The electrostatic potential of dynamic charge densities

Tackling antibiotic contaminations in wastewater with novel Modified-MOF nanostructures: A study of molecular simulations and DFT calculations

The contamination of wastewater with antibiotics has emerged as a critical global challenge, with profound implications for environmental integrity and human well-being. Adsorption techniques have been meticulously investigated and developed to mitigate and alleviate their effects. In this study, we have investigated the adsorption behaviour of Erythromycin (ERY), Gentamicin (GEN), Levofloxacin (LEVO), and Metronidazole (MET) antibiotics as pharmaceutical contaminants (PHCs) on amide-functionalized (RC (=O)NH2)/MIL-53 (Al) (AMD/ML53A), using molecular simulations and density functional theory (DFT) calculations. Based on our DFT calculations, it becomes apparent that the adsorption tendencies of antibiotics are predominantly governed by the presence of AMD functional groups on the adsorbent surface. Specifically, hydrogen bonding (HB) and van der Waals (vdW) interactions between antibiotics and AMD groups serve as the primary mechanisms facilitating adsorption. Furthermore, we have observed that the adsorption behaviors of these antibiotics are influenced by their respective functional groups, molecular shapes, and sizes. Our molecular simulations delved into how the AMD/ML53A surfaces interact with antibiotics as PHCs. Moreover, various chemical quantum descriptors based on Frontier Molecular Orbitals (FMO) were explored to elucidate the extent of AMD/ML53A adsorption and to assess potential alterations in their electronic properties throughout the adsorption process. Monte Carlo simulation showed that ERY molecules adsorb stronger to the adsorbent in acidic and basic conditions than other contaminants, with high energies: -404.47 kcal/mol in acidic and -6375.26 kcal/mol in basic environments. Molecular dynamics (MD) simulations revealed parallel orientation for the ERY molecule's adsorption on AMD/ML53A with 80% rejection rate. In conclusion, our study highlighted the importance of modeling in developing practical solutions for removing antibiotics as PHCs from wastewater. The insights gained from our calculations can facilitate the design of more effective adsorption materials, ultimately leading to a more hygienic and sustainable ecosystem.

Application of Molecular Dynamics Simulations in the Analysis of Cyclodextrin Complexes

Cyclodextrins (CDs) are highly respected for their ability to form inclusion complexes via host-guest noncovalent interactions and, thus, ensofance other molecular properties. Various molecular modeling methods have found their applications in the analysis of those complexes. However, as showed in this review, molecular dynamics (MD) simulations could provide the information unobtainable by any other means. It is therefore not surprising that published works on MD simulations used in this field have rapidly increased since the early 2010s. This review provides an overview of the successful applications of MD simulations in the studies on CD complexes. Information that is crucial for MD simulations, such as application of force fields, the length of the simulation, or solvent treatment method, are thoroughly discussed. Therefore, this work can serve as a guide to properly set up such calculations and analyze their results.

The chemical reactivity and QSPR of organic compounds applied to dye-sensitized solar cells using DFT

The structural and electronic properties were calculated for seventy organic compounds used as dye sensitizers in solar cells, applying the B3LYP exchange-correlation energy functional with the 6-311G∗∗ basis set. Moreover, the present study proposes two new quantitative structure-property relationship (QSPR) models that enable the prediction of the power conversion efficiency (PCE) and maximum absorption wavelength (λ_max) of these systems, the two QSPR models were validated using the coefficient of determination (R²) of 0.62 for both models with the leave-one-out cross-validation correlation coefficient (Q²_LOO) of 0.55 and 0.57, respectively. Furthermore, applicability domain analysis was conducted in order to identify the related compounds via the extrapolation of the model.

Extension of the transferable aspherical pseudoatom data bank for the comparison of molecular electrostatic potentials in structure-activity studies

The transferable aspherical pseudoatom data bank, UBDB2018, is extended with over 130 new atom types present in small and biological molecules of great importance in biology and chemistry. UBDB2018 can be applied either as a source of aspherical atomic scattering factors in a standard X-ray experiment (d_min ≃ 0.8 Å) instead of the independent atom model (IAM), and can therefore enhance the final crystal structure geometry and refinement parameters; or as a tool to reconstruct the molecular charge-density distribution and derive the electrostatic properties of chemical systems for which 3D structural data are available. The extended data bank has been extensively tested, with the focus being on the accuracy of the molecular electrostatic potential computed for important drug-like molecules, namely the HIV-1 protease inhibitors. The UBDB allows the reconstruction of the reference B3LYP/6-31G** potentials, with a root-mean-squared error of 0.015 e bohr^-1 computed for entire potential grids which span values from ca 200 e bohr^-1 to ca -0.1 e bohr^-1 and encompass both the inside and outside regions of a molecule. UBDB2018 is shown to be applicable to enhancing the physical meaning of the molecular electrostatic potential descriptors used to construct predictive quantitative structure-activity relationship/quantitative structure-property relationship (QSAR/QSPR) models for drug discovery studies. In addition, it is suggested that electron structure factors computed from UBDB2018 may significantly improve the interpretation of electrostatic potential maps measured experimentally by means of electron diffraction or single-particle cryo-EM methods.