In-silico selection of peptides for the recognition of imidacloprid.

The sensitive detection of pesticides using low-cost receptors designed from peptides can widen their uses in the environmental surveillance for emerging pollutants. In-silico selection of peptides can help accelerate the design of receptor sequence banks for a given target of interest. In this work, we started from Lymnaea stagnalis acetylcholine-binding protein Q55R mutant receptor-imidacloprid complex, available in the PDB databank, to select three primary short peptides (YSP09, DMR12, WQW13 respectively having 9, 12 and 13 amino acids (AA) in length) from the pesticide interacting zones with the A, B and C chains of the nicotinic receptor. Using molecular docking and molecular dynamics (MD) simulations, we showed that the three peptides can form complexes with the target imidacloprid, having energies close to that obtained from a reference RNR12 peptide. Combination of these peptides allowed preparing a new set of longer peptides (YSM21, PSM22, PSW31 and WQA34) that have higher stability and affinity as shown by the MM-PBSA calculations. In particular, the WQA34 peptide displayed an average binding free energy of -6.44±0.27 kcal/mol, which is three times higher than that of the reference RNR12 peptide (-2.29±0.25 kcal/mol) and formed a stable complex with imidacloprid. Furthermore, the dissociation constants (Kd), calculated from the binding free energy, showed that WQA32 (40 µM) has three orders of magnitude lower Kd than the reference RNR12 peptide (3.4 × 104 µM). Docking and RMSD scores showed that the WQA34 peptide is potentially selective to the target imidacloprid with respect to acetamiprid and clothianidin. Therefore, this peptide can be used in wet-lab experiments to prepare a biosensor to selectively detect imidacloprid.

Correction: Surface modification of graphene with functionalized carbenes and their applications in the sensing of toxic gases: a DFT study.

[This corrects the article DOI: 10.1039/D3RA02557H.].

Surface modification of graphene with functionalized carbenes and their applications in the sensing of toxic gases: a DFT study.

Graphene and other 2D materials have gained significant attention in the development of gas sensors. In this study, we employed Density Functional Theory (DFT) to investigate the adsorption properties of diazomethanes (1a-1g) with various functional groups (R = OH (a), OMe (b), OEt (c), OPr (d), CF3 (e), Ph (f)) on pristine graphene. Furthermore, we explored the adsorption behavior of activated carbenes (2a-2g) generated from the decomposition of diazomethanes on graphene, as well as the functionalized graphene derivatives (3a-3g) resulting from [2 + 1] cycloaddition reactions between (2a-2g) and graphene. The interaction between these functionalized derivatives (3a-3g) and toxic gases was also investigated. Our results revealed that carbenes exhibited a stronger affinity for graphene compared to diazomethanes. The adsorption energy of esters (3b, 3c, and 3d) on graphene decreased relative to compound 3a, while 3e exhibited increased adsorption energy due to the electron-withdrawing effect of fluorine atoms. Additionally, the adsorption energy of phenyl and nitrophenyl groups (3f and 3g) decreased due to their π-stacking interaction with graphene. Importantly, all functionalized derivatives (3a-3g) demonstrated favorable interactions with gases. Notably, the derivative 3a, acting as a hydrogen bonding donor, exhibited superior performance. Furthermore, modified graphene derivatives exhibited the highest adsorption energy with NO2 gas, highlighting their potential for selective NO2 sensing applications. These findings contribute to the understanding of gas-sensing mechanisms and the design of novel graphene-based sensor platforms.

Evaluation of Biological Activities of Twenty Flavones and In Silico Docking Study.

This work aimed to evaluate the biological activities of 20 flavones (M1 to M20) and discuss their structure-activity relationships. In vitro assays were established to assess their numerous biological activities (anti-α-amylase, anti-acetylcholinesterase, anti-xanthine oxidase, anti-superoxide dismutase, and anticancer cell lines (HCT-116, MCF7, OVCAR-3, IGROV-1, and SKOV-3 cells lines)). An in silico docking study was also established in order to find the relationship between the chemical structure and the biological activities. In vitro tests revealed that M5 and M13 were the most active in terms of anti-α-amylase activity (IC50 = 1.2 and 1.4 µM, respectively). M17 was an inhibitor of xanthine oxidase (XOD) and performed better than the reference (allopurinol), at IC50 = 0.9 µM. M7 presented interesting anti-inflammatory (IC50 = 38.5 µM), anti-supriode dismutase (anti-SOD) (IC50 = 31.5 µM), and anti-acetylcholinesterase (IC50 = 10.2 µM) activities. Those abilities were in concordance with its high scavenging activity in antioxidant ABTS and DPPH assays, at IC50 = 6.3 and 5.2 µM, respectively. Selectivity was detected regarding cytotoxic activity for those flavones. M1 (IC50 = 35.9 µM) was a specific inhibitor to the MCF7 cancer cell lines. M3 (IC50 = 44.7 µM) and M15 (IC50 = 45.6 µM) were particularly potent for the OVCAR-3 cell line. M14 (IC50 = 4.6 µM) contributed more clearly to inhibiting the colon cancer cell line (HCT116). M7 (IC50 = 15.6 µM) was especially active against the ovarian SKOV human cancer cell line. The results of the biological activities were supported by means of in silico molecular docking calculations. This investigation analyzed the contribution of the structure-activity of natural flavones in terms of their biological properties, which is important for their future application against diseases.

Synthesis, Characterization of Chitosan-Aluminum Oxide Nanocomposite for Green Synthesis of Annulated Imidazopyrazol Thione Derivatives.

Chitosan-aluminum oxide nanocomposite was synthesized, characterized, and used as a green heterogeneous catalyst to synthesize novel imidazopyrazolylthione derivatives. Nanocomposite polymeric material was characterized by EDS-SEM and XRD. The powerful catalytic activity, and its base character of the nanocomposite, was used to synthesize imidazopyrazolylthione (1) in a good yield compared to traditional cyclocondensation synthesis. Using the nanocomposite catalyst, substitution of the thiol group (1) afforded the corresponding thiourea (2) and the corresponding ester (3). The efficiency of the nanocomposite over the traditional base organic catalyst, Et3N and NaOH, makes it an effective, economic, and reproducible nontoxic catalyst. Moreover, the heterogeneous nanocomposite polymeric film was easily isolated from the reaction medium, and recycled up to four times, without a significant loss of its catalytic activity. The newly synthesized derivatives were screened as antibacterial agents and showed high potency. Molecular docking was also performed for a more in-depth investigation. The results of the docking studies have demonstrated that the docked compounds have strong interaction energies with both Gram-positive and Gram-negative bacteria.

Pristine graphene covalent functionalization with aromatic aziridines and their application in the sensing of volatile amines - an ab initio investigation.

Food quality is of paramount importance for public health safety. For instance, fish freshness can be assessed by sensing the volatile short chain alkylamines produced by spoiled fish. Functionalized graphene is a good candidate for the design of gas sensors for such compounds and therefore of interest as the basic material in food quality sensor devices. To shed theoretical insight in this direction, in the present work we investigate via first-principles density functional theory (DFT) simulations: (i) graphene functionalization via aziridine appendages and (ii) the adsorption of short chain alkylamines (methylamine MA, dimethylamine DMA, and trimethylamine TMA) on the chemically functionalized graphene sheets. Optimal geometries, adsorption energies, and projected density of states (PDOS) are computed using a DFT method. We show that nitrene reactive intermediates, formed by thermal or photo splitting of arylazides - p-carboxyphenyl azide (1a), p-carboxyperfluorophenyl azide (1b), and p-nitrophenyl azide (1c) - react with graphene to yield functionalized derivatives, with reaction energies >-1.0 eV and barriers of the order of 2.0 eV, and open a ∼0.3 to 0.5 eV band gap which is in principle apt for applications in sensing and electronic devices. The interaction between the amines and functionalized graphene, as demonstrated from the calculations of charge density differences showing regions of charge gain and others of charge depletion between the involved groups, occurs through hydrogen bonding with interaction energies ranging from -0.04 eV to -0.76 eV, and induce charge differences in the system, which in the case of p-carboxyperfluorophenyl azide (1b) are sizeable enough to be experimentally observable in sensing.

First-principles study of Au-Cu alloy surface changes induced by gas adsorption of CO, NO, or O2.

The surface composition of bimetallics can be strongly altered by adsorbing molecules where the metal with the strongest interaction with the adsorbate segregates into the surface. To investigate the effect of reactive gas on the surface composition of Au-Cu alloy, we examined by means of density functional theory to study the segregation behavior of copper in gold matrices. The adsorption mechanisms of CO, NO, and O2 gas molecules on gold, copper, and gold-copper low index (111), (100), and (110) surfaces were analyzed from energetic and electronic points of view. Our results show a strong segregation of Cu toward the (110) surface in the presence of all adsorbed molecules. Interestingly, the Cu segregation toward the (111) and (100) surface could occur only in the presence of CO and at a lower extent in the presence of NO. The analysis of the electronic structure highlights the different binding characters of adsorbates inducing the Cu segregation.

Theoretical prediction of a peptide binding to major histocompatibility complex II.

Prediction of the binding energy of a peptide implicated in multipole sclerosis to its major histocompatibility complex (MHC) receptor is reported using numerous ab initio, density functional (DFT) and semi-empirical theoretical methods. Using the crystalline coordinates taken from the protein databank, two ab initio methods are shown to be in good agreement for pairwise interaction of amino acids. These data are then used to benchmark more approximate DFT and semi-empirical approaches, which are shown to have substantial errors. However, in some cases significant improvement is apparent on inclusion of an empirical correction to account for dispersion interactions. Most promising among these cases is RM1, a re-parameterization of the popular AM1 method for atoms typically found in organic and biological molecules. Together with the dispersion correction, this reproduces ab initio data with a mean unsigned error of 1.36 kcal/mol. This approach is used to predict binding for progressively larger model systems, up to binding of the peptide with the entire MHC receptor, and is then applied to multiple snapshots taken from molecular dynamics simulation.