has developed resistance to carbapenems, as well. Therefore, development of novel therapeutics targeting A. baumannii resistant strains is an urgent global requirement. One of the causes responsible for this bacterial resistance against beta-lactam antibiotics is the decreased strength of interactions between A. baumannii Penicillin-Binding Proteins 1A (PBP1A) and carbapenems. Therefore, the aim of this study is to design a novel analogue of imipenem with significantly higher binding affinity and improved drug-likeness properties to overcome resistance of the pathogen and optimize bioavailability, respectively. De novo drug design was performed using virtual screening to predict the ligand(s) with the highest binding affinity. The two-dimensional and three-dimensional structure of the designed molecules were sketched using Chemdraw professional and MarvinSketch, respectively. After separating the targeted protein from A. baumannii PBP1A-imipenem complex structure (3UDX) and retaining a monomer (chain A) from a dimer of the protein structure using Text Editor (ConTEXT v0.98.6), docking was achieved using virtual screening AutoDock Vina program. Finally, drug-likeness properties were assessed. The results could find the selected compounds with significantly higher binding affinity and improved physicochemical properties compared with imipenem.

An accurate prediction of the ligand-receptor binding free energies (ΔG) is a critical step in the early stages of rational drug design. The Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) method is a popular   approach to estimate ΔG. However, correlations between the predicted and the experimental ΔG are variable. The goal of this study is to investigate various approaches to optimize accuracy of the MM-GBSA method. A molecular dynamic (MD) simulations protocol was applied using penicillopepsin receptor against its inhibitor ligands, repeated 50 times for each complex system. After that, ΔG of the five inhibitors were predicted using MM-GBSA method. Moreover, a diverse ΔG values were calculated from the replicate MD simulations of each system. The results were showed correlations not only between the predicted and the experimental binding affinities of the systems but also between the predicted values and root-mean-square deviation. In addition, statistical analysis was evaluated the sample size.

Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzyme. The tested sets are composed of eight receptor-ligand complexes with high resolution crystal structures downloaded from Protein Data Bank website. Molecular dockings were applied between approved HIV-1 protease inhibitors and the HIV-1 protease using AutoDock Vina, 1-Click Docking, and DOCK6. Then, docking poses of the top-ranked solution was realized using UCSF Chimera. Furthermore, Pearson correlation coefficient (r) and coefficient of determination (r2) between the experimental results and the top scored docking results of each program were calculated using Graphpad prism V9.2. After comparing saquinavir top scored binding poses of each docking program with the crystal structure, various conformational changes were observed. Moreover, according to the relative comparison between the top ranked calculated ?Gbinding values against the experimental results, r2 value of AutoDock Vina, 1-Click Docking, and DOCK6 were 0.65, 0.41, and 0.005, respectively. The outcome of this study shows that the top scored binding free energy could not produce the best pose prediction. In addition, AutoDock Vina results have the highest correlation with the experimental results.