A combined experimental and quantum chemical study on molecular structure, spectroscopic properties and biological activity of anti-inflammatory Glucocorticosteroid drug, Dexamethasone

A Molecular Fragment Representation Learning Framework for Drug-Drug Interaction Prediction

The concurrent use of multiple drugs may result in drug-drug interactions, increasing the risk of adverse reactions. Hence, it is particularly crucial to propose computational methods for precisely identifying unknown drug-drug interactions, which is of great significance for drug development and health. However, most recent studies have limited the drug-drug interaction prediction task to identifying interactions between substructures, overlooking molecular hierarchical information. Moreover, the extracted substructures in these methods are always restricted to have the same number of atoms as contained in the molecular graph, which does not align with real-world facts. In this study, a molecular fragment representation learning framework for drug-drug interaction prediction is introduced. Initially, a fragment extraction module is designed to acquire a series of molecular fragments. Subsequently, to capture more comprehensive features, molecular hierarchical information is effectively integrated, enabling drug-drug interaction prediction by identifying pairwise interactions between molecular fragments of each drug. Comprehensive evaluations demonstrate that the proposed method achieved state-of-the-art performance in both DrugBank and Twosides datasets, particularly achieving an improved accuracy of over 20% for unseen drugs in both two datasets. Furthermore, case studies and visual analysis confirm that the proposed method can accurately identify crucial substructures influencing the interactions, which are basically consistent with functional group structures in reality. In conclusion, this method not only enhances the performance of drug-drug interaction prediction but also offers high interpretability. Source code is freely available at https://github.com/kennysyp/MFR-DDI .

A DFT study of the effect of hydrostatic pressure on the structure and electronic properties of sarcosine crystal

CONTEXT

We perform density functional theory calculations to study the dependence of the structural and electronic properties of the amino acid sarcosine crystal structure on hydrostatic pressure application. The results are analyzed and compared with the available experimental data. Our findings indicate that the crystal structure and properties of sarcosine calculated using the Grimme dispersion-corrected PBE functional (PBE-D3) best agree with the available experimental results under hydrostatic pressure of up to 3.7 GPa. Critical structural rearrangements, such as unit cell compression, head-to-tail compression, and molecular rotations, are investigated and elucidated in the context of experimental findings. Band gap energy tuning and density of state shifts indicative of band dispersion are presented concerning the structural changes arising from the elevated pressure. The calculated properties indicate that sarcosine holds great promise for application in electronic devices that involve pressure-induced structural changes.

METHODS

Three widely used generalized gradient approximation functionals-PBE, PBEsol, and revPBE-are employed with Grimme's D3 dispersion correction. The non-local van der Waals density functional vdW-DF is also evaluated. The calculations are performed using the projector-augmented wave method in the Quantum Espresso software suite. The geometry optimization results are visualized using VMD. The Multiwfn and NCIPlot programs are used for wavefunction and intermolecular interaction analyses.

General performance, kinetic modification, and key regulating factor recognition of microalgae-based sulfonamide removal

Sulfonamides have been widely detected in water treatment plants. Advanced wastewater treatment for sulfonamide removal based on microalgal cultivation can reduce the ecological risk after discharge, achieve carbon fixation, and simultaneously recover bioresource. However, the general removal performance, key factors and their impacts, degradation kinetics, and potential coupling technologies have not been systematically summarized. To guide the construction and enhance the efficient performance of the purification system, this study summarizes the quantified characteristics of sulfonamide removal based on more than 100 groups of data from the literature. The biodegradation potential of sulfonamides from different subclasses and their toxicity to microalgae were statistically analyzed; therefore, a preferred option for further application was proposed. The mechanisms by which the properties of both sulfonamides and microalgae affect sulfonamide removal were comprehensively summarized. Thereafter, multiple principles for choosing optimal microalgae were proposed from the perspective of engineering applications. Considering the microalgal density and growth status, a modified antibiotic removal kinetic model was proposed with significant physical meaning, thereby resulting in an optimal fit. Based on the mechanism and regulating effect of key factors on sulfonamide removal, sensitive and feasible factors (e.g., water quality regulation, other than initial algal density) and system coupling were screened to guide engineering applications. Finally, we suggested studying the long-term removal performance of antibiotics at environmentally relevant concentrations and toxicity interactions for further research.

Spectroscopic characterization, DFT, antimicrobial activity and molecular docking studies on 4,5-bis[(E)-2-phenylethenyl]-1H,1'H-2,2'-biimidazole

The newly synthesized imidazole derivative namely, 4,5-bis[(E)-2-phenylethenyl]-1H,1'H-2,2'-biimidazole (KA1), was studied for its molecular geometry, docking studies, spectral analysis and density functional theory (DFT) studies. Experimental vibrational frequencies were compared with scaled ones. The reactivity sites were determined using average localized ionization analysis (ALIE), electron localized function (ELF), localized orbital locator (LOL), reduced density gradient (RDG), Fukui functions and frontier molecular orbital (FMO). Due to the solvent effect, a lower gas phase energy gap was observed. Through utilization of the noncovalent interaction (NCI) method, the hydrogen bond interaction, steric effect and Vander Walls interaction were investigated. Molecular docking simulations were employed to determine the specific atom inside the molecules that exhibits a preference for binding with protein. The parameters for the molecular electrostatic potential (MESP) and global reactivity descriptors were also determined. The thermodynamic characteristics were determined through calculations employing the B3LYP/cc-pVDZ basis set. Antimicrobial activity was carried out using the five different microorganisms like Escherichia coli, Streptococcus pneumoniae, Staphylococcus aureus, Klebsiella pneumoniae and Candida albicans.

Synthesis, topology, molecular docking and dynamics studies of o-phenylenediamine derivative

The N, N'-(1,2-phenylene) bis (1- (4- chlorophenyl) methanimine) (CS4) was synthesized and characterized by infrared (IR), absorption (UV-vis) and NMR (1H and 13C) spectral analyses. The structural parameters, vibrational frequencies, potential energy and the distribution analysis (PED) were calculated by using DFT with the basis set of B3LYP/cc-pVDZ and these spectral values were compared to the experimental values. HOMO and LUMO studied were performed in order to understand the stability and biological activity of the compound. The most reactive sites on the compound were investigated by utilizing MEP energy surface and Fukui function descriptor with the natural population analysis (NPA) of the charges. The study of the natural bond orbitals (NBO) reveals the delocalization of the intramolecular interaction of the charges in the compound. Additionally, topological investigations (ELF, LOL), determination of thermodynamic parameters and noncovalent interaction (NCI) study by using topology (RDG) analysis were also carried out. Finally, the molecular docking and molecular dynamics simulations was carried out by examining against glycosylphosphatidylinositol phospholipase D inhibitor receptor for distinct protein targets (3MZG).Communicated by Ramaswamy H. Sarma.

Charge-transfer chemistry of two corticosteroids used adjunctively to treat COVID-19. Part II: The CT reaction of hydrocortisone and dexamethasone donors with TCNQ and fluoranil acceptors in five organic solvents

Hydrocortisone (termed as D1) and dexamethasone (termed as D2) are corticosteroids currently used to treat COVID-19. COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Exploring additional chemical properties of drugs used in the treatment protocols for COVID-19 could help scientists alike improve these treatment protocols and potentially even the vaccines (i.e., Janssen, Moderna, AstraZeneca, Pfizer-BioNTech). In this work, the charge-transfer (CT) properties of these two corticosteroids (D1 and D2) with two universal acceptors: 7,8,8-tetracyanoquinodimethane (termed as TCNQ) and fluoranil (termed as TFQ) in five different solvents were investigated. The examined solvents were MeOH, EtOH, MeCN, CH2Cl2, and CHCl3. The CT interactions formed stable corticosteroid CT complexes in all examined solvents. Several spectroscopic parameters were derived, and the oscillator strength (f) and transition dipole moment (μe.g. ) values revealed that the interaction between the investigated corticosteroids with TCNQ acceptor is much stronger than their interaction with TFQ acceptor. The CT interactions were proposed to process via n → π* transition.

Synthesis, spectroscopic, topological, hirshfeld surface analysis, and anti-covid-19 molecular docking investigation of isopropyl 1-benzoyl-4-(benzoyloxy)-2,6-diphenyl-1,2,5,6-tetrahydropyridine-3-carboxylate

Isopropyl 1-benzoyl-4-(benzoyloxy)-2,6-diphenyl-1,2,5,6-tetrahydropyridine-3-carboxylate (IDPC) was synthesized and characterized via spectroscopic (FT-IR and NMR) techniques. Hirshfeld surface and topological analyses were conducted to study structural and molecular properties. The energy gap (Eg), frontier orbital energies (EHOMO, ELUMO) and reactivity parameters (like chemical hardness and global hardness) were calculated using density functional theory with B3LYP/6-311++G (d,p) level of theory. Molecular docking of IDPC at the active sites of SARS-COVID receptors was investigated. IDPC molecule crystallized in the centrosymmetric triclinic ( P 1 ¯ ) space group. The topological and Hirshfeld surface analysis revealed that covalent, non-covalent and intermolecular H-bonding interactions, and electron delocalization exist in the molecular framework. Higher binding score (-6.966 kcal/mol) of IDPC at the active site of SARS-COVID main protease compared to other proteases suggests that IDPC has the potential of blocking polyprotein maturation. H-bonding and π-cationic and interactions of the phenyl ring and carbonyl oxygen of the ligand indicate the effective inhibiting potential of the compound against the virus.

Charge-transfer chemistry of two corticosteroids used adjunctively to treat COVID-19. Part I: Complexation of hydrocortisone and dexamethasone donors with DDQ acceptor in five organic solvents

COVID-19 is the disease caused by a novel coronavirus (CoV) named the severe acute respiratory syndrome coronavirus 2 (termed SARS coronavirus 2 or SARS-CoV-2). Since the first case reported in December 2019, infections caused by this novel virus have led to a continuous global pandemic that has placed an unprecedented burden on health, economic, and social systems worldwide. In response, multiple therapeutic options have been developed to stop this pandemic. One of these options is based on traditional corticosteroids, however, chemical modifications to enhance their efficacy remain largely unexplored. Obtaining additional insight into the chemical and physical properties of pharmacologically effective drugs used to combat COVID-19 will help physicians and researchers alike to improve current treatments and vaccines (i.e., Pfizer-BioNTech, AstraZeneca, Moderna, Janssen). Herein, we examined the charge-transfer properties of two corticosteroids used as adjunctive therapies in the treatment of COVID-19, hydrocortisone and dexamethasone, as donors with 2,3-dichloro-5,6-dicyano-p-benzoquinone as an acceptor in various solvents. We found that the examined donors reacted strongly with the acceptor in CH2Cl2 and CHCl3 solvents to create stable compounds with novel clinical potential.