Synthesis, kinetic studies, and QSAR of dinucleoside polyphosphate derivatives as human AK1 inhibitors.

Adenylate kinase (AK) plays a crucial role in the metabolic monitoring of cellular adenine nucleotide homeostasis by catalyzing the reversible transfer of a phosphate group between ATP and AMP, yielding two ADP molecules. By regulating the nucleotide levels and energy metabolism, the enzyme is considered a disease modifier and potential therapeutic target for various human diseases, including malignancies and inflammatory and neurodegenerative disorders. However, lacking approved drugs targeting AK hinders broad studies on this enzyme's pathological importance and therapeutic potential. In this work, we determined the effect of a series of dinucleoside polyphosphate derivatives, commercially available (11 compounds) and newly synthesized (8 compounds), on the catalytic activity of human adenylate kinase isoenzyme 1 (hAK1). The tested compounds belonged to the following groups: (1) diadenosine polyphosphates with different phosphate chain lengths, (2) base-modified derivatives, and (3) phosphate-modified derivatives. We found that all the investigated compounds inhibited the catalytic activity of hAK1, yet with different efficiencies. Three dinucleoside polyphosphates showed IC50 values below 1 µM, and the most significant inhibitory effect was observed for P1-(5'-adenosyl) P5-(5'-adenosyl) pentaphosphate (Ap5A). To understand the observed differences in the inhibition efficiency of the tested dinucleoside polyphosphates, the molecular docking of these compounds to hAK1 was performed. Finally, we conducted a quantitative structure-activity relationship (QSAR) analysis to establish a computational prediction model for hAK1 modulators. Two PLS-regression-based models were built using kinetic data obtained from the AK1 activity analysis performed in both directions of the enzymatic reaction. Model 1 (AMP and ATP synthesis) had a good prediction power (R2 = 0.931, Q2 = 0.854, and MAE = 0.286), while Model 2 (ADP synthesis) exhibited a moderate quality (R2 = 0.913, Q2 = 0.848, and MAE = 0.370). These studies can help better understand the interactions between dinucleoside polyphosphates and adenylate kinase to attain more effective and selective inhibitors in the future.

HATS5m as an Example of GETAWAY Molecular Descriptor in Assessing the Similarity/Diversity of the Structural Features of 4-Thiazolidinone.

Among the various methods for drug design, the approach using molecular descriptors for quantitative structure-activity relationships (QSAR) bears promise for the prediction of innovative molecular structures with bespoke pharmacological activity. Despite the growing number of successful potential applications, the QSAR models often remain hard to interpret. The difficulty arises from the use of advanced chemometric or machine learning methods on the one hand, and the complexity of molecular descriptors on the other hand. Thus, there is a need to interpret molecular descriptors for identifying the features of molecules crucial for desirable activity. For example, the development of structure-activity modeling of different molecule endpoints confirmed the usefulness of H-GETAWAY (H-GEometry, Topology, and Atom-Weights AssemblY) descriptors in molecular sciences. However, compared with other 3D molecular descriptors, H-GETAWAY interpretation is much more complicated. The present study provides insights into the interpretation of the HATS5m descriptor (H-GETAWAY) concerning the molecular structures of the 4-thiazolidinone derivatives with antitrypanosomal activity. According to the published study, an increase in antitrypanosomal activity is associated with both a decrease and an increase in HATS5m (leverage-weighted autocorrelation with lag 5, weighted by atomic masses) values. The substructure-based method explored how the changes in molecular features affect the HATS5m value. Based on this approach, we proposed substituents that translate into low and high HATS5m. The detailed interpretation of H-GETAWAY descriptors requires the consideration of three elements: weighting scheme, leverages, and the Dirac delta function. Particular attention should be paid to the impact of chemical compounds' size and shape and the leverage values of individual atoms.

Quantitative relationships between structure and cytotoxic activity of flavonoid derivatives. An application of Hirshfeld surface derived descriptors.

Quantitative relationships between the structure and cytotoxic activity of series flavonoid derivatives were examined. The first regression-based model, developed for 18 flavanone-2-pyrazoline hybrids, involved two interpretable descriptors: a Mor04v and partial atomic charge. The second model, developed for structurally diverse set of compounds, was based on descriptors derived from Hirshfeld surface analysis. This model suggests that cytotoxic activity of compounds can be successfully predicted based on a fraction of H⋯H contacts and a fraction of interactions involving a halogen atom. For non-halogen derivatives, the data reveal that cytotoxic activity is inversely proportional to the percentage of O⋯H and N⋯H close contacts to Hirshfeld surface, while directly proportional to the percentage of H⋯H interactions. Chlorine (1k) and bromine (1l) derivatives of compounds, containing flavanone fused with N-methyl-2-pyrazoline, exhibited high cytotoxic potential against HL-60 cancer cell line (IC50<10µM). The cytotoxicity of 1k and 1l towards normal cells (HUVEC) was 10 and 25-fold lower, respectively.

Detection of adulterants in dietary supplements with Ginkgo biloba extract by attenuated total reflectance Fourier transform infrared spectroscopy and multivariate methods PLS-DA and PCA.

The infrared spectroscopy with attenuated total reflectance (ATR) sampling coupled with chemometric methods has been applied to non-destructive detection of adulterants in dietary supplements containing Ginkgo biloba extract. The sample set comprised the spectra of six drugs and sixteen dietary supplements with ginkgo leaf extract. Spectral data (900-1800 cm-1) were analyzed using multivariate partial least squares regression combined with a discriminant analysis (PLS-DA). The second derivative of spectra followed by mean centering was used as pre-processing method. Three models were constructed and validated for detection of potential adulterants: kaempferol, quercetin, and rutin. The iPLS-DA classification models achieved about 87.5%, 93,7%, and 87,5% of correct classification for adulteration with kaempferol, quercetin and rutin, respectively. The results obtained from classification models were verified by chromatographic fingerprints of unhydrolyzed sample extracts. Two-trace two-dimensional asynchronous correlation maps were constructed from pairs of spectra (each dietary supplement spectrum vs. averaged spectrum of drugs) and then analyzed by multiway PCA which revealed good discrimination between samples.

An application of QSRR approach and multiple linear regression method for lipophilicity assessment of flavonoids.

The analysis of quantitative structure-retention relationships (QSRR) is useful tool for assessment of compound's lipophilicity/hydrophobicity due to similarity between its retention in chromatographic system and ability to permeation through biological membranes. The main goal of this study was to compare usefulness of two reversed-phase chromatographic columns (Synergy POLAR and Synergy-FUSION) for lipophilicity assessment of 30 structurally diverse flavonoids using the QSRR approach and multiple linear regression method. The developed MLR models included the mechanistically interpretable geometrical descriptors: 3D Molecule Representation of Structure based on Electron diffraction (3D-MoRSE) and Radial Distribution Function (RDF). Both models were evaluated by the internal and external validation and selected descriptors were further interpreted. According to obtained results the FUSION-RP column can be recommended to log kw prediction of flavonoids. The comprehensive interpretation of molecular descriptors was used to present the molecular mechanisms and structural features governing the chromatographic retention of tested compounds.