Improved molecular descriptors based on the optimization of correlation weights of local graph invariants

We report the calculation of boiling points for several alkyl alcohols through the use of improved molecular descriptors based on the optimization of correlation weights of local invariants of graphs. As local invariants we have used the presence of different chemical elements (i.e. C, H, and O) and the existence of different vertex degree values (i.e. 1, 2, 3 and 4). The inherent flexibility of the chosen molecular descriptor seems to be rather suitable to obtain satisfactory enough predictions of the property under study. Comparison with other similar approximation reveals a very good behavior of the present method. The use of higher order polynomials do not seem to be necessary to improve results regarding the simple linear fitting equations. Some possible future extensions are pointed out in order to achieve a more definitive conclusion about this approximation

QSAR based on hybrid optimal descriptors as a tool to predict antibacterial activity against Staphylococcus aureus

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Structure-toxicity relationships for aliphatic compounds based on Correlation Weighting of Local Graph Invariants

Quantitative Structure-Activity Relationships based on molecular descriptors calculated with Correlation Weights of Local Graph Invariants were developed to model the toxicity of aliphatic compounds to the 50% population growth inhibition. The relationships were computed on the basis of Labeled Hydrogen- Filled Graphs and correlation weights were obtained by an optimization to render as large as possible correlation coefficients between log(IGC 50-1) and descriptors calculated with correlation weights. Morgan extended connectivity indices of zero, first, and second orders, paths of lengths two and three and valence shells of second and third ranges have been tested as local invariants of the Labeled Hydrogen-Filled Graphs. The best quantitative relationship obtained from the optimization of correlation weights is that one based on the valence shell of range two. First, second, and third order fitting equations were determined and statistical results are better than other similar data for the same molecular set

Structure-toxicity relationships for aliphatic compounds based on Correlation Weighting of Local Graph Invariants

Quantitative Structure-Activity Relationships based on molecular descriptors calculated with Correlation Weights of Local Graph Invariants were developed to model the toxicity of aliphatic compounds to the 50% population growth inhibition. The relationships were computed on the basis of Labeled Hydrogen- Filled Graphs and correlation weights were obtained by an optimization to render as large as possible correlation coefficients between log(IGC 50-1) and descriptors calculated with correlation weights. Morgan extended connectivity indices of zero, first, and second orders, paths of lengths two and three and valence shells of second and third ranges have been tested as local invariants of the Labeled Hydrogen-Filled Graphs. The best quantitative relationship obtained from the optimization of correlation weights is that one based on the valence shell of range two. First, second, and third order fitting equations were determined and statistical results are better than other similar data for the same molecular set.Facultad de Ciencias Exacta

Usporedba QSPR modela zasnovanih na vodikom-popunjenim molekularnim grafovima i na grafovima atomskih orbitala

QSPR models are studied for normal boiling points of alkanes, alkylbenzenes, and polyaromatic hydrocarbons, in terms of optimized correlation weights of local invariants of the hydrogen- -filled graphs (HFGs) and of the graphs of atomic orbitals (GAOs). Morgan extended connectivities of the zeroth, first, and second order of the HFGs and GAOs were employed. The best QSPR model obtained is based on optimized correlation weights of the extended connectivity of the first order of the GAO. The statistical characteristics of this model are: n = 70, r superscript(2) = 0.9988, s = 5.8 °C, F = 57437 (training set); n = 70, r superscript(2) = 0.9985, s = 6.7 °C, F = 45154 (test set).Istraživani su QSPR modeli za normalnu točku vrelišta alkana, alkilbenzena i poliaromatskih ugljikovodika, zasnovani na optimiziranim korelacijskim te`inama lokalnih invarijanti vodikom-popunjenih molekularnih grafova (HFG) i grafova atomskih orbitala (GAO). Primjenjeni su Morganovi indeksi proširene povezanosti nultoga, prvoga i drugoga reda, kako za HFG tako i za GAO. Najbolji QSPR model je dobiven na osnovi optimiziranih korelacijskih težina za proširenu povezanost prvoga reda za GAO. Statističke karakteristike ovoga modela su: n = 70, r superscript(2) = 0.9988, s = 5.8 °C, F = 57437 (training set); n = 70, r superscript(2) = 0.9985, s = 6.7 °C, F = 45154 (test set)

Maximum topological distances based indices as molecular descriptors for QSPR : 4. Modeling the enthalpy of formation of hydrocarbons from elements

The enthalpy of formation of a set of 60 hydroarbons is calculated on the basis of topological descriptors defined from the distance and detour matrices within the realm of the QSAR/QSPR theory. Linear and non-linear polynomials fittings are made and results show the need to resort to higher-order regression equations in order to get better concordances between theoretical results and experimental available data. Besides, topological indices computed from maximum order distances seems to yield rather satisfactory predictions of heats of formation for hydrocarbons.Facultad de Ciencias Exacta

Special issue on flexible molecular descriptors

Molecular indices are characterized by fixed numerical values, which are independent of the physical chemistry property or/and biological activity considered. Once the bonding pattern of a molecule is defined they can then be computed. Contrarily, variable indices depend on the property/activity under consideration. Thus, variable descriptors are functions instead of numerical data and they change during the regression analysis. This more general definition of molecular indices has offered a powerful tool for studies within the realm of QSAR/QSPR theory and it has enabled authors to surmount the so called “nightmare of molecular descriptors”. This drawback arises when one has to choose among a huge number of possibilities to assign a set of molecular descriptors to perform a given study. In fact, the optimization of molecular descriptors for the particular application makes it unnecessary to focus the attention on the choice of a particular set of indices and the efforts can then be directed towards the suitable search of the best mathematical algorithm to obtain the corresponding flexible descriptors. (Párrafo extraído del texto a modo de resumen)Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA

QSPR calculation of normal boiling points of organic molecules based on the use of correlation weighting of atomic orbitals with extended connectivity of zero- and first-order graphs of atomic orbitals

We report the results of a calculation of the normal boiling points of a representative set of 200 organic molecules through the application of QSPR theory. For this purpose we have used a particular set of flexible molecular descriptors, the so called Correlation Weighting of Atomic Orbitals with Extended Connectivity of Zero- and First-Order Graphs of Atomic Orbitals. Although in general the results show suitable behavior to predict this physical chemistry property, the existence of some deviant behaviors points to a need to complement this index with some other sort of molecular descriptors. Some possible extensions of this study are discussed.SCOPU

An Improved QSPR Modeling of Hydrocarbon Dipole Moments

Dipole moments of hydrocarbons are not an easy property to model with conventional 2D descriptors. A comparison of the performance of the most commonly used sets of topological descriptors is presented, each set containing descriptors derived from the regular and Detour distance matrix, Electrotopological State Indices, and the basic number of atoms of each type and bonds. Data were taken on a representative set of 35 hydrocarbon dipole moments previously reported and the classical multivariable regression analysis for establishing the models is employed

QSPR modeling aqueous solubility of polychlorinated biphenyls by optimization of correlation weights of local and global graph invariants

Aqueous solubilities of polychlorinated biphenyls have been correlated with topological molecular descriptors which are functions of local and global invariants of labeled hydrogen filled graphs. Morgan extended connectivity and nearest neighboring codes have been used as local graph invariants. The number of chlorine atoms in biphenyls has been employed as a global graph invariant. Present results show that taking into account correlation weights of global invariants gives quite reasonable improvement of statistical characteristics for the prediction of aqueous solubilities of polychlorinated biphenyls.Instituto de Investigaciones Fisicoquímicas Teóricas y AplicadasFacultad de Ciencias Exacta