Ana-Maria Putz

Spectral Inverse Quantum (Spectral-IQ) Method for Modeling Mesoporous Systems: Application on Silica Films by FTIR

The present work advances the inverse quantum (IQ) structural criterion for ordering and characterizing the porosity of the mesosystems based on the recently advanced ratio of the particle-to-wave nature of quantum objects within the extended Heisenberg uncertainty relationship through employing the quantum fluctuation, both for free and observed quantum scattering information, as computed upon spectral identification of the wave-numbers specific to the maximum of absorption intensity record, and to left-, right- and full-width at the half maximum (FWHM) of the concerned bands of a given compound. It furnishes the hierarchy for classifying the mesoporous systems from more particle-related (porous, tight or ionic bindings) to more wave behavior (free or covalent bindings). This so-called spectral inverse quantum (Spectral-IQ) particle-to-wave assignment was illustrated on spectral measurement of FT-IR (bonding) bands’ assignment for samples synthesized within different basic environment and different thermal treatment on mesoporous materials obtained by sol-gel technique with n-dodecyl trimethyl ammonium bromide (DTAB) and cetyltrimethylammonium bromide (CTAB) and of their combination as cosolvents. The results were analyzed in the light of the so-called residual inverse quantum information, accounting for the free binding potency of analyzed samples at drying temperature, and were checked by cross-validation with thermal decomposition techniques by endo-exo thermo correlations at a higher temperature.

Quantum-SAR Extension of the Spectral-SAR Algorithm. Application to Polyphenolic Anticancer Bioactivity

Aiming to assess the role of individual molecular structures in the molecular mechanism of ligand-receptor interaction correlation analysis, the recent Spectral-SAR approach is employed to introduce the Quantum-SAR (QuaSAR) “wave” and “conversion factor” in terms of difference between inter-endpoint inter-molecular activities for a given set of compounds; this may account for inter-conversion (metabolization) of molecular (concentration) effects while indicating the structural (quantum) based influential/detrimental role on bio-/eco- effect in a causal manner rather than by simple inspection of measured values; the introduced QuaSAR method is then illustrated for a study of the activity of a series of flavonoids on breast cancer resistance protein.

Alert-QSAR. Implications for Electrophilic Theory of Chemical Carcinogenesis

Given the modeling and predictive abilities of quantitative structure activity relationships (QSARs) for genotoxic carcinogens or mutagens that directly affect DNA, the present research investigates structural alert (SA) intermediate-predicted correlations ASA of electrophilic molecular structures with observed carcinogenic potencies in rats (observed activity, A = Log[1/TD50], i.e., ASA=f(X1SA,X2SA,…)). The present method includes calculation of the recently developed residual correlation of the structural alert models, i.e., ARASA=f(A−ASA,X1SA,X2SA,…). We propose a specific electrophilic ligand-receptor mechanism that combines electronegativity with chemical hardness-associated frontier principles, equality of ligand-reagent electronegativities and ligand maximum chemical hardness for highly diverse toxic molecules against specific receptors in rats. The observed carcinogenic activity is influenced by the induced SA-mutagenic intermediate effect, alongside Hansch indices such as hydrophobicity (LogP), polarizability (POL) and total energy (Etot), which account for molecular membrane diffusion, ionic deformation, and stericity, respectively. A possible QSAR mechanistic interpretation of mutagenicity as the first step in genotoxic carcinogenesis development is discussed using the structural alert chemoinformation and in full accordance with the Organization for Economic Co-operation and Development QSAR guidance principles.

Parabolic Reactivity “Coloring” Molecular Topology: Application to Carcinogenic PAHs

The ability to derive colored representations of widely employed distance-based topological indices from chemical reactivity electronegativity and chemical hardness has been developed in the novel theoretical tool presented in this work to provide novel, mean- ingful topo-reactive or structure-reactivity indices with application to polycyclic aromatic hydrocarbons (PAHs). The model, which com- bines topological and ab initio molecular structural information, relies on the so-called Timisoara-Parma rule for assigning the axial dis- tribution of electronegativity and chemical hardness to a given molecular structure based on a compact finite-difference (CFD) hierarchy, which involves ordering nine forms of electronegativity and chemical hardness derivative-based definitions within conceptual density functional theory (DFT). The results are in good agreement with theoretical and experimental properties improving the predictive power of standard topological indices. The proposed method is suitable for molecular structures with delocalized electrons.

Introducing Catastrophe-QSAR. Application on Modeling Molecular Mechanisms of Pyridinone Derivative-Type HIV Non-Nucleoside Reverse Transcriptase Inhibitors

The classical method of quantitative structure-activity relationships (QSAR) is enriched using non-linear models, as Thom’s polynomials allow either uni- or bi-variate structural parameters. In this context, catastrophe QSAR algorithms are applied to the anti-HIV-1 activity of pyridinone derivatives. This requires calculation of the so-called relative statistical power and of its minimum principle in various QSAR models. A new index, known as a statistical relative power, is constructed as an Euclidian measure for the combined ratio of the Pearson correlation to algebraic correlation, with normalized t-Student and the Fisher tests. First and second order inter-model paths are considered for mono-variate catastrophes, whereas for bi-variate catastrophes the direct minimum path is provided, allowing the QSAR models to be tested for predictive purposes. At this stage, the max-to-min hierarchies of the tested models allow the interaction mechanism to be identified using structural parameter succession and the typical catastrophes involved. Minimized differences between these catastrophe models in the common structurally influential domains that span both the trial and tested compounds identify the “optimal molecular structural domains” and the molecules with the best output with respect to the modeled activity, which in this case is human immunodeficiency virus type 1 HIV-1 inhibition. The best molecules are characterized by hydrophobic interactions with the HIV-1 p66 subunit protein, and they concur with those identified in other 3D-QSAR analyses. Moreover, the importance of aromatic ring stacking interactions for increasing the binding affinity of the inhibitor-reverse transcriptase ligand-substrate complex is highlighted.

Chemical Structure-Biological Activity Models for Pharmacophores’ 3D-Interactions

Within medicinal chemistry nowadays, the so-called pharmaco-dynamics seeks for qualitative (for understanding) and quantitative (for predicting) mechanisms/models by which given chemical structure or series of congeners actively act on biological sites either by focused interaction/therapy or by diffuse/hazardous influence. To this aim, the present review exposes three of the fertile directions in approaching the biological activity by chemical structural causes: the special computing trace of the algebraic structure-activity relationship (SPECTRAL-SAR) offering the full analytical counterpart for multi-variate computational regression, the minimal topological difference (MTD) as the revived precursor for comparative molecular field analyses (CoMFA) and comparative molecular similarity indices analysis (CoMSIA); all of these methods and algorithms were presented, discussed and exemplified on relevant chemical medicinal systems as proton pump inhibitors belonging to the 4-indolyl,2-guanidinothiazole class of derivatives blocking the acid secretion from parietal cells in the stomach, the 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio)thymine congeners’ (HEPT ligands) antiviral activity against Human Immunodeficiency Virus of first type (HIV-1) and new pharmacophores in treating severe genetic disorders (like depression and psychosis), respectively, all involving 3D pharmacophore interactions.

Logistic vs. W-Lambert Information in Quantum Modeling of Enzyme Kinetics

In this paper, the authors use the logistic temporal solution of the generalized Michaelis-Menten kinetics to provide a quantum basis for the tunnelling time and energy evaluations of Brownian enzymic reactions. The mono-substrate and mixed inhibition cases are treated and the associated quantum diagrams of the reaction mechanisms are depicted in terms of intermediate enzyme complexes. The methodology is suited for practically controlling the enzymic activity throughout absorption spectroscopy.

Spectral-Structure Activity Relationship (Spectral-SAR) Assessment of Ionic Liquids’ in Silico Ecotoxicity

The use of green solvents, including ionic liquids (IL), in the synthesis of new materials is currently highlighted worldwide [1-5]. The green high thermal stabilities, and can remain in the liquid state over a wide range of temperatures (from -50°C to 200°C). Furthermore, ILs exhibit low toxicity because of their exceptionally low volatility. This property is why ILs could be used as “green” alternatives to volatile organic solvents in many processes [6,7].

Bondonic Chemistry: Predicting Ionic Liquids' (IL) Bondons by Raman-IR Spectra

The notable nowadays physical-chemical structures as ionic liquids (ILs) are, due to their versatility properties adjusted by changing either the anion or cation sides, with spread applications as solvents (viz. organic reaction, bio- and nano-catalysis, polymerization), electrolytes (viz. fuel cells, batteries and sensors), lubricants and additives (including fuel additives), or in chemical engineering including separation (gas chromatography/GC-head space solvents, gas separation, membranes extraction, extractive distillation), heat storage (as thermal fluids), till the nano-technology (protein crystallization, liquids crystals and their use in monitor displays, robotics and artificial muscles), just to name few, are in the present chapter reviewed from the scientific generations created with their structural consequences; they are then used as the compounds for which the recently predicted bondon as the quantum quasi-particle of chemical bonding may be identified in the allied Raman/IR spectra through a specific algorithm involving the bondonic quantum numbers prediction in spectra and of their most tangible quantum appearance; this because the invariable four-levels for bondonic formations confirms the quantum entangled states associated with their existences, as just noted by Putz and Ori 2015, see Chap. 10 of the same monograph, while the objective realization associates either with IR or Raman of IL computed spectra; connection with experimental recorded IR spectra is also presented with encouragement perspective for bondonic observation, while correlation with eco-toxicological data (EC50) is equally presented and interpreted from a bondonic sub-atomic perspective.

Introducing “Colored” Molecular Topology by Reactivity Indices of Electronegativity and Chemical Hardness

Within the context of conceptual density functional theory chemical reactivity definitions of electronegativity (EN) and chemical hardness (HD), nine forms of their finite difference are expressed in order to consider the global “coloring” of the molecular topology with respect to their symmetry centers (atomic centers or bonding centers), according to the so-called Timisoara–Parma rule. The resulting parabolic-reactive energy in terms of EN and HD is compared with the bond topological Wiener index for short list of PAH (poly-aromatic hydrocarbons) selected as paradigmatic structures for validating the new reactivity descriptors based on topological quantities.