From the Kinetic Theory of Gases to the Kinetics of Rate Processes: On the Verge of the Thermodynamic and Kinetic Limits

Investigation of antitumor activity and albumin interaction of new sulfosalicylate-based complex by spectroscopic and computational approaches

In the present study, the drug delivery by albumin protein and antiproliferetaive activity of new transition metal complex i.e., [Pd (phen)(SSA)] (where phen and SSA represent 1, 10 phenanthroline and sulfosalicylic acid, respectively) was investigated. DFT (density functional theory) calculations were conducted at B3LYP level with 6-311G(d,p)/aug-ccpVTZ-PP basis set for the purpose of geometry optimization, frontier molecular orbital (FMO) analysis, molecular electrostatic potential (MEP), and natural bond orbital (NBO) analysis. Experimental tests were conducted to preliminarily assess the lipophilicity and antitumor activity of the metal complex, resulting in promising findings. In-silico prediction was accomplished to assess its toxicity and bioavailability. To evaluate the binding of the newly formed complex with DNA (which results in halting the cell cycle) or serum albumin protein (drug transporter to the tissues), in-silico molecular modeling was employed. Experimental results (spectroscopic and non-spectroscopic) showed that the new compound interacts with each biomolecule via hydrogen bond and van der Waals interactions. Molecular docking demonstrated the binding of this complex to the DNA groove and site I of BSA occurs mainly through hydrogen bonds. Molecular dynamics simulation confirmed the interactions between [Pd (phen)(SSA)] with DNA or BSA through stable hydrogen bonds.

Proof of concept for a nonadditive stochastic model of supercooled liquids

The recently proposed nonadditive stochastic model (NSM) offers a coherent physical interpretation for diffusive phenomena in glass-forming systems. This model presents nonexponential relationships between viscosity, activation energy, and temperature, characterizing the non-Arrhenius behavior observed in supercooled liquids. In this work, we fit the NSM viscosity equation to experimental temperature-dependent viscosity data corresponding to 25 glass-forming liquids and compare the fit parameters with those obtained using the Vogel-Fulcher-Tammann (VFT), Avramov-Milchev (AM), and Mauro-Yue-Ellison-Gupta-Allan (MYEGA) models. The results demonstrate that the NSM provides an effective fitting equation for modeling viscosity experimental data in comparison with other established models (VFT, AM, and MYEGA), characterizing the activation energy in fragile liquids, presenting a reliable indicator of the degree of fragility of the glass-forming liquids.

"pySiRC": Machine Learning Combined with Molecular Fingerprints to Predict the Reaction Rate Constant of the Radical-Based Oxidation Processes of Aqueous Organic Contaminants

We developed a web application structured in a machine learning and molecular fingerprint algorithm for the automatic calculation of the reaction rate constant of the oxidative processes of organic pollutants by ^•OH and SO₄^•- radicals in the aqueous phase-the pySiRC platform. The model development followed the OECD principles: internal and external validation, applicability domain, and mechanistic interpretation. Three machine learning algorithms combined with molecular fingerprints were evaluated, and all the models resulted in high goodness-of-fit for the training set with R² > 0.931 for the ^•OH radical and R² > 0.916 for the SO₄^•- radical and good predictive capacity for the test set with R_ext² = Q_ext² values in the range of 0.639-0.823 and 0.767-0.824 for the ^•OH and SO₄^•- radicals. The model was interpreted using the SHAP (SHapley Additive exPlanations) method: the results showed that the model developed made the prediction based on a reasonable understanding of how electron-withdrawing and -donating groups interfere with the reactivity of the ^•OH and SO₄^•- radicals. We hope that our models and web interface can stimulate and expand the application and interpretation of kinetic research on contaminants in water treatment units based on advanced oxidative technologies.

Topography of the free energy landscape of Claisen-Schmidt condensation: solvent and temperature effects on the rate-controlling step

Recent studies have found that hydroxide elimination and the C[double bond, length as m-dash]C bond formation step in base-promoted aldol condensation have a strong influence on the overall rate of the reaction, in contrast to the well-accepted first enolization or C-C bond formation step. Here, applying theoretical models to the prototypical reaction of chalcone formation, the complete free energy profile of Claisen-Schmidt condensation is assessed, revealing how a protic solvent and a slight increase in temperature can induce the second enolization as the rate-controlling step (RCS). It is also observed: i) the nonexistence of a step with a much higher energetic barrier than the others, making the concept of RCS debatable; and ii) that the overall inverse kinetic isotopic effect does not exclude second enolization as a RCS in protic continuum medium. We expect that these results can expand the understanding of the decisive role of physicochemical factors on the choose of the RCS in the aldol condensation.

Temperature effect on water dynamics in tetramer phosphofructokinase matrix and the super-arrhenius respiration rate

Advances in understanding the temperature effect on water dynamics in cellular respiration are important for the modeling of integrated energy processes and metabolic rates. For more than half a century, experimental studies have contributed to the understanding of the catalytic role of water in respiration combustion, yet the detailed water dynamics remains elusive. We combine a super-Arrhenius model that links the temperature-dependent exponential growth rate of a population of plant cells to respiration, and an experiment on isotope labeled ¹⁸O₂ uptake to H₂¹⁸O transport role and to a rate-limiting step of cellular respiration. We use Phosphofructokinase (PFK-1) as a prototype because this enzyme is known to be a pacemaker (a rate-limiting enzyme) in the glycolysis process of respiration. The characterization shows that PFK-1 water matrix dynamics are crucial for examining how respiration (PFK-1 tetramer complex breathing) rates respond to temperature change through a water and nano-channel network created by the enzyme folding surfaces, at both short and long (evolutionary) timescales. We not only reveal the nano-channel water network of PFK-1 tetramer hydration topography but also clarify how temperature drives the underlying respiration rates by mapping the channels of water diffusion with distinct dynamics in space and time. The results show that the PFK-1 assembly tetramer possesses a sustainable capacity in the regulation of the water network toward metabolic rates. The implications and limitations of the reciprocal-activation-reciprocal-temperature relationship for interpreting PFK-1 tetramer mechanisms are briefly discussed.