Journal of Computational Biophysics and Chemistry

The study of intermolecular interactions is of great importance. This study attempted to quantitatively examine the interactions between bromine monochloride (BrCl) with pristine boron nitride nanotube (BNNT) armchair (5,5) and zigzag (7,0) as well as armchair (5,5) BC₂NNT and zigzag (7,0) BC₂NNT in vacuum. Quantum mechanical studies of such systems are possible in the density functional theory (DFT) framework. For this purpose, various functionals, such as B3LYP-D3, $\omega$B97XD, and M062X, have been used. One of the most suitable basis functionals for the systems studied in this research is 6-311G (d), which has been used in both optimization calculations and calculations related to wave function analyses. The main part of this work is the study of various analyses that reveal the nature of the intermolecular interactions between the two components introduced above. The results of conceptual DFT, natural bond orbital, non-covalent interactions, and quantum theory of atoms in molecules (QTAIM) were consistent and in favor of physical adsorption in all systems. Gallium had more adsorption energy than other dopants. The HOMO–LUMO energy gaps were as follows: BNNT (5,5): 10.296, BNNT (7,0): 9.015, BC₂NNT (5,5): 7.022, and BC₂NNT (7,0): 5.979eV at B3LYP-D3/6-311G (d) model chemistry. The strongest interaction is related to the BC₂NNT (7,0)/BrCl cluster: $-0.488$eV. The results of QTAIM and NCI analysis identified the intermolecular interactions of the type of strong van der Waals interaction for these nanotubes. The sensitivity of the adsorption increased when a gas molecule interacted with carbon-doped BNNT, and the change in the frontier orbital gap could be used to design nanosensors to detect BrCl gas.

Introduction: Turmeric rhizome (Cucurma longa L.) has showed great potential as a traditional drug in folk medicine of several countries. In light of the prominent use of turmeric rhizome in treating both respiratory and viral diseases, we aimed to dock major compounds from the essential oil of turmeric against three key proteins involved in COVID-19 cell entry and replication. Methods: The essential oil of turmeric rhizome was obtained using a hydrodistillation technique, and the chemical characterization of the oil was investigated using GC-MS/GC-FID. Then, main compounds were docked with the key proteins of COVID-19. Results: A total of 26 components were identified in the essential oil extracted from the rhizomes via GC-MS/GC-FID. Seven dominant compounds (turmerone (31.4%), ar-turmerone (16.1%), turmerol (14.6%), terpinolene (11.0%), $\alpha$-zingiberene (5.2%), $\beta$-sesquiphellandrene (4.8%), and $\beta$-caryophyllene (3.5%)) were docked against COVID-19 main protease, papain-like protease (PLpro), spike protein and 3C-like protease (3CLpro), and the best inhibitor was picked according to the calculated binding affinity and non-bonding interactions with the protein active site. $\beta$-sesquiphellandrene and $\alpha$-zingiberene showed highest besides the same binding affinity towards COVID-19 virus ($-6.38$ and $-6.39$kcal/mol, respectively). $\alpha$-zingiberene was found to bind at the active site of the COVID-19 protein and interacted with different non-bonding interactions, while turmerol showed the highest affinity ($-5.78$kcal/mol) against CLpro enzyme by binding with Met165, Leu141, Met49, Ser144, Cys145, and Glu166 residues. Conclusion: The essential oil of turmeric harbors a blend of potentially bioactive compounds that may be considered as a good target against COVID-19 virus and warrants further experimental studies.

Dengue virus (DENV) is the causative agent of dengue fever, dengue hemorrhagic disease and dengue shock syndrome (DSS), transmitted predominantly in tropical and subtropical regions by Aedes aegypti. It infects millions of people and causes thousands of deaths each year, but there is no antiviral drug against DENV. Usnic acid lately piqued the interest of researchers for extraordinary biological characteristics, including antiviral activity. Based on high larvicidal activities against Aedes aegypti, this study aims to search usnic acid derivatives as novel anti-DENV agents through a combination of ligand-based and pharmacophore-based virtual screening. One hundred and sixteen (116) usnic acid derivatives were obtained from a database of 428 in-house usnic acid derivatives through pharmacophore filtering steps. Subsequent docking simulation on DENV-3 NS-5 RdRp afforded 41 compounds with a strong binding affinity towards the enzyme. The pharmacokinetics and drug likeness prediction resulted in seven hit compounds, which eventually undergo cytochrome P450 enzyme screening to obtain the lead compound, labelled as 362. In addition, molecular dynamic (MD) simulation of lead compound 362 was performed to verify the stability of the docked complex and the binding posture acquired in docking experiments. Overall, the lead compounds have shown a high fit value of pharmacophore, strong binding affinity towards RdRp enzyme, good pharmacokinetics, and drug likeness properties. The discovery of a new usnic acid derivative as a novel anti-DENV agent targeting RdRp could lead to further drug development and optimization to treat dengue.

Benzimidazole derivative molecules attract attention of scientists due to their bioactivities. The dramatic changes in recorded activities according to the type and position of the substituents motivate synthesis and analysis of new molecules. Commercial benzimidazole-based molecules have been used in therapeutic procedures. It is known that the activities of metal complexes with benzimidazole derivative ligands have different activities when compared to the benzimidazole main structure. Nowadays, one of the most important health problems is COVID-19, which caused the pandemic that we are still experiencing. Although vaccine studies are important to overcome acute problems, regarding the possible post-vaccination adverse effects, the need for new drugs against the virus is obvious. Considering the urgency and the limited facilities during the pandemic, preliminary in silico studies of candidate molecules are essential. In this study, {[bis-(N-benzylbenzimidazole)] tetracarbonylmolybdenum}, {[bis-(N-4-chlorobenzylbenzimidazole)] tetracarbonylmolybdenum} and {[bis-(N-4-methoxybenzylbenzimidazole)] tetracarbonylmolybdenum} were synthesized and characterized. The optimization and the structural analysis of these molecules were performed by DFT/TDDFT methods. The molecules were docked into SARS coronavirus main peptidase (PDB ID: 2gtb), COVID-19 main protease in complex with Z219104216 (PDB ID: 5r82), COVID-19 main protease in complex with an inhibitor N3 (PDB ID: 6lu7) and Papain-like protease of SARS-CoV-2 (PDB ID: 6w9c) crystal structures for evaluation of their anti-viral activity.

Dehydrozingerone (the half-analogue of curcumin) is a natural product that is isolated from ginger rhizomes. Recent studies have shown that this compound displays several physiological activities including antioxidant properties, and it can scavenge oxygen-free radicals like hydroxyl, peroxyl and superoxide radicals. In this work, the thermodynamic and kinetic aspects of the antiradical activity of the natural dehydrozingerone DHZ0 (R=H) and the designed derivatives DHZ1 (R=CHO), DHZ2 (R=OMe) and DHZ3 (R=NMe₂) towards the hydroperoxyl radical (HOO^•) were investigated at the M06-2X/6-311$+$G($d$,$p$) level of theory. The calculations have been performed in gas phase, pentyl ethanoate and water solvents using the implicit SMD solvation model. Four potential mechanisms have been investigated, namely, hydrogen atom transfer (HAT), single-electron transfer followed by proton transfer (SET-PT), sequential proton loss electron transfer (SPLET) and radical adduct formation (RAF). The obtained results show that the SET-PT and RAF mechanisms are endergonic processes and are thermodynamically disfavored, whereas the exergonic HAT process is predicted as the most thermodynamically favored mechanism in all media. The SPLET mechanism was excluded due the minor proportions of the anion species at physiological pH. Kinetic calculations show that DHZ3 reacts with HOO^• 1860, 1250 and 215 times faster than DHZ0 in gas phase, pentyl ethanoate, and water, respectively. Based on thermodynamic and kinetic calculations, the designed compound DHZ3 is predicted as a good candidate for hydroperoxyl scavenging in both polar and nonpolar media. Drug likeness evaluation of the studied DHZ derivatives shows that the pharmacokinetic parameters satisfy all the Lipinski and Veber rules.

Sirtuin 2 (SIRT2) is a nicotinamide adenine dinucleotide (NAD+)-dependent deacetylase that has been identified as a target for many diseases, including Parkinson’s disease (PD) and leukemia. Using 234 SIRT2 inhibitors from the ZINC15 database, we generated molecular descriptors with PaDEL and constructed a machine-learning (ML) model for the binary classification of SIRT2 inhibitors. To predict compounds with novel inhibitory mechanisms, we then applied the model on the ZINC15/FDA subset, yielding 107 potential SIRT2 inhibitors. For validation of these substances, we employed the binding analysis software AutoDock Vina to perform virtual screening, with which 43 compounds were considered best inhibitors at the $-10$kcal/mol binding affinity threshold. Our results demonstrate the potential of ligand-based (LB) ML techniques in conjunction with receptor-based virtual screening (RBVS) to facilitate the drug discovery or repurposing.

$\alpha$-amylase is the most widely used Glycoside Hydrolase (GH) in industries for decades. It randomly cleaves the $\alpha$-D-(1, 4) glucosidic bonds of $\alpha$-polysaccharides (starch and glycogen) to release glucose and short-chain oligosaccharides. Substantial advances have taken place in research related to $\alpha$-amylases. However, bioinformatics study needs a little more exploration before conducting wet-lab experiments. We aimed to perform a comparative structure-function relationship study of 10 different Bacillus-derived $\alpha$-amylases using several computational biology tools. After aligning all the $\alpha$-amylases, 3D structures were made using the SWISS-MODEL. The accuracy and stability of the predicted models were validated via different web servers like Verify-3D, ERRAT, RMSD and ProSA. MolProbity and PROCHECK were used for mapping the residues in the most favored region of the Ramachandran plot. The Ramachandran plot reveals that $>90\%$ of the amino acid residues of the selected $\alpha$-amylase genes lie within the favored region. Our findings suggest that all the $\alpha$-amylases were stable as per the validation results we got. The study has revealed clear and concise structural related aspects. This paper will encourage the researchers to include and prioritize in silico work of $\alpha$-amylase genes to obtain more accurate outcomes. As the output obtained in this study via in silico tools reveals the structural peculiarity and more about the catalytic domain impression, it highly recommends incorporating such studies for better results. This approach will save efforts, costs and time for researchers.

Piperazine/morpholine derivatives of quinoline substituted at positions C-3, C-6 and C-8 has been previously prepared by S_NAr reactions of 3,6,8-tribromoquinoline (1) under microwave or conventional heating reaction conditions. In this study, we evaluated binding interactions between the piperazine/morpholine substituted quinolines and its highly-likely receptor, Cyclin G associated kinase (GAK) involved in hepatitis C virus (HCV) entry into host cells, via docking, molecular dynamics (MD), thermodynamic and pharmacokinetics computations in order to select a possible lead compound, which may be used for lead-optimization in our future studies to develop novel drug candidates against HCV infections. 372 nsec MD simulations followed by MM-PBSA thermodynamic computations revealed that compound 23 ($K_d$= 0.08nM) possesses the greatest potential to inhibit GAK. Pharmacokinetics computations suggest that compound 23 is a drug-like molecule as it conforms to the Lipinski filter. We determined that compound 23 could be a lead-like molecule for peripheric and cerebral HCV infections.