Physicochemical properties and mechanism of action of a new copper(ii) pyrazine-based complex with high anticancer activity and selectivity towards cancer cells.

Two compounds, benzyl-2-(amino(pyrazin-2-yl)methylene)-1-methylhydrazine-1-carbodithioate (L) and its copper(ii) complex Cu(L) were synthesized and studied in terms of their physicochemical properties, including single crystal, spectroscopic and magnetic properties; simulations, including DFT calculations and pharmacokinetic profile analysis; and biological activity. The Cu(L) compound was found to exhibit good anticancer activity against A375, PANC-1, MKN-74, T-47D, HeLa, and NCI-H1563 cells, with the IC value against the HeLa cell line reaching 17.50 μM, significantly surpassing the activity of the organic ligand.

Accurate and rapid antibiotic susceptibility testing using a machine learning-assisted nanomotion technology platform.

Antimicrobial resistance (AMR) is a major public health threat, reducing treatment options for infected patients. AMR is promoted by a lack of access to rapid antibiotic susceptibility tests (ASTs). Accelerated ASTs can identify effective antibiotics for treatment in a timely and informed manner.

Structure-activity relationship and cytotoxicity of the new thiosemicarbazide derivatives and their Cu(II) complexes against prostate and melanoma cancer cells.

In this study, eighteen new ligands (B1-B18) containing a thiosemicarbazide core were synthesized and characterized in terms of physicochemical properties, molecular docking and in vitro biological activity. The structures of eleven ligands were investigated using X-Ray diffraction and Hirschfeld Surface analysis. To study the structure-activity relationship, the organic ligands contained pyridin-2-ylmethyl, pyridin-3-ylmethyl or pyridin-4-ylmethyl moieties and various substituents.

Nanomotion technology in combination with machine learning: a new approach for a rapid antibiotic susceptibility test for Mycobacterium tuberculosis.

Nanomotion technology is a growth-independent approach that can be used to detect and record the vibrations of bacteria attached to cantilevers. We have developed a nanomotion-based antibiotic susceptibility test (AST) protocol for Mycobacterium tuberculosis (MTB). The protocol was used to predict strain phenotype towards isoniazid (INH) and rifampicin (RIF) using a leave-one-out cross-validation (LOOCV) and machine learning techniques.

In Silico ADME and Toxicity Prediction of Benzimidazole Derivatives and Its Cobalt Coordination Compounds. Synthesis, Characterization and Crystal Structure.

As a result of the synthesis, three new solids, cobalt (II) coordination compounds with benzimidazole derivatives, and chlorides were obtained. The ligands that were used in the synthesis were specially synthesized and were commercially unavailable. During the synthesis, a single crystal of the complex with the ligand was obtained and the crystal structure was refined.