Parameters connectivity indices

Keywords Growth inhibition activity, QSAR, physicochemical parameters, connectivity indices, MLR... 

Saxena, A.K. (1995a). Physicochemical Significance of Topological Parameters, Connectivity Indices and Information Content. Part 1 Correlation Studies in the Sets with Aromatic and Aliphatic Substituents. Quant. Struct.-Act. Relat., 14,31-38. 

Saxena, A.K. (1995b) Physico-chemical significance of topological parameters. Connectivity indices and information content. Part 2. Correlation... 

Molecular Connectivity Indexes and Graph Theory. Perhaps the chief obstacle to developing a general theory for quantification of physical properties is not so much in the understanding of the underlying physical laws, but rather the inabiUty to solve the requisite equations. The plethora of assumptions and simplifications in the statistical mechanics and group contribution sections of this article provide examples of this. Computational procedures are simplified when the number of parameters used to describe the saUent features of a problem is reduced. Because many properties of molecules correlate well with stmctures, parameters have been developed which grossly quantify molecular stmctural characteristics. These parameters, or coimectivity indexes, are usually based on the numbers and orientations of atoms and bonds in the molecule. 

As computing capabiUty has improved, the need for automated methods of determining connectivity indexes, as well as group compositions and other stmctural parameters, for existing databases of chemical species has increased in importance. New naming techniques, such as SMILES, have been proposed which can be easily translated to these indexes and parameters by computer algorithms. Discussions of the more recent work in this area are available (281,282). SMILES has been used to input Contaminant stmctures into an expert system for aquatic toxicity prediction by generating LSER parameter values (243,258). 

On the basis of data obtained the possibility of substrates distribution and their D-values prediction using the regressions which consider the hydrophobicity and stmcture of amines was investigated. The hydrophobicity of amines was estimated by the distribution coefficient value in the water-octanole system (Ig P). The molecular structure of aromatic amines was characterized by the first-order molecular connectivity indexes ( x)- H was shown the independent and cooperative influence of the Ig P and parameters of amines on their distribution. Evidently, this fact demonstrates the host-guest phenomenon which is inherent to the organized media. The obtained in the research data were used for optimization of the conditions of micellar-extraction preconcentrating of metal ions with amines into the NS-rich phase with the following determination by atomic-absorption method. 

TTie structural features are represented by molecular descriptors, which are numeric quantities related directly to the molecular structure rather than physicochemical properties. Examples of such descriptors include molecular weight, molecular connectivity indexes, molecular complexity (degree of substitution), atom counts and valencies, charge, molecular polarizability, moments of inertia, and surface area and volume. Once a set of descriptors has been developed and tested to remove interdependent/collinear variables, a linear regression equation is developed to correlate these variables with the retention parameter of interest, e.g., retention index, retention volume, or partition coefficient The final equation includes only those descriptors that ate statistically significant and provide the best fit to the data. For more details on QSRR and the development and use of molecular descriptors, the reader is referred to the literature [188,195,198,200-202 and references therein]. 

The aforementioned macroscopic physical constants of solvents have usually been determined experimentally. However, various attempts have been made to calculate bulk properties of Hquids from pure theory. By means of quantum chemical methods, it is possible to calculate some thermodynamic properties e.g. molar heat capacities and viscosities) of simple molecular Hquids without specific solvent/solvent interactions [207]. A quantitative structure-property relationship treatment of normal boiling points, using the so-called CODESS A technique i.e. comprehensive descriptors for structural and statistical analysis), leads to a four-parameter equation with physically significant molecular descriptors, allowing rather accurate predictions of the normal boiling points of structurally diverse organic liquids [208]. Based solely on the molecular structure of solvent molecules, a non-empirical solvent polarity index, called the first-order valence molecular connectivity index, has been proposed [137]. These purely calculated solvent polarity parameters correlate fairly well with some corresponding physical properties of the solvents [137]. 

To derive these equations, log P (hydrophobic parameter), MR (molar refrac-tivity index), and MV (molar volume) were calculated using software freely available on the internet (wwwlogP.com, www.daylight.com). The first-order valence molecular connectivity index of substituents was calculated as suggested by Kier and Hall [46,47]. In these equations, is cross-vahdated obtained by the leave-one-out jackknife procedure. Its value higher than 0.6 defines the good predictive ability of the equation. The different indicator variables in these equations were defined as follows. 

Jinno and Kawasaki also obtained the best correlations between log k and topological index x. van der Waals volume (Vw)> and hydrophobic parameter (log P) for alkylbenzenes separated on reversed-phase C2, Cg, and Cl 8 columns by HPLC (r>0.94). In addition, Smith presented relationships between log k and connectivity index x for alkylbenzenes and n-alkylbenzenes separated by RP-HPLC on SAS-Hypersil and ODS-Hypersil columns (r>0.97). 

Burda et al. separated 54 alkanes (C5-C11), with different degrees of branching, by RP-HPLC on an octadecy 1-silica Lichrosorb R18 column, by using a mixture of methanol and water (80 20) as mobile phase. The connectivity index x was employed to correlate the structures of investigated alkanes with their obtained retention parameter, log Jd. 

Bojarski, J. and Ekiert, L. (1983). Evaluation of Modified Valence Molecular Connectivity Index for Correlation of Chromatographic Parameters. J. Liquid Chromat., 6,73. 

Markowki, W, Dzido, T. and Wawrzynowicz, T. (1 8). Correlation Between Chromatographic Parameters and Connectivity Index in Liquid-Solid Chromatography. PoU.Chem., 52,2063. 

A variety of parameters are included into the QSAR equation. Log P is a commonly used parameter and is obtained from Medchem or estimated using the CLOGP3 computer program. Molecular weight is calculated. In interspecies models the LD50 or LC50 value is incorporated as a typical parameter. Molecular connectivity indexes, electronic charge distributions, and kappa environmental descriptors have been proven as powerful predictors of toxicity. The efficacy of these values lies in the fact that each of these parameters describes a molecule in a fashion similar to that actually seen by the molecular receptors that initiate a toxic response. Substructural keys are identified with the help of the MOLSTAC substructural key system. MOLSTAC consists of five classes of descriptors ... 

Hunt et al. have used ab initio methods to study ion pairs in l-butyl-3-methylimidazolium (Bmim) ILs. The anions were Cl, BF4 , and NTf2". The authors established relationships between ion-pair association energy and a derived parameter called the connectivity index . Overall, the results suggest that Bmim-Cl forms a strongly connected and quite highly structured network, which leads to the rather high viscosity observed experimentally. In contrast, Bmim-NTf2 only forms a rather weak network, where the connectivity and the viscosity are much lower [106],... 

Variable connectivity index, variable Balaban index, and variable Zagreb indices for 2-pentanol. A(x, y) and D(x, y) are the variable augmented adjacency matrix and the variable augmented distance matrix, respectively. VS, indicates the matrix row sums x and y are the variable parameters for carbon and oxygen atom, respectively. 

Sardana, S. and Madan. A.K. (2002a) Application of graph theory relationship of antimycobacterial activity of quinolone derivatives with eccentric connectivity index and Zagreb group parameters. MATCH Commun. Math. Comput. Chem., 45, 35-53. 

An additional connectivity index (°%), the geometrical parameter Nrot, and the atomic correction term Ngj, were used along with 1%v in the final fit. Weight factors of 100/Cps(exp)... 

Table 4.3. Experimental change ACp of the heat capacity at the glass transition in J/(mole K), the geometrical parameter NBBrol used in the correlation, and the fitted values of ACp, for 89 polymers. The connectivity index 1%v, which is also used in the correlation, is listed in Table 2.2. The alternative set of values listed in Table 2.3 is used for the silicon-containing polymers. The 33 ACp(exp) values listed in parentheses are those for which there is a question mark in parentheses ( ) for the appropriate number of "mobile beads" in the tabulations [3,34],... 

Saxena AK. Physicochemical significance of topological parameters molecular connectivity index and information content Part 2. Correlation studies with molar refractivity and lipophilicity. Quant Struct-Act Relat 1995 14 142-148. 

G. Szasz, O. Papp, J. Vamos, K, Hanko-Novak, and L. B. Kier,/. Chromatogr., 269, 144 (1984). Relationships Between Molecular Connectivity Indexes, Partition Coefficients and Chromatographic Parameters. 

Three major approaches to the prediction of aqueous solubility of organic chemicals using Quantitative Structure Activity Relationship (QSAR) techniques arc reviewed. The rationale behind six QSAR models derived from these three approaches, and the quality of their fit to the experimental data are summarized. Their utility and predictive ability are examined and compared on a common basis. Three of the models employed octanol-water partition coefficient as the primary descriptor, while two others used the solvatochromic parameters. The sixth model utilized a combination of connectivity indexes and a modified polarizability parameter. Considering the case of usage, predictive ability, and the range of applicability, the model derived from the connectivity- polarizability approach appears to have greater utility value. 

ASf- Entropy of fusion oX,oXv- molecular connectivity indexes 0 - polarizability parameter. 

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