Alkanes with the First Three Maximal/Minimal Modified First Zagreb Connection Indices.

The modified first Zagreb connection index ( ) is a molecular descriptor, which was initially appeared within a formula of the total electron energy of alternant hydrocarbons in 1972. In a recent paper [A. Ali, N.

A Novel/Old Modification of the First Zagreb Index.

In the seminal paper [I. Gutman, N. Trinajstić, Chem.

The sum-connectivity index--an additive variant of the Randic connectivity index.

This review discusses structure-property modeling applications of a novel variant of the Randic connectivity index that is called the sum-connectivity index. We compare published one-descriptor quantitative structure-property relationship (QSPR) models obtained with the new sum-connectivity index and with the Randic connectivity index, called here the product-connectivity index. Additionally, the efficiency of both variants of connectivity indices in QSPR modeling is tested on five datasets of alkanes and two datasets of polycyclic hydrocarbons.

Master connectivity index and master connectivity polynomial.

We give the standard expressions of the Zagreb indices, Randić indices and their variants. Then we present the master connectivity index and show how this index can generate all connectivity indices of both varieties. We also present the master connectivity polynomial and show the relationship between this polynomial and the master connectivity index.

On sum-connectivity matrix and sum-connectivity energy of (molecular) graphs.

If G is a (molecular) graph with n vertices, and di is the degree of its i-th vertex, then the sum-connectivity matrix of G is the n × n matrix whose (i, j) -entry is equal to 1/√di + dj if the i-th and the j-th vertices are adjacent and 0 otherwise. The sum-connectivity energy of a graph G is defined as the sum of the absolute values of the eigenvalues of the sum-connectivity matrix. Some properties including upper and lower bounds for the eigenvalues of the sum-connectivity matrix and the sum-connectivity energy are established, and the extremal cases are characterized.

Antioxidant QSAR modeling as exemplified on polyphenols.

Methodology for deriving quantitative structure-activity relationship (QSAR) models based on computed molecular descriptors, representing numerically structural features of polyphenols, and applicable to the antioxidant activity of polyphenols is delineated. The application of this methodology is illustrated on a data set of 100 polyphenols. Prior to the computation of molecular descriptors, molecular structures are coded in the SMILES form, a computer-acceptable version of structure, and then converted to the 3D form by the CORINA program.

Bond dissociation enthalpies calculated by the PM3 method confirm activity cliffs in radical scavenging of flavonoids.

Radical scavenging potency of flavonoids is associated with activity cliffs, i.e., small chemical modifications on flavonoid core can have a significant effect on activity.

On use of the variable Zagreb vM2 index in QSPR: boiling points of benzenoid hydrocarbons.

The variable Zagreb (v)M(2) index is introduced and applied to the structure-boiling point modeling of benzenoid hydrocarbons. The linear model obtained (the standard error of estimate for the fit model S(fit)=6.8 degrees C) is much better than the corresponding model based on the original Zagreb M2 index (S(fit)=16.

SAR and QSAR of the antioxidant activity of flavonoids.

Flavonoids are a group of naturally occurring phytochemicals abundantly present in fruits, vegetables, and beverages such as wine and tea. In the past two decades, flavonoids have gained enormous interest because of their beneficial health effects such as anti-inflammatory, cardio-protective and anticancer activities. These findings have contributed to the dramatic increase in the consumption and use of dietary supplements containing high concentrations of plant flavonoids.

Toxicity of aliphatic ethers: a comparative study.

The CROMRsel procedure was used to model the toxicity of aliphatic ethers against mice. The best model obtained is based on three molecular descriptors and is a better model than other QSAR models from the literature. The only comparable model is one by Ren, based on four descriptors.

On reformulated Zagreb indices.

Zagreb indices were reformulated in terms of the edge-degrees instead of the vertex-degrees as the original Zagreb indices. Three types of Zagreb indices were considered: original, modified and variable Zagreb indices. It is found that the optimum exponent of the variable reformulated Zagreb M2 index (v = -1/2) is identical with the exponent of the vertex-connectivity index, which is the most used topological index in QSPR and QSAR.

Random walks and chemical graph theory.

Simple random walks probabilistically grown step by step on a graph are distinguished from walk enumerations and associated equipoise random walks. Substructure characteristics and graph invariants correspondingly defined for the two types of random walks are then also distinct, though there often are analogous relations. It is noted that the connectivity index as well as some resistance-distance-related invariants make natural appearances among the invariants defined from the simple random walks.

Use of variable selection in modeling the secondary structural content of proteins from their composition of amino acid residues.

The possibility of prediction of protein secondary structure content from composition of their amino acid residues can help in bridging the gap between proteins of known primary sequence having an unknown secondary structure. Almost all recently published models for understanding the relationship between composition (frequency of occurrence) of amino acid residues and secondary structure content of proteins involved composition of all 20 amino acid residues. However, it is well-known that many amino acid residues are mutually similar according to their physicochemical properties (hydrophobicity, hydrophilicity, charge, size, etc.

Atomic walk counts of negative order.

Atomic walk counts (awc's) of order k (k > or = 1) are the number of all possible walks of length k which start at a specified vertex (atom) i and end at any vertex j separated by m (0 < or = m < or = k) edges from vertex i. The sum of atomic walk counts of order k is the molecular walk count (mwc) of order k. The concept of atomic and molecular walk counts was extended to zero and negative orders by using a backward algorithm based on the usual procedure used to obtain the values of mwc's.

Toward generating simpler QSAR models: nonlinear multivariate regression versus several neural network ensembles and some related methods.

In this study we want to test whether a simple modeling procedure used in the field of QSAR/QSPR can produce simple models that will be, at the same time, as accurate as robust Neural Network Ensemble (NNE) ones. We present results of application of two procedures for generating/selecting simple linear and nonlinear multiregression (MR) models: (1) method for selecting the best possible MR models (named as CROMRsel) and (2) Genetic Function Approximation (GFA) method from the Cerius2 program package. The obtained MR models are strictly compared with several NNE models.

Nanotubes: number of Kekulé structures and aromaticity.

Carbon nanotubes (CNTs) are composed of cylindrical graphite sheets consisting of sp(2) carbons. Due to their structure CNTs are considered to be aromatic systems. In this work the number of Kekulé structures (K) in "armchair" CNTs was estimated by using the transfer matrix technique.