Quantum Descriptors Research Articles

Exploring compound suitability and employing DFT calculations, molecular docking, and dynamics simulation to investigate potent compounds from podophyllum medicinal plants for breast cancer therapy

BackgroundBreast cancer, one of the most often diagnosed malignancies worldwide, continues to take countless women's lives. Its treatment usually involves targeting the human estrogen receptor alpha (ERα). Current research explores the potential of natural compounds to regulate ERα activity, providing a hopeful direction for breast cancer therapy. Our study utilized a comprehensive approach to identify promising natural compounds for breast cancer treatment, including quantum descriptors, molecular docking, molecular dynamics simulations, and ADMET/pharmacokinetics analysis. ResultsSix natural compounds derived from podophyllum medicinal plants, namely 4-demethylpodophyllotoxin (NP1), α-peltatin (NP2), podophyllotoxin (NP3), deoxypodophyllotoxin (NP4), podophyllotoxone (NP5), and β-peltatin (NP6), were investigated as potential selective estrogen receptor α (ERα) inhibiting agents for breast cancer. These compounds demonstrated the strongest binding affinity to the target enzyme, with binding energies of − 8.9 and − 8.1 kcal/mol, respectively. Further assessments of drug-likeness and ADME properties were conducted for these compounds, along with quantum calculations (HOMO–LUMO) to evaluate their reactivity. Additionally, molecular dynamics studies were performed to assess the stability of the NP1 and NP2 protein–ligand complexes.ConclusionsWe analyzed six natural compounds comprehensively, evaluating their ADME properties, molecular docking interactions, quantum descriptors, and dynamic simulations. Our findings demonstrate that these natural compounds are promising possibilities for treating breast cancer. Additionally, they may provide a basis for developing future compounds targeting estrogen receptor α (ERα) activity.Graphical abstract

Development of new sustainable pyridinium ionic liquids: From reactivity studies to mechanism-based activity predictions.

This study addresses the development of sustainable pyridinium ionic liquids (ILs) because of their potential applications in agriculture and pharmaceuticals. Pyridinium-based ILs are known for their low melting points, high thermal stability, and moderate solvation properties. We synthesized three novel pyridinium-based ILs: 1-(2-(isopentyloxy)-2-oxoethyl)pyridin-1-ium chloride, 1-(2-(hexyloxy)-2-oxoethyl)pyridin-1-ium chloride, and 1-(2-(benzyloxy)-2-oxoethyl)pyridin-1-ium chloride. The biological activities of these compounds were evaluated through plant growth promotion, herbicidal, and insecticidal assays. Our results show that the benzyloxy derivative significantly enhances wheat and cucumber growth, whereas the isopentyloxy compound has potent herbicidal effects. Computational methods, including DFT calculations and molecular docking, were applied to understand the structure‒activity relationships (SARs) and mechanisms of action. The computational techniques involved dispersion-corrected density functional theory (DFT) with the B3LYP functional and the 6-311G** basis set. Grimme's D3 corrections were included to account for dispersion interactions. The calculations were performed via GAMESS-US software. Quantum descriptors of reactivity, such as ionization potential, electron affinity, chemical potential, and electrophilicity index, were derived from the HOMO and LUMO energies. Molecular docking studies were conducted via the CB-Dock server via AutoDock Vina software to predict binding affinities to cancer-related proteins. Petra/Osiris/Molinspiration (POM) analysis was used to predict the drug likeness and other pharmaceutical properties of the synthesized ILs.

Understanding adsorption ability of CNT (6, 6-6) and BNNT (6, 6-7) nanotubes for a novel hybrid pyrazole-indole drug, InPy-7a

The quest for enhanced drug delivery efficacy across diverse physiological conditions has spurred the exploration of various nanomaterials, including carbon-based materials like carbon nanotubes (CNTs) and boron nitride nanotubes (BNNTs). These materials offer high surface areas conducive to increased drug loading, with considerations such as surface charge, size, shape, and biocompatibility being paramount. The hybrid drug, synthesized by combining indole derivatives with a pyrazole moiety, has shown promising cytotoxicity against various cancer cell lines. In this context, we have explored the adsorption ability of CNT (6, 6-6) and BNNT (6, 6-7) nanotubes for a novel hybrid drug, InPy-7a, using density functional theory (DFT) calculations. Our study has aimed to elucidate the adsorption mechanisms and electronic properties of InPy-7a on the surfaces of CNT (6, 6-6) and BNNT (6, 6-7). Through computational tools, we have analyzed the geometry optimization of InPy-7a onto the nanotube surfaces, evaluating molecular interactions, quantum descriptors, frontier molecular orbitals (FMO), natural bond orbitals (NBO), nuclear magnetic resonance (NMR), and molecular electrostatic potential (MEP). Our results have illuminated the underlying mechanisms by revealing unique interactions and electronic changes during complexation. Based on predicted electronic aspects and molecular interactions, the CNT@InPy-7a-S5 complex system showed greater chemical reactivity, adsorption, and stability than BNNT@InPy-7a-S6. These findings open up opportunities for additional experimental validations and offer insightful information about the possible uses of drug delivery systems based on nanotubes.

Structural modification of graphene material by silicon mono-doping and codoping with heteroatoms as sensors for methyl tert-butyl ether (MTBE) as a fuel additive: Insights from DFT

Due to the association of methyl tert-butyl ether (MTBE) with groundwater contamination and environmental concerns, fuel additives, and recognized health hazards, including respiratory and central nervous system effects upon exposure, the implementation of mitigating measures becomes imperative on a global scale, particularly through the utilization of nano-oriented materials. Hence, to account for the sensitivity, detection, and adsorption of methyl tert-butyl ether (MTBE) pollutants, this research attempts to investigate the potential of silicon-doped graphene (Si@GP) engineered with boron, nitrogen, and phosphorous atoms by employing density functional groups at the ωB97XD/def2vsp level of theory. Interestingly, the results from several quantum descriptors were analysed to obtain comprehensive knowledge of the interactions between the adsorption complexes. The examined systems (MTBE-Si@GP, MTBE-SiB-GP, MTBE-SiN-GP, and MTBE-SiP-GP) produced Fermi energies of 0.4531 eV, 0.4531 eV, 0.5274 eV, and 0.3936 eV, respectively, providing valuable insights into their electronic structure and sensitivity to MTBE. Subsequent calculations revealed that MTBE-SiP-GP had a work function of 0.3936 eV, making it a superior surface for sensing MTBE compared to the other surfaces considered. The adsorption energies for MTBE-Si@GP, MTBE-SiB-GP, MTBE-SiN-GP, and MTBE-SiP-GP were 8.004 eV, 7.159 eV, 7.785 eV, and 5.027 eV, respectively. Despite their physisorption properties, MTBE-SiP-GP was highlighted as the preferable absorbent at the BSSE level. The comprehensive analysis presented in this study highlights the potential of the MTBE-SiP-GP dopant as a reliable sensing material for monitoring MTBE liquified gas in real-world environments. Our research aims to equip experimental researchers with valuable insights on the silver graphene dopant, and specifically, the MTBE-SiP-GP surface, as a promising candidate for detecting gas sensors.

Integrated computational modeling and in-silico validation of flavonoids-Alliuocide G and Alliuocide A as therapeutic agents for their multi-target potential: Combination of molecular docking, MM-GBSA, ADMET and DFT analysis

Alliuocide class of compounds belong to flavonoids and were isolated from Allium cepa. Alliuocide are the key phytoconstituents of Allium cepa having biological activities like anticancer, antidiabetic, anti-allergic, metabolic, and inflammatory disorders, antibacterial as well as effective antioxidants against chronic diseases. However, after their isolation report, there was no further work done and a gap of about 10 years. Herein, the present study was carried out to cover the gap and to identify new lead candidates in drug discovery pipeline. Alliuocide A and G were screened against various antioxidant, antidiabetic, anticancer and antibacterial target proteins. Target based screening by molecular docking against different target receptor co-crystal structure revealed Alliuocide A as potential hit, these results were further demonstrated by MM-GBSA studies. Further optimization of both compounds was done by in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) studies. Both compounds followed Lipinski's rule of five therefore safe for further in vivo studies. Finally spectral studies along with quantum descriptors were carried out by employing DFT method at 6–311 G (d,p) basis set. These quantum chemical parameters proved to be important mechanism for correlating the inhibition efficiency with molecular quatum parameters. All these studies help in designing of derivatives for better pharmacological potential.

Adsorption of Methylene Blue Dye and Analysis of Two Clays: A Study of Kinetics, Thermodynamics, and Modeling with DFT, MD, and MC Simulations.

The purpose of this research was to learn more about the primary and secondary properties of Moroccan natural clay in an effort to better investigate innovative adsorbents and gain access to an ideal adsorption system. Scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy analysis (SEM-EDX) and X-ray fluorescence were employed for identification. SEM revealed clay grains, including tiny particles and unevenly shaped sticks. First- and second-order rate laws, representing two distinct kinetic models, were applied in the kinetic approach. Adsorption of dye MB onto natural clay was studied, and the results agreed with the 2 s order model. The significant correlation coefficients support the inference that the adsorption process was governed by the Langmuir model. Subsequent DFT analyses demonstrated that the methylene blue dye's HOMO and LUMO surfaces are dispersed across most of the dye's components, pointing to a strong interaction with the clay. To determine how the dye might be adsorbed onto the clay, we employed quantum descriptors to locate its most nucleophilic and electrophilic centers. Endothermic reactions are evident during the MB adsorption process on clay, as indicated by the positive values of ΔH0 and ΔS0 (70.49 kJ mol-1of RC and 84.19 kJ mol-1 of OC and 10.45 J mol-1 K-1 of RC and 12.68 mol-1 K-1 of OC, respectively). Additionally dye molecules on the adsorbent exhibit a higher order of distribution than in the solution, indicating that the adsorption process is spontaneous.

Harnessing machine learning and virtual sample generation for corrosion studies of 2-alkyl benzimidazole scaffold small dataset with an experimental validation

The present work deals with the development of a QSAR model based on Artificial Neural Network (ANN) algorithm for the prediction of inhibition efficiencies of 2-alkyl benzimidazole scaffold-based corrosion inhibitors for mild steel corrosion in 1 M HCl. The small dataset problems have been dealt with a Virtual Sample Generation (VSG) methodology using CTGAN algorithm, and credibility and generalizability of the proposed ANN+VSG model has been verified through experimental validation. Two new 2-alkyl benzimidazole scaffold-based corrosion inhibitor compounds namely EBIMOT and PBIMOT, were synthesised, their inhibition efficiencies were experimentally obtained, and the values showed a high resemblance with the predicted one by the model with good accuracy. Synthetic data embedding to the training samples enhances the model's recognition capacity of feature-target relationship and hence stabilizing and improving the correlation of the chemical quantum descriptors with the inhibition efficiency. This proposed method strengthens the prospect of ML for developing material designs, especially in the case of small datasets at a much cost-efficient, user-friendly, and accurate manner and can open doors to new and unexplored venues in the intersection of material science and computational intelligence.

Mapping the Oxygens in the Oxygen-Evolving Complex of Photosystem II by Their Nucleophilicity Using Quantum Descriptors.

The oxygen-evolving complex (OEC) of Photosystem II catalyzes the water-splitting reaction using solar energy. Thus, understanding the reaction mechanism will inspire the design of biomimetic artificial catalysts that convert solar energy to chemical energy. Conceptual Density Functional Theory (CDFT) focuses on understanding the reactivity of molecules and the atomic contribution to the overall nucleophilicity and electrophilicity of the molecule using quantum descriptors. However, this method has not been applied to the OEC before. Here, we use Fukui functions and the dual descriptor to provide quantitative measures of the nucleophilicity and electrophilicity of oxygens in the OEC for different models in different S states. Our results show that the μ-oxo bridges connected to terminal Mn4 are nucleophilic, and those in the cube formed by Mn1, Mn2, and Mn3 are mostly electrophilic. The dual descriptors of the bridging oxygens in the OEC showed a similar reactivity to that of bridging oxygens in Mn model compounds. However, the terminal water W1, which is bound to Mn4, showed very strong reactivity in some of the S3 models. Thus, our calculations support the model that proposes the formation of the O2 molecule through nucleophilic attack by a terminal water.

In silico evaluation for the design of coumarin-type compounds based on phenol and naphthol rings as a coating in carbon steel corrosion processes: DFT B3LYP calculations, synthesis and electrochemical characterization

Corrosion is a natural electrochemical process that converts metals into their most stable form, oxides. Coating metals with paints is done most effectively if oxide scales are removed, which is done by exposing the metals to corrosive media such as HCl, H2SO4, HNO3, and NaCl. However, corrosive solutions also attack the metal surface, and adding an inhibitor to the acid environment becomes necessary. Inhibitors can be inorganic or organic and are evaluated through techniques such as Potentiodynamic Polarization (PDP) and Impedance Spectroscopy (EIS). This work evaluated coumarin-type organic molecules compounds as potential corrosion inhibitors through the DFT B3LYP calculations of quantum descriptors. The results were analyzed using Principal Components Analysis (PCA), it is established that the values of inhibitory efficiency of 1, and 33, showed that the corrosion of the metallic surface which can be seen in the inhibitory efficiency values 1 (57,14 %) and 33 (82,86 %), it is evident that 33 has the highest effect respect other coumarins being identified as phenol and naphthol derivatives. These compounds were synthesized employing sequential reactions from the respective phenol: Pechmann cyclization, nitration, and reduction reactions. Then, the compounds were evaluated as anti-corrosive agents for carbon steel in the presence of 1.0 M HCl. The cathodic and anodic current densities in the HCl solution containing coumarin 1 exhibit lower values than the 33 and the Blank solutions. The obtained data reveals that as the amount of coumarins 1 (3.2 mg), and 33 (2.8 mg) increases, the corrosion current density (icorr) decreases to values of 3.08 and 4.90 mA.cm-2, respectively. These results were validated through the electrochemical evaluation of the molecules obtained by Potentiodynamic Polarization (PDP), Impedance Spectroscopy. (EIS) and Scanning Electron Microscopy (SEM).

In silico and in vitro studies: investigating the chemical composition, DFT, molecular docking, and dynamic simulation of Satureja candidissima (Munby) Briq essential oil as a potential antibacterial agent

This study aimed to investigate the chemical composition and antibacterial properties of the essential oil (EO) derived from the aerial parts of Satureja candidissima (Munby) Briq (SC), as well as the mechanisms of interaction between SCEO chemical components and target proteins related to antibacterial activity mechanisms using a molecular docking approach, and for more accuracy molecular dynamic simulation and DFT calculations were carried out. The GC–MS technique was used to analyze the chemical composition of SCEO. The results showed that SCEO contained various chemical compounds, with pulegone being identified as the major component (53.26%). The results also indicated the presence of (+)-menthone (11.02%), borneol (4.43%), 2-cyclohexen-1-one, 3-methyl-6-(1-methylethylidene) (2.50%), and 3-octanol (2.09%). The study revealed that the SCEO displayed antibacterial activity against all tested gram-positive bacteria. To further understand the mechanism behind its antibacterial activity, in silico molecular docking studies were performed. The results indicated that the antibacterial effect of SCEO compounds could be due to the combination with enoyl-[acyl-carrier-protein] reductase [NADPH] FabI (PDB ID: 4ALL) in a variety of ways. The molecular dynamics simulation analysis yielded favorable outcomes for the docked complex involving 1H-cycloprop[e]azulen-7-ol, decahydro-1,1,7-trimethyl-4-methylene, and 1,4,7-tetramethyldecahydro-1H-cyclopropa[e]azulen-4-ol with enoyl-[acyl-carrier-protein] reductase [NADPH]. Geometry optimization, coupled with Density Functional Theory (DFT), can be employed to assess the importance of quantum chemical descriptors in elucidating potential antibacterial activity. Quantum descriptors were computed based on E HOMO and E LUMO. The results of this study provide important insights into the potential use of Satureja candidissima (Munby) Briq EO as antibacterial agent. Communicated by Ramaswamy H. Sarma

DFT and MCDS Outcome for a Comparative Analysis of NO, NO2, SO, SO2 and SO3 Gas Adsorption onto a NaMgPO4 (033) Surface

The research purpose of this work is to examine the adsorption interaction of gaseous molecules (GMs), such as NO, NO2, SO, SO2, and SO3, with the surface of sodium magnesium phosphate NaMgPO4 (033), in a neutral medium, using two different computational methods: density functional theory (DFT) and Monte Carlo dynamic simulation (MCDS). Various quantum and dynamic descriptors, such as global and local quantum descriptors and the radial distribution function (RDF), are also evaluated and discussed. The data obtained revealed that the NO2 molecule has a small energy gap (0.363 eV) when compared to the other molecules, which means that it is highly reactive and is liable to adsorb, or stick, to the surface of NaMgPO4 (033). Furthermore, this NO2 molecule exhibits good adsorption in aqueous media, returning to the lowest global hardness value (0.1815 eV). MCDS predicted adsorption energies of −874.03, −819.94, −924.81, −876.33, and −977.71 kcal/mol for NO, NO2, SO, SO2, and SO3, respectively. These energies are negative, implying that adsorption occurs spontaneously. Thus, the side views indicated which SO, NO, and SO3 molecules are adsorbed in parallel to NaMgPO4 and the other SO2 and NO2 molecules are adsorbed horizontally. Eventually, the theoretical results reveal that the studied gaseous molecules interact strongly with NaMgPO4. The result obtained by radial distribution function (RDF) analysis for all complexes below 3.5 Å confirm that the adsorption is of the chemi1cal type.

Study of new carbonitrile as an anti-muscular dystrophy agent: Crystal, vibrational spectroscopy, molecular docking, electronic and intermolecular interaction investigations by the DFT method

Muscular dystrophy, a genetically induced and highly lethal disease, necessitates urgent curative solutions. Many therapeutic drugs for this condition incorporate heterocyclic compounds. This study presents the synthesis, spectral analysis (FT-IR, 1HNMR , 13CNMR , HSQC, Mass), X-ray crystallography, molecular structure examination, electronic properties, and in-silico investigations of 3-((4-nitrophenyl)(p-tolylamino)methyl)-1H-indole-5-carbonitrile (TNIC) as a potent anti-muscular dystrophy drug. Density function theory (DFT) at the B3LYP-D3(BJ)/6-311++ (2d, 2p) level provided geometric and reactivity parameters. Computational studies explored natural bond orbitals, nonlinear optics properties, frontier molecular orbitals, quantum descriptors, and molecular electrostatic potential. Calculated wavelengths closely matched experimental values for TNIC. Molecular docking results indicated anti-muscle dystrophy effects against muscle dystrophy proteins (2VD5 and 2KKQ) with binding energies of −8.5 kcal/mol and −8.2 kcal/mol, surpassing the standard drug Deflazacort. This study highlights TNIC's significant biological activity against muscular dystrophy.

Experimental and theoretical investigations of the effect of bis-phenylurea-based aliphatic amine derivative as an efficient green corrosion inhibitor for carbon steel in HCl solution

A novel bis-phenylurea-based aliphatic amine (BPUA) was prepared via a facile synthetic route, and evaluated as a potential green organic corrosion inhibitor for carbon steel in 1.0 M HCl solutions. NMR spectroscopy experiments confirmed the preparation of the targeted structure. The corrosion inhibitory behavior of the prospective green compound was explored experimentally by electrochemical methods and theoretically by DFT-based quantum chemical calculations. Obtained results revealed an outstanding performance of BPUA, with efficiency of 95.1% at the inhibitor concentration of 50 mg L−1 at 25 °C. The novel compound has improved the steel resistivity and noticeably reduced the corrosion rate from 33 to 1.7 mils per year. Furthermore, the adsorption study elucidates that the mechanism of the corrosion inhibition activity obeys Langmuir isotherm with mixed physisorption/chemisorption modes for BPUA derivatives on the steel surface. Calculated Gibb's free energy of the adsorption process ranges from −35 to −37 kJ mol−1.The SEM morphology analysis validates the electrochemical measurements and substantiates the corrosion-inhibiting properties of BPUA. Additionally, the eco-toxicity assessment on human epithelial MCF-10A cells proved the environmental friendliness of the BPUA derivatives. Density functional theory (DFT) calculations correlated the inhibitor's chemical structure with the corresponding inhibitory behavior. Quantum descriptors disclosed the potentiality of BPUA adsorption onto the surface through the heteroatom-based functional groups and aromatic rings.

Elucidating the efficacy of plant-derived triterpenoids for treating urinary tract infections: insights from experimental investigation, quantum chemical analysis, and molecular docking

Abstract Urinary tract infections persist as recurring maladies in human health, triggered by diverse bacterial species. The rise of antibiotic resistance necessitates novel therapeutic agents. This investigation delves into the experimental and theoretical exploration of three compounds—Methyl ganoderate B (A1), 12-acetoxy-15-hydroxy-3,7,11,23-tetraoxolanost-8-en-26-oic acid (A2), and 15-hydroxy-3,7,11,23-tetraoxolanost-8,20-dien-26-oic acid (A3)—via Density Functional Theory (DFT). Leveraging geometrical optimization, spectroscopic (FT-IR, LC–MS) analysis, electronic property studies in polar (water) and non-polar (cyclohexane) solvents, we uncover their solvent-dependent stability and reactivity. Quantum descriptors reveal A1’s elevated reactivity (−7.113 eV energy gap), while A2 showcases enhanced stability (−4.981 eV energy gap). Molecular docking investigations employing significant Escherichia coli adhesion proteins (PDB: 5LNE and 5LNE) spotlight the compounds’ superior binding affinities over the standard drug (sulfamethoxazole). ADMET studies unveil the compounds’ enhanced druglikeness against E. coli-caused urinary tract infections. Notably, predicted toxicity evaluation assigns A1, A2, and A3 LD50 values of 5000 mg/kg, 6802 mg/kg, and 500 mg/kg, respectively, aligning with toxicity classes 5, 6, and 4. Demonstrating non-hepatotoxic, non-cytotoxic, non-carcinogenic, and non-mutagenic attributes, this study underlines the substantial potential of the investigated compounds as robust agents against urinary tract infections.

QSAR, DFT studies, docking molecular and simulation dynamic molecular of 2-styrylquinoline derivatives through their anticancer activity

In this study, a 2D-QSAR (quantitative structure–activity relationship) was performed on 54 new 2-Styrylquinoline derivatives as anticancer substances capable of inhibiting the p53 protein in the cell HCT116++. The 54 2-Styrylquinoline derivatives was calculated applying DFT 6-31G basis to calculate Quantum descriptors, using MM2 for: Topological, Physico-chemical, Geometrical and Constitutional. The study was carried out by performing multiple linear regression (R2 = 0.90), the QSAR model achieved was tested by artificial neural networks method, which is showed high predictability (R2ANN = 0.89). A DFT study was performed to determine the reactivity of the 2-Styrylquinoline derivatives using frontier molecular orbital analysis and analysis of the molecular electrostatic potential (MEP). Derivatives of 2–4 Styrylquinoline are studied for their synthetic accessibility and their similarity to drug. The obtained results show that all the evaluated compounds have similar properties to drug and are accessible to synthesize.A molecular docking analysis was performed for three compounds: 14, 34, and 54, having various reactivities against the p53 HCT116++ protein (identified by PDB ID: 2GEQ). The results showed strong interactions between the three ligands and the 2GEQ protein, the amino acids HIS 176, SER A180, PRO A188 and ARG A178 are the most active sites of the 2GEQ protein, and based on these result we performed a molecular dynamics simulation to evaluate the stability of our complexes. The MD demonstrates the thermodynamic stability of select compounds during 40 and 100 ns, with all three complexes showing a high level of structural stability.

Fragments quantum descriptors in classification of bio-accumulative compounds

The aim of the following research is to assess the applicability of calculated quantum properties of molecular fragments as molecular descriptors in machine learning classification task. The research is based on bio-concentration and QM9-extended databases. A number of compounds with results from quantum-chemical calculations conducted with Psi4 quantum chemistry package was also added to the quantum properties database. Classification results are compared with a baseline of random guesses and predictions obtained with the traditional RDKit generated molecular descriptors. Chosen classification metrics show that results obtained with fragments quantum descriptors fall between results from baseline and those provided by molecular descriptors widely applied in cheminformatics. According to the results, the implementation of principal component analysis, causes a drop in categorization metrics.

Corrosion inhibitory characteristics, thermodynamics, and theoretical studies of N-((2-aminoethyl) carbamothioyl) acrylamide for carbon steel in 1 M HCl

Green synthesis has become very significant for sustainable development and health concern. The multicomponent is applied as an eco-friendly procedure to synthesize N-((2-aminoethyl) carbamothioyl) acrylamide (ACA). The structure of ACA is verified using FTIR and 1HNMR spectroscopy. The inhibitory effect of ACA for carbon steel in 1 M HCl is assessed using electrochemical measurements and weight loss. The Langmuir adsorption isotherm model fits the inhibitive effect caused by adsorption on the metal surface. Additionally, the surface morphology is examined using SEM and AFM. The photos demonstrate a smoothing of the protective surface and a 0.45 nm reduction in average roughness. Different quantum descriptors using DFT theory were calculated and found to be corroborated with the experimental results. By creating successive resistive adsorption films, the ACA, at a concentration of 10−3 M, protects the carbon steel in 1MHCl with a 97% efficiency as a mixed-type inhibitor.

Quantum Descriptors for Predicting and Understanding the Structure-Activity Relationships of Michael Acceptor Warheads.

Predictive modeling and understanding of chemical warhead reactivities have the potential to accelerate targeted covalent drug discovery. Recently, the carbanion formation free energies as well as other ground-state electronic properties from density functional theory (DFT) calculations have been proposed as predictors of glutathione reactivities of Michael acceptors; however, no clear consensus exists. By profiling the thiol-Michael reactions of a diverse set of singly- and doubly-activated olefins, including several model warheads related to afatinib, here we reexamined the question of whether low-cost electronic properties can be used as predictors of reaction barriers. The electronic properties related to the carbanion intermediate were found to be strong predictors, e.g., the change in the Cβ charge accompanying carbanion formation. The least expensive reactant-only properties, the electrophilicity index, and the Cβ charge also show strong rank correlations, suggesting their utility as quantum descriptors. A second objective of the work is to clarify the effect of the β-dimethylaminomethyl (DMAM) substitution, which is incorporated in the warheads of several FDA-approved covalent drugs. Our data suggest that the β-DMAM substitution is cationic at neutral pH in solution and promotes acrylamide's intrinsic reactivity by enhancing the charge accumulation at Cα upon carbanion formation. In contrast, the inductive effect of the β-trimethylaminomethyl substitution is diminished due to steric hindrance. Together, these results reconcile the current views of the intrinsic reactivities of acrylamides and contribute to large-scale predictive modeling and an understanding of the structure-activity relationships of Michael acceptors for rational TCI design.

QSAR modeling of pyrazoline derivative as carbonic anhydrase inhibitors.

The efficacy of 34 pyrazoline derivatives as carbonic anhydrase inhibitors was studied in silico. The quantum descriptors were calculated by the DFT/B3LYP method using the 6-31G(d) basis; the dataset was randomly divided into training and testing. By altering the compounds in the sets, four models were created, and they were then used to determine the predicted pIC50 values for the six chemicals in the test set. According to the OECD guidelines for QSAR model validation and the Golbraikh and Tropsha's criteria for model approval, each created model was independently validated both internally and externally, along with YRandomization. Model 3 is chosen because it has higher R2, R2test, and Q2cv values (R2 = 0.79, R2test = 0.95, Q2cv = 0.64). Only one descriptor has a proportional influence on pIC50 activity, but the other four descriptors have an inverse influence on pIC50 because of the negative contribution coefficient. Given the descriptors of the model, we could propose new molecules with remarkable inhibitory activity.

Quantum chemical studies, spectroscopic NMR and FT-IR analysis, and molecular docking investigation of 3,3′-di-O-methyl ellagic acid (DMA) as a potent Mycobacterium tuberculosis agent

Tuberculosis which is mainly caused by Mycobacterium tuberculosis remains of public health importance due to the resistance of the causative pathogen to the present antibiotics used as treatment options. This resistance has led to the need for the discovery of new treatment options. Herein, the isolation, geometrical optimization, spectroscopic NMR and FT-IR analysis, a study of weak interactions, electronic properties, and the in-silico biological activity of 3,3′-di-O-methyl ellagic acid (DMA) were determined. In addition, the effect of solvent on the kinetic stability, reactivity, and other electronic properties of DMA was determined in three solvents; DMSO, methanol, and water. Also, the biological activity potential and the drug-likeness of DMA were determined using molecular docking protocol and ADMET studies. The studied compound was isolated using column and thin-layer chromatography techniques while characterization was done using spectroscopic techniques. Key vibrations in the compound are C = O vibrations, C = C vibrations, C-H vibrations, –CH3 vibrations, and O-H vibrations. A study of quantum descriptors revealed that DMA is more reactive in water with an energy gap of −3.162 eV and those in three solvents are −3.163, −3.944, and −4.3022 eV in methane, gas, and water respectively. The compound shows great optical potentials with dipole moments of 3.2415D, 5.221D, 5.2015D, and 4.469D in water, DMSO, methanol, and Gas-phase respectively which are greater than that of urea used in the comparison. The QTAIM analysis based on the bond ellipticity < 0.5 suggests the presence of covalent bonds within the atoms of the studied compound. The MESP result shows the presence of π- H bond interaction within the OCH3 and oxygen atom. Molecular docking studies of the studied compound were carried out employing proteins 1W2G, 1YWF, and 1F0N proteins for mycobacterial tuberculosis and the standard drug isoniazid. The result was compared with that of a standard drug. The binding affinities of −7.1, −6.9, and −7.1 kcal/mol for 1W2G, 1YWF, and 1F0N were obtained, and −5.9, −5.9 and −6.0 kcal/mol for the standard drug with 1W2G, 1YWF and 1F0N. These results show that the studied compound has greater biological activity against these proteins as compared to the standard drug. ADMET studies show that the studied compound has great drug-likeness and bioavailability since it did not violate any of Lipinski’s rule of five.