Search Results (23)

A comprehensive analysis of key findings derived from density functional theory (DFT) studies reveals that current theoretical data on curcumin remain incomplete, underscoring the need for further computational investigation to achieve a more thorough understanding of its chemical and biological reactivity. This study addresses these gaps through four primary objectives: (i) determination of a complete set of thermodynamic descriptors and elucidation of the multi-step anti-radical mechanisms of the neutral, radical, anionic, and radical–anionic forms of curcumin; (ii) calculation of global chemical reactivity descriptors of curcumin in various solvent environments; (iii) theoretical reproduction of experimentally determined pK_a values for all active sites within the molecule; and (iv) examination of the effects of dispersion interactions and solvent polarity on the reactivity descriptors of keto–enol forms of curcumin. The results obtained provide enhanced insight into the molecular behavior of curcumin, facilitating improved predictions of its reactivity under diverse conditions. Moreover, the findings indicate a potential structural modification of the keto form of curcumin, involving the attachment of two 4-hydroxy-3-methoxyphenyl-prop-1-en-2-one moieties to the methylene group. The resulting modeled compound, referred to as di-curcumin, exhibits enhanced chemical reactivity and increased anti-radical potential. Full article

This study investigates the structural and energetic properties of hydrogen-bonded complexes between indole and a range of aliphatic, cyclic, and aromatic ketones using a combined vibrational spectroscopic and quantum-chemical approach. FTIR measurements in CCl₄ revealed redshifts in the N-H stretching vibration of indole upon complexation, with formation constants (K_a) ranging from 0.3 to 6.6 M⁻¹. Cyclohexanone displayed the strongest binding, while benzophenone exhibited the weakest interaction. Quantum-chemical calculations, employing CREST and MMFF94 conformational sampling, along with M06-2X/6-311++G(d,p) optimizations, confirmed the formation of hydrogen bonds and additional weak interactions that govern the stability of the complex. QTAIM analysis revealed moderate closed-shell hydrogen bonds with electron densities at the bond critical points (ρ) ranging from 0.010 to 0.019 a.u. and potential energy densities (V) from −18.4 to −36.4 kJ mol⁻¹. Multivariate regression analysis established strong correlations (R² = 0.928 and 0.957) between experimental binding constants and theoretical descriptors, including binding energy, NBO charge on oxygen atom, ionization potential, and electrophilicity index, highlighting the interplay between geometric, electronic, and global reactivity factors. This comprehensive study underlines the predictive power of spectroscopic and quantum descriptors for assessing hydrogen bonding in biologically relevant systems. Full article

Kapakahines A–G are natural products isolated from the marine sponge Carteriospongia sp., characterized by complex molecular architectures composed of fused rings and diverse functional groups. Preliminary studies have indicated that some of these peptides may exhibit cytotoxic and antitumor activities, which has prompted interest in further exploring their chemical and pharmacokinetic properties. Computational chemistry—particularly Conceptual Density Functional Theory (CDFT)-based Computational Peptidology (CP)—offers a valuable framework for investigating such compounds. In this study, the CDFT-CP approach is applied to analyze the structural and electronic properties of Kapakahines A–G. Alongside the calculation of global and local reactivity descriptors, predicted ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiles and pharmacokinetic parameters, including pKa and LogP, are evaluated. The integrated computational analysis provides insights into the stability, reactivity, and potential drug-like behavior of these marine-derived cyclopeptides and contributes to the theoretical groundwork for future studies aimed at optimizing their bioactivity and safety profiles. Full article

The aim of this study was to compare the physical, sensorial, and microstructural properties of selected meat products with their plant-based alternatives to assess how closely the alternatives mimic the original products. Six meat analogue products, including Frankfurter sausage (SuA), steak (StA), Hungarian sausage (KA), minced meat (MA), salami (SaA), and burger (BA), were compared with their corresponding meat products (SuM, StM, KM, MM, SaM, and BM, respectively). The study measured colour indicators, texture parameters, sensory attributes, and microstructural properties. The redness values (a*) of the external surfaces of SuM and KM, as well as the hardness of MM, were similar to those of their alternative products, with no statistically significant differences (p > 0.05). Sensory evaluation revealed similar ratings for two attributes: product similarity and overall appearance. However, significant differences were found in the descriptors for animal character and meat taste. Full article

The development of organelle-specific fluorescent probes has been impeded by the absence of a comprehensive understanding of the relationship between the physicochemical properties of fluorescent probes and their selectivity towards specific organelles. Although a few machine learning models have suggested several physicochemical parameters that control the target organelle of the probes and have attempted to predict the target organelles, they have been challenged by low accuracy and a limited range of applicable organelles. Herein, we report a multi-organelle prediction QSAR model that is capable of predicting the destination of probes among nine categories, including cytosol, endoplasmic reticulum, Golgi body, lipid droplet, lysosome, mitochondria, nucleus, plasma membrane, and no entry. The model is trained using the Random Forest algorithm with a dataset of 350 organelle-specific fluorescent probes and 786 descriptors, and it is able to predict the target organelles of fluorescent probes with an accuracy of 75%. The MDI analysis of the model identifies 38 key parameters that have a significant impact on the organelle selectivity of the probes, including LogD, pKa, hydrophilic-lipophilic balance (HLB), and topological polar surface area (TPSA). This prediction model may be useful in developing new organelle-specific fluorescent probes by providing crucial variables that determine the destination of the probes. Full article

Betanidin (Bd) is a nitrogenous metabolite with significant bioactive potential influenced by pH. Its free radical scavenging activity and deprotonation pathway are crucial to studying its physicochemical properties. Motivated by the published discrepancies about the best deprotonation routes in Bd, this work explores all possible pathways for proton extractions on that molecule, by using the direct approach method based on pK_a. The complete space of exploration is supported by a linear relation with constant slope, where the pK_a is written in terms of the associated deprotonated molecule energy. The deprotonation rounds 1, …, 6 define groups of parallel linear models with constant slope. The intercepts of the models just depend on the protonated energy for each round, and then the pK_a can be trivially ordered and explained by the energy. We use the direct approximation method to obtain the value of pK_a. We predict all possible outcomes based on a linear model of the energy and some related verified assumptions. We also include a new measure of similarity or dissimilarity between the protonated and deprotonated molecules, via a geometric–chemical descriptor called the Riemann–Mulliken distance (RMD). The RMD considers the cartesian coordinates of the atoms, the atomic mass, and the Mulliken charges. After exploring the complete set of permutations, we show that the successive deprotonation process does not inherit the local energy minimum and that the commutativity of the paths does not hold either. The resulting clusterization of pK_a can be explained by the local acid and basic groups of the BD, and the successive deprotonation can be predicted by using the chemical explained linear models, which can avoid unnecessary optimizations. Another part of the research uses our own algorithm based on shape theory to determine the protein’s active site automatically, and molecular dynamics confirmed the results of the molecular docking of Bd in protonated and anionic form with the enzyme aldose reductase (AR). Also, we calculate the descriptors associated with the SET and SPLET mechanisms. Full article

Pyrite has been used in photo-Fenton reactions for the degradation of pollutants, but the application of photo-Fenton processes with extra H₂O₂ in real water/wastewater treatment has still been limited by the economic cost of H₂O₂ and artificial light sources. Herein, citric acid (CA) and simulated/natural sunlight are used to develop a pyrite-based photo-Fenton system (pyrite–CA–light) in situ generating H₂O₂ through the enhanced activation of molecular oxygen. The degradation of pharmaceuticals and personal care products (PPCPs), especially acetaminophen (APAP) as the main target pollutant, in the pyrite–CA–light system was investigated. The effects of influencing factors such as various organic acids, APAP concentration, pH, pyrite dosage, CA concentration and co-existing anions (HCO₃⁻, Cl⁻, NO₃⁻, SO₄²⁻ and H₂PO₄⁻) were examined. At a pyrite dosage of 0.1 g L⁻¹, CA concentration of 0.6 mM and an initial pH of 6.0, the degradation efficiency of APAP (30 μM) was 99.1% within 30 min under the irradiation of xenon lamp (70 W, λ ≥ 350 nm). Almost the same high efficiency of APAP degradation (93.9%) in the system was achieved under natural sunlight irradiation (ca. 650 W m⁻²). The scavenging experiments revealed that the dominant active species for degrading APAP was hydroxyl radical (HO^•). Moreover, a quantitative structural–activity relationship (QSAR) model for pseudo-first-order rate constants (k_obs) was established with a high significance (R² = 0.932, p = 0.001) by using three descriptors: octanol–water partition coefficient (logKow), dissociation constant (pK_a) and highest occupied molecular orbital (HOMO). This work provides an innovative strategy of the photo-Fenton process for the degradation of PPCPs using natural minerals and ordinary carboxylic acid under sunlight. Full article

Electrochemical reduction of CO₂ to value-added chemicals has been hindered by poor product selectivity and competition from hydrogen evolution reactions. This study aims to unravel the origin of the product selectivity and competitive hydrogen evolution reaction on [MP]⁰ catalysts (M = Fe, Co, Rh and Ir; P is porphyrin ligand) by analyzing the mechanism of CO₂ reduction and H₂ formation based on the results of density functional theory calculations. Reduction of CO₂ to CO and HCOO⁻ proceeds via the formation of carboxylate adduct ([MP-COOH]⁰ and ([MP-COOH]⁻) and metal-hydride [MP-H]⁻, respectively. Competing proton reduction to gaseous hydrogen shares the [MP-H]⁻ intermediate. Our results show that the pK_a of [MP-H]⁰ can be used as an indicator of the CO or HCOO⁻/H₂ preference. Furthermore, an ergoneutral pH has been determined and used to determine the minimum pH at which selective CO₂ reduction to HCOO⁻ becomes favorable over the H₂ production. These analyses allow us to understand the product selectivity of CO₂ reduction on [FeP]⁰, [CoP]⁰, [RhP]⁰ and [IrP]⁰; [FeP]⁰ and [CoP]⁰ are selective for CO whereas [RhP]⁰ and [IrP]⁰ are selective for HCOO⁻ while suppressing H₂ formation. These descriptors should be applicable to other catalysts in an aqueous medium. Full article

A study of 250 commercial drugs to act as corrosion inhibitors on steel has been developed by applying the quantitative structure-activity relationship (QSAR) paradigm. Hard-soft acid-base (HSAB) descriptors were used to establish a mathematical model to predict the corrosion inhibition efficiency (IE%) of several commercial drugs on steel surfaces. These descriptors were calculated through third-order density-functional tight binding (DFTB) methods. The mathematical modeling was carried out through autoregressive with exogenous inputs (ARX) framework and tested by fivefold cross-validation. Another set of drugs was used as an external validation, obtaining SD, RMSE, and MSE, obtaining 6.76%, 3.89%, 7.03%, and 49.47%, respectively. With a predicted value of IE% = 87.51%, lidocaine was selected to perform a final comparison with experimental results. By the first time, this drug obtained a maximum IE%, determined experimentally by electrochemical impedance spectroscopy measurements at 100 ppm concentration, of about 92.5%, which stands within limits of 1 SD from the predicted ARX model value. From the qualitative perspective, several potential trends have emerged from the estimated values. Among them, macrolides, alkaloids from Rauwolfia species, cephalosporin, and rifamycin antibiotics are expected to exhibit high IE% on steel surfaces. Additionally, IE% increases as the energy of HOMO decreases. The highest efficiency is obtained in case of the molecules with the highest ω and ΔN values. The most efficient drugs are found with pK_a ranging from 1.70 to 9.46. The drugs recurrently exhibit aromatic rings, carbonyl, and hydroxyl groups with the highest IE% values. Full article

Bioactive peptides are chemical compounds created through the covalent bonding of amino acids, known as amide or peptide bonds. Due to their unusual chemistry and various biological effects, marine bioactive peptides have garnered considerable research. The effectiveness of a bioactive marine peptide is attributed to its structural features, such as amino acid content and sequence, which vary depending on the degree of action. Cyclic peptides combine several favorable properties such as good binding affinity, target selectivity and low toxicity that render them an attractive modality for the development of therapeutics. The apratoxins are a class of molecules formed by a series of cyclic depsipeptides with potent cytotoxic activities. The objective of this research is to pursue a computational prospection of the molecular structures and properties of several cylopeptides of marine origin with potential therapeutic applications. The methodology will be based on the determination of the chemical reactivity descriptors of the studied molecules through the consideration of the Conceptual DFT model and validation of a particular model chemistry, MN12SX/Def2TZVP/H₂O. These studies will be complemented by a determination of the pharmacokinetics and ADMET parameters by resorting to certain cheminformatics tools. Full article

As a continuation of our research on the chemical reactivity, pharmacokinetics and ADMET properties of cyclopeptides of marine origin with potential therapeutic abilities, in this work our already presented integrated molecular modeling protocol has been used for the study of the chemical reactivity and bioactivity properties of the Veraguamides A–G family of marine natural drugs. This protocol results from the estimation of the conceptual density functional theory (CDFT) chemical reactivity descriptors together with several chemoinformatics tools commonly considered within the process of development of new therapeutic drugs. CP-CDFT is a branch of computational chemistry and molecular modeling dedicated to the study of peptides, and it is a protocol that allows the estimation with great accuracy of the CDFT-based reactivity descriptors and the associated physical and chemical properties, which can aid in determining the ability of the studied peptides to behave as potential useful drugs. Moreover, the superiority of the MN12SX density functional over other long-range corrected density functionals for the prediction of chemical and physical properties in the presence of water as the solvent is clearly demonstrated. The research was supplemented with an investigation of the bioactivity of the molecular systems and their ADMET (absorption, distribution, metabolism, excretion, and toxicity) parameters, as is customary in medicinal chemistry. Some instances of the CDFT-based chemical reactivity descriptors’ capacity to predict the pKas of peptides as well as their potential as AGE inhibitors are also shown. Full article

It is interesting to know the behavior of Protic Ionic Liquids (PILs) within the binary mixture of molecular solvents, since it is usual to carry out processes such as organic and inorganic synthesis, or liquid–liquid extractions in the presence of another solvent. Moreover, on certain occasions, the absence of water is strictly required. In this sense, it is important to note that the addition of small amounts of IL to the molecular solvent allows a fine adjustment in its microscopic properties, obtaining “new solvent systems” with particular properties. The solvatochromic dyes are traditionally used as microscopic descriptors to determine the molecular microscopic properties of solvents, so we aim to re-evaluate the behavior of these probes and reconsider the validity of traditional polarity scales such as E_T(30) in alkylammonium-based PILs, as well as in their mixtures with molecular solvents, knowing that the real composition of these PILs depends on the equilibrium of autoprotolysis. The characterization of systems was completed in terms of a change in the ∆pKa of the precursor species of a PIL. A thermal analysis was also employed to determine the acid strength’s role in an ion’s complete formation in pure PILs. Full article

In the case of foliar area studies on vines, with a large number of determinations, a simple, fast, sufficiently accurate and low-cost method is very useful. The typology of leaves on the vine is complex, characterized by several descriptive parameters: median rib; secondary venations of the first and second order; angles between the median rib and the secondary venations; sinuses; length and width of the leaf. The present study aimed to evaluate models for calculating the leaf area based on descriptive parameters and KA (KA as the surface constant used to calculate the leaf area) for six vine cultivars, ‘Cabernet Sauvignon’ (CS), ‘Muscat Iantarnîi’ (MI), ‘Muscat Ottonel’ (MO), ‘Chasselas’ (Ch), ‘Victoria’ (Vi) and ‘Muscat Hamburg’ (MH). The determined KA surface constants had subunit values (0.91 to 0.97), except for the cultivars ‘Muscat Iantarnîi’ and ‘Muscat Ottonel’ where the surface constant KA₂ (in relation to the second-order secondary venations) had supraunitary values (1.07 and 1.08, respectively). The determination of the leaf area was possible under different conditions of statistical accuracy (R² = 0.477, p = 0.0119, up to R² = 0.988, p < 0.001) in relation to the variety and parametric descriptors considered. The models obtained from the regression analysis facilitated a more reliable prediction of the leaf area based on the elements on the left side of the leaf, in relation to the median rib, compared to those on the right. The accuracy of the results was checked on the basis of minimum error (ME) and confirmed by parameters R², p and RMSE. Full article

Tuberculosis (TB) is a major global threat, mostly due to the development of antibiotic-resistant forms of Mycobacterium tuberculosis, the causal agent of the disease. Driven by the pressing need for new anti-mycobacterial agents several natural products (NPs) have been shown to have in vitro activities against M. tuberculosis. The utility of any NP as a drug lead is augmented when the anti-mycobacterial target(s) is unknown. To suggest these, we used a molecular reverse docking approach to predict the interactions of 53 selected anti-mycobacterial NPs against known “druggable” mycobacterial targets ClpP1P2, DprE1, InhA, KasA, PanK, PknB and Pks13. The docking scores/binding free energies were predicted and calculated using AutoDock Vina along with physicochemical and structural properties of the NPs, using PaDEL descriptors. These were compared to the established inhibitor (control) drugs for each mycobacterial target. The specific interactions of the bisbenzylisoquinoline alkaloids 2-nortiliacorinine, tiliacorine and 13′-bromotiliacorinine against the targets PknB and DprE1 (−11.4, −10.9 and −9.8 kcal·mol⁻¹; −12.7, −10.9 and −10.3 kcal·mol⁻¹, respectively) and the lignan α-cubebin and Pks13 (−11.0 kcal·mol⁻¹) had significantly superior docking scores compared to controls. Our approach can be used to suggest predicted targets for the NP to be validated experimentally, but these in silico steps are likely to facilitate drug optimization. Full article

A methodology based on the concepts that arise from Density Functional Theory named Conceptual Density Functional Theory (CDFT) was chosen for the calculation of some global and local reactivity descriptors of the Discodermins A–H family of marine peptides through the consideration of the KID (Koopmans in DFT) technique that was successfully used in previous studies of this kind of molecular systems. The determination of active sites of the studied molecules for different kinds of reactivities was achieved by resorting to some CDFT-based descriptors like the Fukui functions as well as the Parr functions derived from Molecular Electron Density Theory (MEDT). A few properties identified with their ability to behave as a drug and the bioactivity of the peptides considered in this examination were acquired by depending on a homology model by studying the correlation with the known bioactivity of related molecules in their interaction with various biological receptors. With the further object of analyzing their bioactivity, some parameters of usefulness for future QSAR studies, their predicted biological targets, and the ADME (Absorption, Distribution, Metabolism, and Excretion) parameters related to the Discodermins A–H pharmacokinetics are also reported. Full article