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Urease, a pivotal enzyme in nitrogen metabolism, plays a crucial role in various microorganisms, including the pathogenic Helicobacter pylori. Inhibiting urease activity offers a promising approach to combating infections and associated ailments, such as chronic kidney diseases and gastric cancer. However, identifying potent urease inhibitors remains challenging due to resistance issues that hinder traditional approaches. Recently, machine learning (ML)-based models have demonstrated the ability to predict the bioactivity of molecules rapidly and effectively. In this study, we present ML models designed to predict urease inhibitors by leveraging essential physicochemical properties. The methodological approach involved constructing a dataset of urease inhibitors through an extensive literature search. Subsequently, these inhibitors were characterized based on physicochemical properties calculations. An exploratory data analysis was then conducted to identify and analyze critical features. Ultimately, 252 classification models were trained, utilizing a combination of seven ML algorithms, three attribute selection methods, and six different strategies for categorizing inhibitory activity. The investigation unveiled discernible trends distinguishing urease inhibitors from non-inhibitors. This differentiation enabled the identification of essential features that are crucial for precise classification. Through a comprehensive comparison of ML algorithms, tree-based methods like random forest, decision tree, and XGBoost exhibited superior performance. Additionally, incorporating the "chemical family type" attribute significantly enhanced model accuracy. Strategies involving a gray-zone categorization demonstrated marked improvements in predictive precision. This research underscores the transformative potential of ML in predicting urease inhibitors. The meticulous methodology outlined herein offers actionable insights for developing robust predictive models within biochemical systems.
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Inibidores Enzimáticos , Aprendizado de Máquina , Urease , Urease/antagonistas & inibidores , Urease/química , Urease/metabolismo , Inibidores Enzimáticos/química , Inibidores Enzimáticos/farmacologia , Helicobacter pylori/enzimologia , Helicobacter pylori/efeitos dos fármacos , Algoritmos , HumanosRESUMO
Thyroxine (T4) is a drug extensively utilized for the treatment of hypothyroidism. However, the oral absorption of T4 presents certain limitations. This research investigates the efficacy of CO2 nanobubbles in water as a potential oral carrier for T4 administration to C57BL/6 hypothyroid mice. Following 18 h of fasting, the formulation was administered to the mice, demonstrating that the combination of CO2 nanobubbles and T4 enhanced the drug's absorption in blood serum by approximately 40%. To comprehend this observation at a molecular level, we explored the interaction mechanism through which T4 engages with the CO2 nanobubbles, employing molecular simulations, semi-empirical quantum mechanics, and PMF calculations. Our simulations revealed a high affinity of T4 for the water-gas interface, driven by additive interactions between the hydrophobic region of T4 and the gas phase and electrostatic interactions of the polar groups of T4 with water at the water-gas interface. Concurrently, we observed that at the water-gas interface, the cluster of T4 formed in the water region disassembles, contributing to the drug's bioavailability. Furthermore, we examined how the gas within the nanobubbles aids in facilitating the drug's translocation through cell membranes. This research contributes to a deeper understanding of the role of CO2 nanobubbles in drug absorption and subsequent release into the bloodstream. The findings suggest that utilizing CO2 nanobubbles could enhance T4 bioavailability and cell permeability, leading to more efficient transport into cells. Additional research opens the possibility of employing lower concentrations of this class of drugs, thereby potentially reducing the associated side effects due to poor absorption.
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Dióxido de Carbono , Modelos Animais de Doenças , Hipotireoidismo , Tiroxina , Água , Animais , Hipotireoidismo/tratamento farmacológico , Hipotireoidismo/metabolismo , Camundongos , Dióxido de Carbono/química , Água/química , Camundongos Endogâmicos C57BL , Administração Oral , Nanopartículas/química , Portadores de Fármacos/químicaRESUMO
Pseudomonas aeruginosa (P. aeruginosa) poses a significant threat as a nosocomial pathogen due to its robust resistance mechanisms and virulence factors. This study integrates subtractive proteomics and ensemble docking to identify and characterize essential proteins in P. aeruginosa, aiming to discover therapeutic targets and repurpose commercial existing drugs. Using subtractive proteomics, we refined the dataset to discard redundant proteins and minimize potential cross-interactions with human proteins and the microbiome proteins. We identified 12 key proteins, including a histidine kinase and members of the RND efflux pump family, known for their roles in antibiotic resistance, virulence, and antigenicity. Predictive modeling of the three-dimensional structures of these RND proteins and subsequent molecular ensemble-docking simulations led to the identification of MK-3207, R-428, and Suramin as promising inhibitor candidates. These compounds demonstrated high binding affinities and effective inhibition across multiple metrics. Further refinement using non-covalent interaction index methods provided deeper insights into the electronic effects in protein-ligand interactions, with Suramin exhibiting superior binding energies, suggesting its broad-spectrum inhibitory potential. Our findings confirm the critical role of RND efflux pumps in antibiotic resistance and suggest that MK-3207, R-428, and Suramin could be effectively repurposed to target these proteins. This approach highlights the potential of drug repurposing as a viable strategy to combat P. aeruginosa infections.
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Antibacterianos , Proteínas de Bactérias , Reposicionamento de Medicamentos , Simulação de Acoplamento Molecular , Proteoma , Proteômica , Pseudomonas aeruginosa , Pseudomonas aeruginosa/efeitos dos fármacos , Pseudomonas aeruginosa/metabolismo , Proteínas de Bactérias/metabolismo , Proteínas de Bactérias/química , Proteínas de Bactérias/antagonistas & inibidores , Proteômica/métodos , Proteoma/metabolismo , Antibacterianos/farmacologia , Antibacterianos/química , Suramina/farmacologia , Suramina/química , HumanosRESUMO
When (4n +2) π-electrons are located in single planar ring, it conventionally qualifies as aromatic. According Hückel's rule, systems possessing ten π-electrons should be aromatic. Herein we report a series of D5h â Li6 E5 Li6 sandwich structures, representing the first global minima featuring ten π-electrons E5 10- ring (E=Si-Pb). However, these π-electrons localize as five π-lone-pairs rather than delocalized orbitals. The high symmetry structure achieved is a direct consequence of σ-aromaticity, particularly favored in elements from Si to Pb, resulting in a pronounced diatropic ring current flow that contributes to the enhanced stability of these systems.
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Using various exploration strategies, in this study, we investigated the potential energy surfaces (PES) of CBe5H5+ and CnBe3n+2H2n+22+ (n = 2-4) clusters. Previous studies proposed that the planar pentacoordinate carbons (ppCs) were the global minima of these clusters. However, our study identified new putative global minima and competitive isomers, refuting some previous assignments. We employed several methods, including evolutive-inspired stochastic approaches guided by "chemical criteria", and ab initio molecular dynamics simulations at elevated temperatures. Our results showed that the size of the scanned population significantly affected the evolutive method and that constrained or guided procedures showed an advantage in identifying better minima for larger systems. This study demonstrated that using multiple complementary strategies can result in a wider variety of minima in a given energy range. Our findings provide valuable insights into exploring the potential energy surfaces of clusters, mainly medium-sized clusters, which could be the connections between small clusters and nanomaterials.
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DFT calculations were performed to study the effect on energetic and magnetic stability when clusters with up to 24 lithium atoms were doped with one and two atoms of yttrium. In this, the effect of the charge was considered. As a result, some stable structures were identified as possible magnetic superatoms, among them, the YLi12+ cluster with an icosahedron geometry with a spin magnetic moment of 4 bohr magnetons. The participation of yttrium in the electron density of the unpaired electrons providing magnetism in clusters was corroborated at the level of a density of states (DOS) calculation and a spin density calculation. In particular, in the Y2Li12+ superatom, it was found that the encapsulated yttrium atom participates with 35.02% and the second yttrium atom with 15.04%. These percentages, with a contribution from p orbitals, but to a greater extent by d orbitals. The complementation to these percentages is due to the participation of the s and p orbitals of the lithium atoms. In general, doping with a second yttrium atom allowed to obtain a greater amount of high magnetic moments, and considering charged clusters allowed to obtain also high magnetic moments.
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A series of 2-phenylamino-3-acyl-1,4-naphtoquinones were evaluated regarding their in vitro antiproliferative activities using DU-145, MCF-7 and T24 cancer cells. Such activities were discussed in terms of molecular descriptors such as half-wave potentials, hydrophobicity and molar refractivity. Compounds 4 and 11 displayed the highest antiproliferative activity against the three cancer cells and were therefore further investigated. The in silico prediction of drug likeness, using pkCSM and SwissADME explorer online, shows that compound 11 is a suitable lead molecule to be developed. Moreover, the expressions of key genes were studied in DU-145 cancer cells. They include genes involved in apoptosis (Bcl-2), tumor metabolism regulation (mTOR), redox homeostasis (GSR), cell cycle regulation (CDC25A), cell cycle progression (TP53), epigenetic (HDAC4), cell-cell communication (CCN2) and inflammatory pathways (TNF). Compound 11 displays an interesting profile because among these genes, mTOR was significantly less expressed as compared to control conditions. Molecular docking shows that compound 11 has good affinity with mTOR, unraveling a potential inhibitory effect on this protein. Due to the key role of mTOR on tumor metabolism, we suggest that impaired DU-145 cells proliferation by compound 11 is caused by a reduced mTOR expression (less mTOR protein) and inhibitory activity on mTOR protein.
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Antineoplásicos , Naftoquinonas , Neoplasias , Naftoquinonas/farmacologia , Simulação de Acoplamento Molecular , Linhagem Celular Tumoral , Proliferação de Células , Apoptose , Serina-Treonina Quinases TOR/metabolismo , Antineoplásicos/farmacologia , Ensaios de Seleção de Medicamentos AntitumoraisRESUMO
A low-lying structure is revealed for the CuB12 - cluster, which is bowl-shaped. It consists of a triangular CuB2 base and a B10 rim. Molecular dynamics simulations indicates its structural robustness; at an elevated temperature (600â K), the base rotates reversibly within the B10 perimeter. Chemical bonding analysis detects 2σ- and 3π-delocalized bonds, suggesting double aromaticity. This is also confirmed by two diatropic and concentric ring currents under an external magnetic field.
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Xenobiotic reductase B (XenB) catalyzes the reduction of the aromatic ring or nitro groups of nitroaromatic compounds with methyl, amino or hydroxyl radicals. This reaction is of biotechnological interest for bioremediation, the reuse of industrial waste or the activation of prodrugs. However, the structural factors that explain the binding of XenB to different substrates are unknown. Molecular dynamics simulations and quantum mechanical calculations were performed to identify the residues involved in the formation and stabilization of the enzyme/substrate complex and to explain the use of different substrates by this enzyme. Our results show that Tyr65 and Tyr335 residues stabilize the ligands through hydrophobic interactions mediated by the aromatic rings of these aminoacids. The higher XenB activity determined with the substrates 1,3,5-trinitrobenzene and 2,4,6-trinitrotoluene is consistent with the lower energy of the highest occupied molecular orbital (LUMO) orbitals and a lower energy of the homo orbital (LUMO), which favors electrophile and nucleophilic activity, respectively. The electrostatic potential maps of these compounds suggest that the bonding requires a large hydrophobic region in the aromatic ring, which is promoted by substituents in ortho and para positions. These results are consistent with experimental data and could be used to propose point mutations that allow this enzyme to process new molecules of biotechnological interest.
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Pseudomonas putida , Trinitrotolueno , Oxirredutases/metabolismo , Pseudomonas putida/metabolismo , Xenobióticos , Trinitrotolueno/química , Trinitrotolueno/metabolismo , Simulação de Dinâmica MolecularRESUMO
Here, it is shown that the M3B12 (M = Cu-Au) clusters' global minima consist of an elongated planar B12 fragment connected by an in-plane linear M3 fragment. This result is striking since this B12 planar structure is not favored in the bare cluster, nor when one or two metals are added. The minimum energy structures were revealed by screening the potential energy surface using genetic algorithms and density functional theory calculations. Chemical bonding analysis shows that the strong electrostatic interactions with the metal compensate for the high energy spent in the M3 and B12 fragment distortion. Furthermore, metals participate in the delocalized π-bonds, which infers an aromatic character to these species.
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Cromatografia Gasosa , Eletricidade EstáticaRESUMO
After exploring the potential energy surfaces of Mm CE2 p (E=S-Te, M=Li-Cs, m=2, 3 and p=m-2) and Mn CE3 q (E=S-Te, M=Li-Cs, n=1, 2, q=n-2) combinations, we introduce 38 new global minima containing a planar hypercoordinate carbon atom (24 with a planar tetracoordinate carbon and 14 with a planar pentacoordinate carbon). These exotic clusters result from the decoration of V-shaped CE2 2- and Y-shaped CE3 2- dianions, respectively, with alkali counterions. All these 38 systems fulfill the geometrical and electronic criteria to be considered as true planar hypercoordinate carbon systems. Chemical bonding analyses indicate that carbon is covalently bonded to chalcogens and ionically connected to alkali metals.
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We report the global minima structures of Li8 Si8 , Li10 Si9 , and Li12 Si10 systems, in which silicon moieties maintain structural and chemical bonding characteristics similar to those of their building blocks: the aromatic clusters Td -Li4 Si4 and C2v -Li6 Si5 . Electron counting rules, chemical bonding analysis, and magnetic response properties verify the silicon unit's aromaticity persistence. This study demonstrates the feasibility of assembling silicon-based nanostructures from aromatics clusters as building blocks.
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Here, we introduce a hybrid method, named Kick-Fukui, to explore the potential energy surface (PES) of clusters and molecules using the Coulombic integral between the Fukui functions in the first screening of the best individuals. In the process, small stable molecules or clusters whose combination has the stoichiometry of the explored species are used as assembly units. First, a small set of candidates has been selected from a large and stochastically generated (Kick) population according to the maximum value of the Coulombic integral between the Fukui functions of both fragments. Subsequently, these few candidates are optimized using a gradient method and density functional theory (DFT) calculations. The performance of the program has been evaluated to explore the PES of various systems, including atomic and molecular clusters. In most cases studied, the global minimum (GM) has been identified with a low computational cost. The strategy does not allow to identify the GM of some silicon clusters; however, it predicts local minima very close in energy to the GM that could be used as the initial population of evolutionary algorithms.
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Algoritmos , Humanos , Estrutura MolecularRESUMO
Fourteen coumarin-derived compounds modified at the C3 carbon of coumarin with an α,ß-unsaturated ketone were synthesized. These compounds may be designated as chalcocoumarins (3-cinnamoyl-2H-chromen-2-ones). Both chalcones and coumarins are recognized scaffolds in medicinal chemistry, showing diverse biological and pharmacological properties among which neuroprotective activities and multiple enzyme inhibition, including mitochondrial enzyme systems, stand out. The evaluation of monoamine oxidase B (MAO-B) inhibitors has aroused considerable interest as therapeutic agents for neurodegenerative diseases such as Parkinson's. Of the fourteen chalcocumarins evaluated here against MAO-B, ChC4 showed the strongest activity in vitro, with IC50 = 0.76 ± 0.08 µM. Computational docking, molecular dynamics and MM/GBSA studies, confirm that ChC4 binds very stably to the active rMAO-B site, explaining the experimental inhibition data.
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Chalconas/química , Cumarínicos/química , Inibidores da Monoaminoxidase/química , Inibidores da Monoaminoxidase/farmacologia , Monoaminoxidase/química , Animais , Sítios de Ligação , Relação Dose-Resposta a Droga , Humanos , Ligantes , Conformação Molecular , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Estrutura Molecular , Ligação Proteica , Ratos , Relação Estrutura-AtividadeRESUMO
Herein, the first global minima containing a planar hexacoordinate carbon (phC) atom are reported. The fifteen structures belong to the CE3 M3 + (E=S-Te and M=Li-Cs) series and satisfy both geometric and electronic criteria to be considered as a true phC. The design strategy consisted of replacing oxygen in the D3h â CO3 Li3 + structure with heavy and less electronegative chalcogens, inducing a negative charge on the Câ atom and an attractive electrostatic interaction between C and the alkali-metal cations. The chemical bonding analyses indicate that carbon is covalently bonded to three chalcogens and ionically connected to the three alkali metals.
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Through delicate tuning of the electronic structure, we report herein a rational design of seventeen new putative global minimum energy structures containing a planar tetra- or pentacoordinate carbon atom embedded in an aromatic hydrocarbon. These structures are the result of replacing three consecutive hydrogen atoms of an aromatic hydrocarbon by less electronegative groups, forming a multicenter σ-bond with the planar hypercoordinate carbon atom and participating in the π-electron delocalization. This strategy that maximizes both mechanical and electronic effects through aromatic architectures can be extended to several molecular combinations to achieve new and diverse compounds containing planar hypercoordinate carbon centers.
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Extensive explorations of their potential energy surfaces, combined with high-level quantum chemical computations, strikingly show that the lowest energy structures of the (Li6 Si5 )2-5 systems consist of 2-5â Si5 6- aromatic units, surrounded by Li+ counterions, respectively. These viable gas-phase compounds are the pioneering reported cases of oligomers made by planar aromatic silicon rings. Based on the key evidence that these oligomers are energetically favored, and that their silicon rings aromaticity is thoroughly preserved, the Li6 Si5 cluster is proposed as a potential assembly unit to build silicon-lithium nanostructures, thus opening new paths to design Zintl compounds at the nanoscale level.
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The synthesis and structural characterization of the dimer [(Sn6Ge2Bi)2]4- raise the possibility of obtaining a broad variety of analogous compounds with different Sn/Ge/Bi proportions. Several combinations of nine atoms have been detected by electrospray mass spectrometry as potential assembly units. However, [(Sn6Ge2Bi)2]4- remains as the unique experimentally characterized species in this series. This fact has motivated us to explore its potential energy surface, as well as its monomers' [Sn6Ge2Bi]3-/2-, in an effort to gain insight into the factors that might be privileging the experimental viability of this species. Our results show that the lowest-energy [Sn6Ge2Bi]3- structure remains in its oxidized product [Sn6Ge2Bi]2-, which corresponds to that identified in the dimer [(Sn6Ge2Bi)2]4-. Additionally, local minima, very close in energy to the lowest-energy monomer, are chiral mixtures that dimerize into diverse structures with a probable energetic cost, making them noncompetitive isomers. Finally, the global minimum of the dimer [(Sn6Ge2Bi)2]4- presents the most stable monomers as assembly units. These results show the importance of considering the simultaneity of all of these conditions for the viability of these types of compounds.
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Theoretical studies are essential for the structural characterization of clusters, when it comes to rationalize their unique size-dependent properties and composition. However, the rapid growth of local minima on the potential energy surface (PES), with respect to cluster size, makes the candidate identification a challenging undertaking. In this article, we introduce a hybrid strategy to explore the PES of clusters. This proposal involves the use of a biased initial population of a genetic algorithm procedure. Each individual in this population is built by assembling small fragments, according to the best matching of the Fukui function. The performance of a genetic algorithm procedure. The performance of the method is assessed on the PES exploration of medium-sized Sin clusters (n = 12-20). The most relevant results are: (a) the method converges at almost half of the time used by the canonical version of the GA and, (b) in all the studied cases, with the exception of Si13 and Si16 , the method allowed to identify the global minimum (GM) and other important low-lying structures. Additionally, the apparent deficiency of the proposal to identify the GM was corrected when a Si atom, or other low-lying isomers, were considered to build the clusters. © 2017 Wiley Periodicals, Inc.
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The prediction of reactivity is one of the long-standing objectives of chemistry, contributing to enforce the link between theory and experiment. In particular, the regioselectivity of aromatic molecules has motivated the proposal of different reactivity descriptors based on foundational theories, like Frontier Molecular Orbital (FMO) theory and density functional theory, to predict and rationalize such regioselectivity. This article examines cases where reactivity descriptors, based on FMO theories, are known to have failed, specifically on electrophilic aromatic substitution reactions, through a simple but effective new reactivity model: the Orbital-weighted Fukui function ( fw-(r)) and its topological analysis. Interestingly, this descriptor proves to be effective in adequately predicting regioselectivities where other approximations failed. © 2017 Wiley Periodicals, Inc.