Accelerating NMR Shielding Calculations Through Machine Learning Methods: Application to Magnesium Sodium Silicate Glasses.

In this work, we have applied the Kernel Ridge Regression (KRR) method using a Least Square Support Vector Regression (LSSVR) approach for the prediction of the NMR isotropic magnetic shielding (σiso) of active nuclei (17O, 23Na, 25Mg, and 29Si) in a series of (Mg, Na) - silicate glasses. The Machine Learning (ML) algorithm has been trained by mapping the local environment of each atom described by the Smooth Overlap of Atomic Position (SOAP) descriptor with isotropic chemical shielding values computed with DFT using the Gauge-Included-Projector-Augmented-Wave (GIPAW) approach. The influence of different training datasets generated through molecular dynamics simulations at various temperatures and with different inter-atomic potentials has been tested and we demonstrate the importance of a wide exploration of the configurational space to enhance the transferability of the ML-regressor.  Finally, the trained ML-regressor has been used to simulate the 29Si MAS NMR spectra of systems containing up to 20000 atoms by averaging hundreds of configurations extracted from classical MD simulations to account for thermal vibrations. This ML approach is a powerful tool for the interpretation of NMR spectra using relatively large systems at a fraction of the computational time required by quantum mechanical calculations which are of high computational cost.

Accurate and Transferable Machine Learning Potential for Molecular Dynamics Simulation of Sodium Silicate Glasses.

An accurate and transferable machine learning (ML) potential for the simulation of binary sodium silicate glasses over a wide range of compositions (from 0 to 50% Na2O) was developed. The potential energy surface is approximated by the sum of atomic energy contributions mapped by a neural network algorithm from the local geometry comprising information on atomic distances and angles with neighboring atoms using the DeePMD code [Wang, H. Comput. Phys. Commun. 2018, 228, 178-184]. Our model was trained on a large data set of total energies and atomic forces computed at the density functional theory level on structures extracted from classical molecular dynamics (MD) simulations performed at several temperatures from 300 to 3000 K. This allows for the generation of a robust and transferable ML potential applicable over the full compositional range of glass formability at different temperatures that outperforms the empirical potentials available in the literature in reproducing structures and properties such as bond angle distribution, total distribution functions, and vibrational density of state. The generality of the approach enables the future training of a potential with other or more elements allowing for simulations of structures, properties, and behavior of ternary and multicomponent oxide glasses with nearly ab initio accuracy at a fraction of the computational cost.

Bridging pyrimidine hemicurcumin and Cisplatin: Synthesis, coordination chemistry, and in vitro activity assessment of a novel Pt(II) complex.

In the upcoming decades, the incidence and mortality rates of cancer are expected to rise globally, with colorectal and prostate cancers among the most prevalent types. Despite advancements in molecular targeted therapy, platinum-based chemotherapies remain the cornerstone of treatment, especially for colorectal and prostate cancer, with oxaliplatin and cisplatin being extremely effective due to their DNA-targeting capabilities. In our pursuit of new platinum-based chemotherapeutics that are potentially less toxic and more effective, we have explored the combination of the Pt-binding groups of the diaminocyclohexane ring used in oxaliplatin, with the stable amino-pyrimidine hemicurcumin moiety. This new derivative exhibit improved stability in physiological conditions and increased solubility in aqueous media, demonstrating promising effects on cell proliferation of both colorectal and prostate cells. We report herein the complete synthesis and chemical characterization in solution of the new derivative [(1R,2R)-N1-(3-(4-((E)-2-(2-Amino-6-methylpyrimidin-4-yl)vinyl)-2-methoxyphenoxy) propyl) cyclohexane-1,2-diamine] (MPYD). Our analysis includes an examination of its acid-base equilibria, speciation and stability in physiological conditions. The synthesis and in situ formation of Pt(II) complexes were investigated by nuclear magnetic resonance spectroscopy, while density functional theory calculations were employed to elucidate the chemical structure in solution. Results on the biological activity were obtained through cell viability assays on different colorectal and prostate cell lines (HCT116, HT29, PC3 and LNCaP).