Electrotopological Indices Research Articles

Comparative Study of Molecular Docking, Structural, Electronic, Vibrational Spectra and Fukui Function Studies of Thiadiazole Containing Schiff Base – A Complete Density Functional Study

A detailed first principle study on the three thiadiazole containing Schiff base ligands having phenol, chloro and bromo combinations has been carried out [Density functional theory-DFT/B3LYP/6-311 G (d, p)]. The calculated structural properties show close resemblance with the literature data. The vibrational spectra of phenol-substituted molecule is calculated and compared with those obtained with experimental FTIR (Fourier Transform infrared spectroscopy) while for chloro-and bromo-substituted, it is predicted theoretically with vibartional assignments. TDDFT (Time dependent Density Functional Theory) calculations and Natural bond (NBO) analysis of title molecules have been also done with same level of theory. From NBO analysis, the lone pair electron n1 (O21) plays significant role in stabilization of compound A as compared to lone pair electron of n2 (Cl26), n2 (Br26) in B and C respectively. Some biological parameter Log P and Log S (Electro-topological indices) are also calculated (molecular docking calculations) which suggests that the derivatives of the title molecule have good ability to deliver drugs in various diseases. The reactivity of molecules using various descriptors (local) such as Fukui functions, local softness and electrophilicity as well as global i.e., electronegativity, hardness, HOMO (Highest occupied molecular orbital) - LUMO (Lowest unoccupied molecular orbital) gap etc. of the same are calculated and discussed.

Terminal secondary C(sp3), aliphatic secondary C(sp2), aliphatic tertiary C(sp2), primary amine (aliphatic), ring secondary C(sp3) and imidazole numbers can be used to discriminate between cytokinins and cytokinin antagonists

One of the most widely used approaches to study cytokinin mode of action involves the use of cytokinin antagonists (anticytokinins). Despite this, few studies have compared the chemical structure of cytokinins and anticytokinins. This formed the focus of the present study, which identified a range of molecular descriptors differentiating four cytokinins from 11 cytokinins antagonists. DRAGON software (version 5.5, 2007) and CambridgeSoft ChemOffice (version 12, 2010) tools (viz. ChemDraw and Chem3D) were used to calculate 212 molecular descriptors for the cytokinins and anticytokinins studied. Only 18 descriptors showed statistically significant differences between cytokinins and antagonists. The most marked molecular descriptor differences included the following: Cytokinins did not contain terminal secondary C(sp3), primary amines (aliphatic) or ring secondary C(sp3) which were present in several antagonists; cytokinins averaged 11 times more imidazoles, 2.2 times more secondary amines (aromatic), 1.8 times more rotatable bonds, 1.6 times more pyrimidines, 1.5 times more multiple bonds, 1.5 times aromatic bonds, 1.2 times non-H bonds and 1.2 times non-N atoms. The following molecular descriptors were also higher in cytokinins: rotatable bond fraction, sum of conventional bond orders (H-depleted), sum of Kier-Hall electrotopological states, molecular weight, and unsaturation index. The molecular descriptors (18) that differed significantly between cytokinins and anticytokinins were used to generate a dendrogram which correctly classified the two groups as two independent branches. The data presented support the classification of these 15 molecules as cytokinins or cytokinin antagonists and can be explored to determine their usefulness in finding new molecules of either class. Molecular descriptors differentiate cytokinins and anticytokinins.

First report on two-fold classification of Plasmodium falciparum carbonic anhydrase inhibitors using QSAR modeling approaches.

Quantitative structure-activity relationship (QSAR)-based classification approach is one of the important chemometric tools in drug discovery process for categorizing the target protein inhibitors into more active and less active classes. In this background, we have presented here a novel approach of two-fold QSAR-based classification modeling for the Plasmodium falciparum carbonic anhydrase (PfCA) inhibitors using 2D-QSAR and linear discriminant analysis (LDA) methods. The logic of applying this concept is to ensure more accurate classification of compounds and to draw some concrete conclusion about structure-activity relations for further work, in absence of 3D-protein structure and lack of sufficient experimental data using the PfCA target. The 2D-QSAR modeling analysis suggested the importance of electrotopological, electronic, extended topochemical atom, and spatial (Jurs) indices for modeling the inhibitory activity against PfCA. The LDA model analysis showed that spatial (Jurs), electrotopological and thermodynamic indices were the discriminating features to differentiate the inhibitors into more active and less active groups. The classification ability of both the models for training and test sets was checked by different qualitative validation parameters such as sensitivity, specificity, accuracy, recall, precision, F-measure and G-means. The classification results revealed that the developed models were significant in classifying the more active inhibitors as compared to the less active inhibitors of both training and test sets. The structural features unveiled from these two models could be utilized for the selection of more active compounds against PfCA in the database screening process.

A simple electrotopological index for quantitative structure-activity relationship correlation of physical properties with biomolecular activities

Quantitative structure-activity relationship (QSAR) studies constitute a process by which the physicochemical properties of a set of chemical structures are quantitatively correlated with a measurable, such as the concentration of a substance required to give a certain therapeutic drug response. 2D-QSAR studies start with 10–20 analogues, ranging from biologically active to inactive; each analogue, regardless of bioactivity, is described by a series of descriptors. To further broaden the practical utility of these simple descriptors we have sought to identify hybrid indices which are trivial to calculate but which capture data from at least two categories of descriptors. An electrotopological descriptor, termed ET\(_\mathrm{Z}\), which combines electronic information and molecular topology, has been devised and validated against a set of 25 anticonvulsant hydantoin molecules. This ET\(_\mathrm{Z}\) is based solely on atomic connectivity information obtained from the graph without explicit input from molecular geometry.

Estimating the Octanol/Water Partition Coefficient for Aliphatic Organic Compounds Using Semi-Empirical Electrotopological Index

A new possibility for estimating the octanol/water coefficient (log P) was investigated using only one descriptor, the semi-empirical electrotopological index (ISET). The predictability of four octanol/water partition coefficient (log P) calculation models was compared using a set of 131 aliphatic organic compounds from five different classes. Log P values were calculated employing atomic-contribution methods, as in the Ghose/Crippen approach and its later refinement, AlogP; using fragmental methods through the ClogP method; and employing an approach considering the whole molecule using topological indices with the MlogP method. The efficiency and the applicability of the ISET in terms of calculating log P were demonstrated through good statistical quality (r > 0.99; s < 0.18), high internal stability and good predictive ability for an external group of compounds in the same order as the widely used models based on the fragmental method, ClogP, and the atomic contribution method, AlogP, which are among the most used methods of predicting log P.

Diprotonation process of meso-tetraphenylporphyrin derivatives designed for Photodynamic Therapy of cancers: From Multivariate Curve Resolution to predictive QSPR modeling

Tetrapyrrole rings possess four nitrogen atoms, two of which act as Bröndsted bases in acidic media. The two protonation steps occur on a close pH range, particularly in the case of meso-tetraphenylporphyrin (TPP) derivatives. If the cause of this phenomenon is well known – a protonation-induced distortion of the porphyrin ring – data on stepwise protonation constants and on electronic absorption spectra of monoprotonated TPPs are sparse. A multivariate approach has been systematically applied to a series of glycoconjugated and hydroxylated TPPs, potential anticancer drugs usable in Photodynamic Therapy. The dual purpose was determination of protonation constants and linking substitution with basicity. Hard-modeling version of MCR-ALS (Multivariate Curve Resolution Alternating Least Squares) has given access to spectra and distribution profile of pure components. Spectra of monoprotonated species (H 3TPP +) in solution resemble those of diprotonated species (H 4TPP 2+), mainly differing by a slight blue-shift of bands. Overlap of H 3TPP + and H 4TPP 2+ spectra reinforces the difficulty to evidence an intermediate form only present in low relative abundance. Depending on macrocycle substitution, p K values ranged from 3.5 ± 0.1 to 5.1 ± 0.1 for the first protonation and from 3.2 ± 0.2 to 4.9 ± 0.1 for the second one. Inner nitrogens’ basicity is affected by position, number and nature of peripheral substituents depending on their electrodonating character. p K values have been used to establish a predictive Multiple Linear Regression (MLR) model, relying on atom-type electrotopological indices. This model accurately describes our results and should be applied to new TPP derivatives in a drug-design perspective.

Development of semi‐empirical electrotopological index using the atomic charge in QSPR/QSRR models for alcohols

AbstractThe semi‐empirical electrotopological index (ISET) used for quantitative structure‐retention relationship (QSRR) models firstly developed for alkanes and alkenes, was remodeled for different organic compounds such as ketones, aldehydes and esters. In this study, the ISET was developed and optimized to describe the chromatographic retention of aliphatic alcohols on six different stationary phases (SE‐30, OV‐3, OV‐7, OV‐11, OV‐17 and OV‐25). The presence of a hydroxyl group leads to a charge redistribution increasing the interactions between these molecules and the stationary phases relative to the interactions between hydrocarbons and the same stationary phases. These considerations were included in the calculation of ISET. The simple linear regressions (SLR) between retention indices and the ISET for each stationary phase showed good statistical quality, high internal stability and good predictive ability for external groups, especially for stationary phases with low polarity. A single combined model, in which the McReynolds polarity term was added as a descriptor, was developed for all the data points for the stationary phases and the results were of satisfactory predictive quality. The efficiency and the applicability of the approach were demonstrated through the high quality quantitative structure‐property relationship (QSPR) model for the boiling point (BP). For this physical property 134 compounds were used; most of them were not included in the original data set employed to develop the ISET. Copyright © 2010 John Wiley &amp; Sons, Ltd.

Quantitative structure–retention relationship modelling of esters on stationary phases of different polarity

The semi-empirical electrotopological index, I SET, used for QSRR models, was developed and optimized to describe the chromatographic retention of saturated esters on the five different stationary phases (SE-30, OV-7, DC-710, OV-225 and XE-60). The simple linear regressions between the retention indices and the proposed index were of good statistical quality, high internal stability and good predictive ability for external groups, especially for the stationary phase with low polarity, showing that the specific molecular interactions occur on highly polar phases. For the esters, the interactions between the molecules and the stationary phase are slowly increased relative to hydrocarbons due to the charge redistribution that occurs in the presence of the heteroatom. These facts were included in the calculation of I SET through a small increase in the SET i values for heteroatoms and the carbon atoms attached to them. The increase in the SET i values originates from the dipole moment of the whole molecule and an equivalent local dipole moment related to the net charges of the atoms belonging to the functional group and the carbon atoms attached to them. The polarity of the stationary phases, indicated by the retention polarity ( P R) given by Tarján, is reflected in the intercept of the equations obtained for each stationary phase. Thus, a single combined QSRR model was generated with a satisfactory predictive quality, including a parameter that represents the polarity retention of all stationary phases studied.

Modeling the semi‐empirical electrotopological index in QSPR studies for aldehydes and ketones

AbstractThe semi‐empirical electrotopological index, ISET, used for quantitative structure–retention relationship (QSRR) models firstly developed for alkanes and alkenes, was remodeled for organic functions such as ketones and aldehydes. The ISET values for hydrocarbons are calculated through the atomic charge values obtained from a Mulliken population analysis using the semi‐empirical AM1 method and their correlation with the SETi values attributed to the different types of carbon atoms according to experimental data. For ketones and aldehydes the interactions between the molecules and the stationary phase are slowly increased relative to the hydrocarbons, due to the charge redistribution that occurs in the presence of heteroatoms. For these polar molecules the increase in the interactions was included in the calculation of the ISET values through the dipole moment of the whole molecule and also through an equivalent local dipole moment related to the net charges of the atoms of the CO and HCO functional groups. Our findings show that the best definition of an equivalent local dipole moment is clearly dependent on the specific features of the charge distribution in the polar region of the molecules (e.g. ketones and aldehydes), which allows them to be distinguished. Thus, the QSRR models for 15 aldehydes and 42 ketones obtained using the remodeled ISET were of good quality as shown by the statistical parameters. The ability of this remodeled index to include charge distribution and structural details opens a new way to study the correlations between the molecular structure and retention indices in gas chromatography. Copyright © 2009 John Wiley &amp; Sons, Ltd.

On a new semi‐empirical electrotopological index for QSRR models

AbstractA new semi‐empirical electrotopological index, ISET, for quantitative structure–retention relationships (QSRR) models was developed based on the refinement of the previously published semi‐empirical topological index, IET. We demonstrate that the values of Ci fragments that were firstly attributed from the experimental chromatographic retention and theoretical deductions have an excellent relationship with the net atomic charge of the carbon atoms. Thus, the values attributed to the vertices in the hydrogen‐suppressed graph of carbon atoms (Ci) are calculated from the correlation of the net atomic charge in each carbon atom, which is obtained from quantum chemical semi‐empirical calculations, and the Ci fragments for primary, secondary, tertiary and quaternary carbon atoms (1.0, 0.9, 0.8 and 0.7, respectively) obtained from the experimental values. This shows that IET encoded this quantum physical reality and that it is possible to calculate a new ISET (the semi‐empirical electrotopological index) through the net atomic charge values obtained from a Mulliken population analysis using the semi‐empirical AM1 method and their correlation with the values attributed to the different types of carbon atoms. This demonstrates that the ISET encodes information on the charge distribution of the solute on which dispersive and electrostatic interactions between the solute (alkanes and alkenes) and the stationary phase strongly depend. Thus, this new method can be considered as an initial step towards forthcoming QSRR/QSAR studies. Copyright © 2008 John Wiley &amp; Sons, Ltd.

QSPR CALCULATION OF AROMATICITY IN SOME FIVE-MEMBERED HETEROAROMATIC COMPOUNDS

Aromatic stabilization energies (ASE) for a set of 29 five-membered heteroaromatic compounds are calculated using molecular descriptors such as magnetic susceptibility exaltation (Λ), nucleus-independent chemical shifts (NICS), and electrotopological indices (EI) via linear, quadratic and cubic fitting polynomials. Theoretical estimations compare fairly well with experimental data when three variables multilinear regression equations are employed.

Computational models to predict blood-brain barrier permeation and CNS activity.

The blood-brain permeation of a structurally diverse set of 281 compounds was modeled using linear regression and a multivariate genetic partial least squares (G/PLS) approach. Key structural features affecting the logarithm of blood-brain partitioning (logBB) were captured through statistically significant quantitative structure-activity relationship (QSAR) models. These relationships reveal the importance of logP, polar surface area, and a variety of electrotopological indices for accurate predictions of logBB. The best models reveal an excellent correlation (r > 0.9) for a training set of 58 compounds. Likewise, the comparison of the average logBB values obtained from an ensemble of QSAR models with experimental values also verifies the statistical quality of the models (r > 0.9). The models provide good agreement (r approximately 0.7) between the predicted logBB values for 34 molecules in the external validation set and the experimental values. To further validate the models for use during the drug discovery process, a prediction set of 181 drugs with reported CNS penetration data was used. A >70% success rate is obtained by using any of the QSAR models in the qualitative prediction for CNS permeable (active) drugs. A lower success rate (approximately 60%) was obtained for the best model for CNS impermeable (inactive) drugs. Combining the predictions obtained from all the models (consensus) did not significantly improve the discrimination of CNS active and CNS inactive molecules. Finally, using the therapeutic classification as a guiding tool, the CNS penetration capability of over 2000 compounds in the Synthline database was estimated. The results were very similar to the smaller set of 181 compounds.

Use of topological indices of polychlorinated biphenyls in structure–retention relationships

Topological parameters (Balaban index and electrotopological index) were used as structural parameters in the structure–retention relationships (SRRs). These relationships were found to be statistically valid and useful in the prediction of retention data of polychlorinated biphenyls (PCBs) despite of the temperature program used in the gas chromatographic experiment.

Partially unified multiple property recursive partitioning (PUMP-RP) analyses of cyclooxygenase (COX) inhibitors.

We have carried out partially unified multiple property recursive partitioning (PUMP-RP) analyses on a database of cyclooxygenase (COX) inhibitors, using CART methods implemented in Cerius(2). Three sets of physicochemical descriptors (ISIS public keys, DAYLIGHT Fingerprints, and Cerius(2)) were computed for the database molecules which were divided into two groups, assigned as training (89%) and test (11%-selected using diversity analyses tools in Cerius(2)) sets. The descriptors which led to the discrimination of active and selective COX-2 inhibitors included ISIS Key #59 (Snot%A%A), Balaban electrotopological index JY, partition coefficient AlogP, and Jurs surface area descriptors (FNSA, FPSA, and PPSA). A strong correlation is obtained between the predicted and experimental COX-2 inhibitory activity and a moderate correlation for selectivity of the COX-2 inhibitors, both in the training and test sets. Application of the RP trees to a validation set of Merck cyclooxygenase inhibitors shows good consistency with the COX-1 and COX-2 activity data, albeit moderate consistency with the selectivity data. Compared to the independent RP models (obtained by considering each activity separately), the PUMP-RP decision trees provide easier identification and interpretation of those descriptors that are common to both COX-1 and COX-2 activities. Similarly, they are easier to distinguish the descriptors that discriminate the two activities. The study represents a preliminary validation of the PUMP-RP method described in the previous article of this issue.

QSAR: Then and Now

AbstractFor Abstract see ChemInform Abstract in Full Text.

QSPR modeling of heat of formation and heat of vaporization of aliphatic ketones by means of electrotopological indices

This work deals with the application of the electrotopological index to calculate the enthalpies of formation and vaporization of a set of 39 linear and non-linear C 4 to C 12 aliphatic ketones within the realm of QSPR theory. Two variants of this index are employed and results show the best results are obtained when the polar and hydrophobic portion of the molecules are taken into consideration.

QSAR: then and now.

In this review, the evolution of QSAR is traced from the insightful observations of Crum-Brown and Frazier to Hammett's critical equations and finally Hansch's seminal contributions on hydrophobicity and modelling of biological activity based on extrathermodynamic principles. Today's QSAR models can stand alone, augment other graphical approaches or be examined in tandem with equations of a similar mechanistic genre to truly reveal the power of the paradigm. This review will focus on the three standard classifications routinely used in QSAR analysis electronic, hydrophobic, and steric, as well as topological indices. Electronic parameters will focus on Hammett sigma constants and their numerous variations. Dipole moments, hydrogen bond descriptors and quantum chemical indices as well as applications of their utilization will be described. The hydrophobicity parameter will be examined by tracing its early history, its operational definition and its determination by either experimental methods or computational calculations. Steric parameters, which run the gamut from size to shape, will be described by Taft's, Hancock's, Charton's, Fujita's, Verloop's and Simon's contributions. Topological effects, delineated by connectivity indices, kappa shape and electrotopological indices of Kier and Hall are also described. Examples of QSAR models incorporating most of these parameters are reviewed. In cases where the 95% confidence intervals of variables are available, they are listed in parentheses. A brief Comparative QSAR analysis of non-nucleoside reverse transcriptase inhibitors (NNRTI's) is outlined and various models obtained by different groups examining 4, 5, 6, 7-tetrahydro-5-methylimidazo [4, 5,1-j,k][1,4] benzodiazepin-2(1H)-ones (TIBO) and 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)-thymine (HEPT) derivatives are compared for mechanistic insight that could be useful in the process of inhibitor design.

SAR/QSAR approaches to solubility, partitioning and sorption of phthalates

The environmental behavior of xenobiotics such as phthalates is closely connected to parameters such as are solubility (C w sat), partitioning (e.g. K ow) and sorption (e.g. K oc). In this paper the solubility, octanol-water partitioning and sorption of a series of phthalic acid esters are described through various SAR/QSAR concepts including molecular connectivity indices (MCI), electrotopological atomic state indices (EASI) and group-contribution (UNIFAC). Advantages and disadvantages of MCI and UNIFAC based QSAR's for phthalates are discussed. The water solubility as well as the octanol - water partitioning are satisfactorily calculated by application of UNIFAC-derived activity coefficients. Octanol-water partitioning and sorption, but to a lesser extent solubility are, according to MCI analyses, well correlated to molecular size. Octanol-water partitioning and sorption, but to a lesser extent solubility are, according to EASI analyses, well correlated to hydrophobicity as expressed by the “alkyl- group” electrotopological index. The latter correlations is further improved by introducing the polar component as expressed by the “ester- group” electrotopological index.

On Flexible Fitting Using The Molecular Similarity Index. A neural network analysis for antileishmaniasis compounds

AbstractPentamidine analogues bind to the minor groove by using the pharmacophoric conformation as being isohelical do DNA. A QSAR model has disclosed three physiochemical descriptors as being important for such compounds against Leishmania mexicana amazonensis: Clog P, electrotopological index and Carbo similarity index. A comparison of the QSAR equation derived from multiple regression analysis, MRA, and the one from neural network analysis, NN, shows the latter to be of higher significance.