A novel class of bioactive complexes (1–3) [M^II(L)₂(bpy)], where, L = 2-(4-morpholinobenzylideneamino)phenol, bpy = 2,2′-bipyridine, M^II = Mn (1), Co (2) or Ni (3), were assigned to octahedral geometry based on analytical and spectral measurements. Gel electrophoresis showed that complex (2) demonstrated significant DNA cleavage activity compared to the other complexes under the action of oxidation agent (H₂O₂). The DNA binding constant properties measured by various techniques were in the following sequence: (2) > (3) > (1) > (HL), which suggests that the complexes might intercalate DNA, a possibility that is also supported by their biothermodynamic characteristics. The binding constant results for BSA from electronic absorption and fluorometric titrations demonstrate that complex (2) exhibits the highest binding effectiveness among them all, which means that all the compounds could interact with BSA through a static approach, additionally supported by FRET measurements. DFT and docking calculations were employed to realize the electronic structure, reactivity, and interaction capability of all substances with DNA, BSA, and the SARS-CoV-2 main protease. These binding energies fell within the ranges −7.7 to −8.5, −8.2 to −10.1 and −6.7 to −9.3 kcal mol⁻¹, respectively. The higher reactivity of the complexes than the ligand is supported by FMO theory. The in vitro antibacterial, cytotoxicity, and radical scavenging characteristics revealed that complexes (2–3) have better biological efficacy than the others. The cytotoxicity and binding properties also show good correlation with the partition coefficient (log P), which is encouraging because all of the experimental findings are closely correlated with the theoretical measurements.

1. An understanding of van der Waals interactions or weak noncovalent interactions in general in the context of molecular packing in the crystal is an important aspect of crystal engineering. Such ...

FFLUX is a novel machine-learnt force field using pre-trained Gaussian process regression (GPR) models to predict energies and multipole moments of quantum atoms in molecular dynamic simulations. At the heart of FFLUX lies the program FEREBUS, a Fortran90 and OpenMP-parallelized regression engine, which trains and validates GPR models of chemical accuracy. Training a GPR model is about finding an optimal set of model hyperparameters (θ). This time-consuming task is usually accomplished by maximizing the marginal/concentrated log-likelihood function LLy|x,θ, known as the type-II maximum likelihood approach. Unfortunately, this widespread approach can suffer from the propagation of numerical errors, especially in the noise-free regime, where the expected correlation betweenLLy|x,θ̂ [maximized value of theLLy|x,θfunction] and the models’ performance may no longer be valid. In this scenario, the LLy|x,θ function is no longer a reliable guide for model selection. While one could still rely on a pre-conditioner to improve the condition number of the covariance matrix, this choice is never unique and often comes with increased computational cost. Therefore, we have equipped FEREBUS with an alternatively simple, intuitive, viable, and less error-prone protocol called “iterative hold-out cross-validation” for the optimization of θ values. This protocol involves (1) a stratified random sampling of both training and validation sets, followed by (2) an iterative minimization of the predictive RMSE(θ) of intermediary models over a sufficiently large validation set. Its greatest asset is the assurance that the optimization process keeps reducing the generalization error of intermediary GPR models on unseen datasets, something that maximizing LLy|x,θ does not guarantee.

Two novel thiazole derivatives, ethyl 5-((4-fluorophenyl)carbamoyl)-thiazole-4-carboxylate (2b) and ethyl 5-(p-tolylcarbamoyl)thiazole-4-carboxylate (6b) have been synthesized, and their crystal structures determined by X-ray diffraction. To rationalize their structure, reactivity and druggability, we have performed a series of separate, but complementary studies. Hirshfeld surface and 2D-fingerprint plots were first scrutinized to qualitatively unveil all the intermolecular interactions that ensure their crystal packing. Moreover, topological electron density parameters established from the quantum theory of atoms-in-molecules (QTAIM) and Reduced Density Gradient (RDG) were later relied on to characterize the chemical bonding of these species, in terms of the nature and magnitude of noncovalent interactions developed within their monomeric and dimeric forms. In both structures, C-H…O hydrogen bonds are found to be stronger than other noncovalent interactions. Furthermore, H…H bonding contacts and non-conventional C–H…O hydrogen bonds both exhibit a closed shell nature, and play in crucial role in the stability of the novel thiazoles. The isosurfaces in the intermolecular region furnished by NCI molecular diagram signifies the existence of weak noncovalent interactions. Finally, the potential inhibitory activity of the titled compounds and their drug-likeness are demonstrated by molecular docking and ADME-T calculations respectively. Both compounds adhere to the Lipinski’s rule of five and present encouraging pharmacokinetic properties and safety profiles. Communicated by Ramaswamy H. Sarma

The ambident reactivity of small-sized XAHs (X=H, F, Cl, Br, CH3, and A=S, Se, Te) molecules towards the imidazole molecule (IMZ) has been investigated using wave function (MP2) and Density Functional Theory (B3LYP, B3LYP-D3). Molecular electrostatic potentials (MEPs) and frontier molecular orbitals of monomers are computed to rationalise the regioselectivity of IMZ towards XAHs. The chemical bonding of each complex is described in the framework of the quantum theory of atoms in molecules (QTAIM) and natural bond orbital (NBO) paradigms. The symmetry-adapted perturbation theory (SAPT) is employed to assess the physical nature of the interactions. Our findings suggest that XAHs mainly bind to IMZ through H-bonding and chalcogen-bonding interactions of weak to moderate strength, with binding energies ranging from −3.1 to −17.6 kcal/mol at the MP2/aug-cc-pVDZ(-PP) level. Topological QTAIM descriptors reveal all H-bonds between IMZ and XAHs to be purely noncovalent contacts, while chalcogen bonds of halogenated XAHs (X = F, Cl, Br) show a partial covalent character. SAPT2 calculations indicate that both H-bonded and chalcogen-bonded complexes are mainly stabilised by electrostatic interactions. Insights drawn from this study are expected to constitute the bedrock for further investigations about noncovalent interaction between middle to big-sized chalcogen-containing molecules and imidazole derivatives. GRAPHICAL ABSTRACT

FFLUX is a polarizable machine-learning force field that deploys pre-trained kernel-based models of quantum topological properties in molecular dynamics simulations. Despite a track record of successful applications, this unconventional force field still uses Lennard-Jones parameters to account for dispersion effects when performing in-bulk simulations. However, optimal Lennard-Jones parameters are system-dependent and not easy to calibrate. Fortunately, physics-informed dispersion energies can be obtained from the two-particle density matrix (2PDM) of any system using correlated wavefunctions. The only challenge is that the 2PDM is a humongous object whose calculation is very time-consuming and memory-greedy. In this proof-of-concept study, we utilize the Δ-learning method to address both problems using a small set of water trimers. More specifically, we obtain pure two-electron correlation energies with the aug-cc-pVDZ basis set at the cost of Müller-approximated 2PDM calculated at a very small basis set, 6-31+G(d). We also benchmark different Δ-learning tasks designed by changing the baseline and target method and/or the basis set. Our experiments suggest that two-electron correlation energies of weakly relaxed water trimers can be accurately predicted via Δ-learning with a maximum absolute error of 1.30 ± 0.32 kJ/mol traded against a colossal computational speed-up of roughly 40 times.