Molecular Connectivity Indices Research Articles

Modeling Properties with Artificial Neural Networks and Multilinear Least-Squares Regression: Advantages and Drawbacks of the Two Methods

The mean molecular connectivity indices (MMCI) proposed in previous studies are used in conjunction with well-known molecular connectivity indices (MCI) to model eleven properties of organic solvents. The MMCI and MCI descriptors selected by the stepwise multilinear least-squares (MLS) procedure were used to perform artificial neural network (ANN) computations, with the aim of detecting the advantages and limits of the ANN approach. The MLS procedure can replicate the obtained results for as long as is needed, a characteristic not shared by the ANN methodology, which, on the one hand increases the quality of a description, and on the other hand also results in overfitting. The present study also reveals how ANN methods prefer MCI relatively to MMCI descriptors. Four types of ANN computations show that: (i) MMCI descriptors are preferred with properties with a small number of points, (ii) MLS is preferred over ANN when the number of ANN weights is similar to the number of regression coefficients and, (iii) in some cases, the MLS modeling quality is similar to the modeling quality of ANN computations. Both the common training set and an external randomly chosen validation set were used throughout the paper.

Novel Atom-Type-Based Topological Descriptors for Simultaneous Prediction of Gas Chromatographic Retention Indices of Saturated Alcohols on Different Stationary Phases

In this work, novel atom-type-based topological indices, named AT indices, were presented as descriptors to encode structural information of a molecule at the atomic level. The descriptors were successfully used for simultaneous quantitative structure-retention relationship (QSRR) modeling of saturated alcohols on different stationary phases (SE-30, OV-3, OV-7, OV-11, OV-17 and OV-25). At first, multiple linear regression models for Kovats retention index (RI) of alcohols on each stationary phase were separately developed using AT and Randic’s first-order molecular connectivity (1χ) indices. Adjusted correlation coefficient (R2adj) and standard error (SE) for the models were in the range of 0.994-0.999 and 4.40-8.90, respectively. Statistical validity of the models were verified by leave-one-out cross validation (R2cv > 0.99). In the next step, whole RI values on the stationary phases were combined to generate a new data set. Then, a unified model, added McReynolds polarity term as a descriptor, was developed for the new data set and the results were satisfactory (R2adj=0.995 and SE=8.55). External validation of the model resulted in the average values of 8.29 and 8.69 for standard errors of calibration and prediction, respectively. The topological indices well covered the molecular properties known to be relevant for retention indices of the model compounds.

Diorganotin(IV) complexes of Schiff bases derived from salicylaldehyde and 2-amino-6-substituted benzothiazoles: synthesis, spectral studies, in vitro antimicrobial evaluation and QSAR studies

In the present work, Schiff base ligands (1–4) were prepared by condensation of 2-amino-6-substituted-benzothiazole and salicyaldehyde in a 1:1 molar ratio and were further treated with diorganotindichloride R’2SnCl2 leading to a series of organotin(IV) complexes (5–20) of type R’2SnL1−4Cl [R’ = Ph, Bu, Et, Me]. The prepared Schiff base ligands and the organotin(IV) complexes were characterized by various spectroscopic techniques (1H, 13C, 119Sn NMR, FT-IR) and physical techniques. All the synthesized compounds were evaluated for in vitro antibacterial and antifungal activity against two Gram positive bacterial strains B. cereus, S. aureus, two Gram negative bacterial strains E. coli, P. aeruginosa and two fungal strains A. niger and A. flavus by serial dilution method. The spectral data revealed that the complexes were pentacoordinated with bidentate ligands coordinated through oxygen and nitrogen. The results of antimicrobial activity revealed that the synthesized complexes were more toxic towards Gram positive bacterial strains as compared to Gram negative bacterial strains. From the results of QSAR analysis, it was indicated that the antimicrobial activity of the synthesized compounds were controlled by topological parameters (molecular connectivity indices).

A novel concept of Q-markers: Molecular connectivity index

BackgroundDrugs derived from botany have been playing essential role in both clinical treatment and pharmaceutical industry, unfortunately our worry is still that its quality and therapeutic efficacy are inconsistent. Recently many scientists launched a new project on quality (Q)-marker of medicinal herbs, this study was thus designed to generate a novel concept of quality (Q)-markers: molecular connectivity index (MCI), and to test and verify the new concept of molecular connectivity index (MCI). MethodsThe first-order term (1χ) was selected to calculate and study quality (Q)-marker for TCM. Houttuynia cordata Thunb. (HCT) was adopted as a model to verify the hypothesis. Volatile oils of HCT were determined using gas chromatography-mass (GC–MS). SIMCA 13.0 and SPSS 21.0 were used to deal with the data. ResultsThe minimum of the MCI values was 1.273, belonging to the peak 15, but the maximum (12.822) belonged to the peak 34, and the average value of fifty volatile oils was 5.798. The results demonstrated that MCI was the principle component, and monoterpenoid and sesquiterpenoid were also the principle components in oils. Fig. 2a shows peak 5, 24, 34 were the significant ingredients, while Fig. 2b shows peak 2, 5, 24 were the significant components. ConclusionThe data demonstrated that MCI was associated with the structure of molecules and the therapeutic efficacy, MCI could directly exhibit the relationship between ingredients and effectiveness of Traditional Chinese Medicine (TCM). So MCI could be a potential and promising parameter for quality (Q)-marker. Therefore, MCI may be developed as a novel potential concept to control the quality of TCM.

Simulation of the adsorption capacity of polar organic compounds and dyes from water onto activated carbons: Model development and validation

Abstract A model approach is developed to simulate the adsorption isotherms of low-molecular-weight polar organic compounds (LMWPOCs), halogenated LMWPOCs, and dye molecules onto activated carbons (AC). The models were based on the Dubinin–Astakhov equation, with the limiting pore volume of adsorbent estimated from the pore size distribution data, and the adsorption affinity of the adsorbate described by the molecular connectivity index. The models were used to simulate the adsorption data of 87 LMWPOCs onto six ACs, 25 halogenated LMWPOCs onto two ACs and 22 dyes onto three ACs. The developed models follow the experimental data fairly well, with errors of 49, 33 and 43% for the tested LMWPOCs, halogenated LMWPOCs, and dyes, respectively. This study shows that the developed model approach may provide a simple means for the estimation of adsorption capacity for LMWPOCs and dyes onto ACs in water.

QSAR studies on partition coefficients of organic compounds for polydimethylsiloxane of solid-phase microextraction devices

The solid-phase microextraction (SPME) technique has been widely applied to sample the environmental matrices for organic compounds. The success of employing SPME requires knowledge of the coating-matrix partition coefficients of analytes. Polydimethylsiloxane (PDMS) is the most widely used polymeric coating for the SPME device. In this study, the quantitative structure activity relationships (QSAR) for the PDMS-water (K fw ) and PDMS-gas partition coefficients (K fg ) of organic compounds were established using E-Dragon software and multiple linear regression analysis. K fw was significantly correlated to the BLTA96 descriptor, implying that the PDMS-water partition coefficients were primarily determined by the polarity of analyte molecules. In addition, K fg was significantly dependent on the Harary H index, i.e., molecular connectivity index or polarizability, of the organic compounds. If the organic compounds were grouped in alkanes and aromatic hydrocarbons, K fw and K fg were well proportional to their octanol–water partition coefficients. The statistical results of internal and external validation, determined by the square of the coefficient of multiple correlation (R 2 ≥ 0.865) and the leave-one-out cross-validation (Q 2 ≥ 0.751), showed that the QSAR models developed herein have good stability and great predictive power among the molecular descriptors and SPME/PDMS partition coefficients. The results of this study will facilitate the practical applications of SPME as a greener methodology.

Hydrogenation of aromatics compounds: Calculation of thermodynamic properties using molecular index connectivity

AbstractIn this work, calculation of relevant thermodynamics properties, for hydrogenation reaction of aromatics compounds, was performed using the approach of molecular topology. Among the several molecular topological indexes, the molecular connectivity indexes have been used widely for calculation methods like quantitative structure properties relationships (QSPR) and quantitative structure and activity relationships (QSAR). Standard enthalpy of formation (ΔH°f), standard Gibbs free energy of formation (ΔG°f), and heat capacity at constant pressure (Cp°) at 298.15 K for naphthalene, 1‐methylnaphthalene, 2‐methylnaphthalene, tetralin, and t‐decalin and equilibrium reaction constants were calculated and compared with experimental data reported in literature. Additionally, the results obtained for naphthalene, tetralin, and t‐decalin were compared to those obtained from Benson's method. Results show that the thermodynamics properties calculated from molecular connectivity index presented an error less than 2 % and are closer to experimental data than those from Benson's method, showing that molecular connectivity index is a promising tool for estimation of thermodynamic properties to be used in design of chemical process.

Synthesis, characterization, antimicrobial evaluation and QSAR studies of organotin(IV) complexes of Schiff base ligands of 2-amino-6-substituted benzothiazole derivatives

A series of organotin(IV) complexes of type R2SnLCl [R = Ph, Bu, Et, Me] were prepared by reaction of diorganotindichloride(IV) with Schiff base ligands, L1 = (1-[(6-ethoxy-benzothiazol-2-ylimino)-methyl]-naphthalen-2-ol), L2 = (1-[(6-nitro-benzothiazol-2-ylimino)-methyl]-naphthalen-2-ol), L3 = (1-[(6-methoxy-benzothiazol-2-ylimino)-methyl]-naphthalen-2-ol) and L4 = (1-[(6-methyl-benzothiazol-2-ylimino)-methyl]-naphthalen-2-ol) obtained from 2-amino-6-substituted benzothiazole derivatives with 2-hydroxy-1-naphthaldehyde in 1:1 molar ratio. These organotin(IV) complexes were characterized by various spectroscopic techniques (1H, 13C and 119Sn NMR, FT-IR), and physical techniques (X-ray powder diffraction analysis and elemental analysis). The coordination of the prepared complexes has been planned as pentacoordinated around the central tin atom during which ligands coordinated to tin atom in bidentate manner acted as N, O donor system. The ligands and their complexes were screened for antibacterial and antifungal activities against Gram-positive bacteria Bacillus cereus (MTCC 10072), Staphylococcus aureus (NCIM 2901), Gram-negative bacteria Escherichia coli (MTCC 732), Pseudomonas aeruginosa (MTCC 424) and fungi Aspergillus niger (MTCC 9933) and Aspergillus flavus (ATCC 76801). The output of QSAR analysis indicated that topological parameters (molecular connectivity indices) were responsible for controlling the antimicrobial activity of the synthesized compounds.

Can we estimate the critical micelle concentration of amphiphilic drug bases from molecular connectivity indices?

Self-aggregation of drugs is since many years an important topic in the pharmaceutical sciences. Drugs can aggregate similar to surfactants and thereby exhibit a critical micelle concentration (CMC). The present work focused on amphiphilic drug bases and it was aimed to predict log(CMC) based on chemical structure alone. A dataset of 35 compounds was gathered mostly form the literature and complemented with own measurements based on ultrasonic resonator technology. The hydrophilic–lipophilic balance (HLB) values of the protonated bases were calculated and provided a range of 22.9–27.4. Based on a hypothesis from surfactant sciences, it was tried to predict log(CMC) with connectivity and shape indices as well as molecular dipole moment. A fairly good model was obtained using the Randix index (RI), 3 D Wiener number (WN) and molecular dipole moment (DM) (R2 = 0.824). Interestingly, a simple linear regression of log(CMC) with the Randic index alone, resulted in an acceptable model (R2 = 0.755). The present work should help with early identification of drug bases that exhibit surfactant-like behavior and an estimation of log(CMC) values is proposed. An improved understanding of drug aggregation and prediction of log(CMC) helps to better cope with physical consequences like, for example, “anomalous” drug solubility in drug discovery and development.

Characteristics of supramolecular imprinting template on liver meridian tropism of traditional Chinese medicine based on molecular connectivity index

The molecular connectivity index was adopted to explore the characteristics of supramolecular imprinting template of herbs distributed to liver meridian, in order to provide scientific basis for traditional Chinese medicines(TCMs) distributed to liver meridian. In this paper, with "12th five-year plan" national planning textbooks Science of Traditional Chinese Medicine and Chemistry of Traditional Chinese Medicine as the blueprint, literatures and TCMSP sub-databases in TCM pharmacology of northwest science and technology university of agriculture and forestry were retrieved to collect and summarize active constituents of TCM distributed to liver meridian, and calculate the molecular connectivity index. The average molecular connectivity index of ingredients distributed to liver meridian was 9.47, which was close to flavonoid glycosides' (9.17±2.11) and terpenes (9.30±3.62). Therefore, it is inferred that template molecule of liver meridian is similar to physicochemical property of flavonoid glycosides and terpenes, which could be best matched with imprinting template of liver meridian.

A QSAR Study Based on SVM for the Compound of Hydroxyl Benzoic Esters.

Hydroxyl benzoic esters are preservative, being widely used in food, medicine, and cosmetics. To explore the relationship between the molecular structure and antibacterial activity of these compounds and predict the compounds with similar structures, Quantitative Structure-Activity Relationship (QSAR) models of 25 kinds of hydroxyl benzoic esters with the quantum chemical parameters and molecular connectivity indexes are built based on support vector machine (SVM) by using R language. The External Standard Deviation Error of Prediction (SDEPext), fitting correlation coefficient (R2), and leave-one-out cross-validation (Q2LOO) are used to value the reliability, stability, and predictive ability of models. The results show that R2 and Q2LOO of 4 kinds of nonlinear models are more than 0.6 and SDEPext is 0.213, 0.222, 0.189, and 0.218, respectively. Compared with the multiple linear regression (MLR) model (R2 = 0.421, RSD = 0.260), the correlation coefficient and the standard deviation are both better than MLR. The reliability, stability, robustness, and external predictive ability of models are good, particularly of the model of linear kernel function and eps-regression type. This model can predict the antimicrobial activity of the compounds with similar structure in the applicability domain.

Molecular connectivity indices for modeling the critical micelle concentration of cationic (chloride) Gemini surfactants

The molecular connectivity indices were used to derive the simple model relating the critical micelle concentration of cationic (chloride) gemini surfactants to their structure. One index was selected as the best to describe the effect of the structure of investigated compounds on critical micelle concentration consistent with the experimental results. This index encodes the information about molecular size, the branches, and also the information about heteroatoms. The selected model can be helpful in designing novel chloride gemini surfactants.

New models for correlating and predicting the solubility of some compounds in supercritical CO2

Two new semi-empirical models were proposed to calculate and predict the solubility data of some compounds in supercritical carbon dioxide (SCCO2). The new model I was constructed based on the models of Chrastil. Its ability of calculating solubility data was evaluated and compared with the models of Chrastil, Adachi-Lu and de Valle using solubility data of 40 compounds collected from literature published in recent years, and results showed that the new model I is better than other models. However, the new model I as well as other models mentioned above can only be fitted for each solute without the ability of prediction for the unknown solubility data. Meanwhile, the molecular connectivity indices (MCIs) have been widely used as the structure descriptors encoding a large amount of structure information on an entire molecule. Therefore, the new model II was developed by combining the modified MCIs with the new model I to calculate the solubility data of fatty acids, fatty alcohols, fatty acid esters and aromatic compounds in SCCO2. The relation between the solutes' solubility data and their molecular structures was developed by a one-off correlation of experimental data and then the inductive relation was used in the new model II to predict the solubility data of homogeneous solutes successfully.

On the Spacer Group Effect on Critical Micelle Concentration of Cationic Gemini Surfactants Using Molecular Connectivity Indices.

The important factor which differentiates gemini surfactants from conventional monomeric surfactants is the spacer group. The molecular connectivity method was used to study the effect of the spacer group on critical micelle concentration of cationic gemini surfactants. Two models were derived employing only Kier and Hall molecular connectivity indices. The relationships were developed for a set of 17 gemini surfactants with various spacer groups only. These models can be used to design the structure of the spacer group and in consequence novel cationic gemini surfactants more active in micelle formation.

Solubilization characteristics of licorice based on supramolecular “imprinted template” theory

To investigate the effect of the ingredient group of traditional Chinese medicine (TCM) with different "imprinted template" on the supramolecular solubilization ability of licorice, in order to lay a theoretical foundation for explaining the solubilization phenomenon of the components of TCM. Based on the independent supramolecular "imprinted template" rules, molecular connectivity index (MCI) and the correlation of n-octanol-water partition coefficient (logP) were used to indicate hydrophilic lipophilic capacity of TCM, and the extractum rate was used to indicate the solubilization effect of licoriceon single TCM herbs or compounds. The solubilization ability of licorice was evaluated based on MCI, logP and the extractum rate. According to the results, the correlation coefficient between MCI and logP for single herbs was 0.942, and that for single herb adding licorice was 0.916. The extractum rate of most herbs was increased after adding licorice. The correlation coefficient among the extractum rate as well as MCI and logP change values before and after adding licorice were respectively 0.837, 0.405. The correlation coefficient between MCI and logP for eight compounds was 0.937. Meanwhile, licorice had a solubilization effect on the remaining 7 compound except for Huangqi decoction. Therefore, licorice shows the solubilization effect through the independent supramolecular "imprinted template", so as to improve the hydrophilic lipophilic ability. There was a high positive correlation between the MCI and logP in ingredients for TCM, which could be used as important parameters to indicate the "imprinted template" feature for components of TCM. The study on the solubilizing effect of TCM with the supramolecular "imprinted template" theory was feasible, and will lay a foundation for the reform of single-herb dosage form.

Establishing quantitative structure tribo-ability relationship model using Bayesian regularization neural network

Abstract Quantitative structure-activity relationship methods are used to study the quantitative structure triboability relationship (QSTR), which refers to the tribology capability of a compound from the calculation of structure descriptors. Here, we used the Bayesian regularization neural network (BRNN) to establish a QSTR prediction model. Two-dimensional (2D) BRNN–QSTR models can flexibly and easily estimate lubricant-additive antiwear properties. Our results show that electron transfer and heteroatoms (such as S, P, O, and N) in a lubricant-additive molecule improve the antiwear ability. We also found that molecular connectivity indices are good descriptors of 2D BRNN–QSTR models.

QSAR Study on Imidazole Derivatives as Corrosion Inhibitors by Genetic Function Approximation Method

Quantitative structure and activity relationship (QSAR) method is becoming more desirable for predicting of corrosion inhibition properties. The inhibition efficiency of organic compounds is dependent on many basic molecular descriptors, including structural descriptors, thermodynamic descriptors, information content descriptors, topological descriptors as Wiener index, Zagreb index and molecular connectivity indices. A genetic function approximation approach was used to run the regression analysis and establish correlations between different types of descriptors and measured corrosion inhibition efficiency for imidazole derivatives. A QSAR equation was developed and used to predict the corrosion inhibition efficiency for 18 imidazole derivatives. The prediction of corrosion efficiencies of these compounds nicely matched the experimental measurements.

Simple graph-theoretical model for flavonoid binding to P-glycoprotein.

Three sets of flavonoid derivatives (N=32, 40, and 74) and logarithms of their dissociation constants (log Kd) that describe flavonoid affinity toward P-glycoprotein were modelled using six connectivity indices. The best results were obtained with the zero-order valence molecular connectivity index (0χv) for all three sets. Standard errors of the calibration models were around 0.3, and of the constants from the test sets even a little lower, 0.22 and 0.24. Despite using only one descriptor, our model proved better in internal (cross-validation) and especially in external (test set) statistics than much more demanding methods used in previous 3D QSAR modelling.

Prediction of Stability Constants of Zinc(II) Complexes with 2-aminobenzamide and Amino Acids.

We developed a model for the stability (log β(ZnLB)) of Zn(2+) mixed complexes (N = 16) with 2-aminobenzamide (L) and four amino acids (B) glycine, alanine, valine, and phenylalanine at 300, 310, 320, and 330 K. The model was based on the quadratic regression function of the molecular valence connectivity index of the third order, (3)χ(v), yielded S.E. = 0.02. We also developed an overall model for K(1), K(2) and β(ZnLB) of the same system at all of the four temperatures (N= 48). This model yielded S.E. = 0.05.

Performance evaluation of a novel CO2 absorbent: Dimethyl carbonate

Vapor–liquid equilibrium (VLE) data for the binary carbon dioxide (CO2)+dimethyl carbonate (DMC) systems at 283.15, 293.15, 303.15 and 308.15K up to 4.67MPa are reported from pseudo on-line chromatography with liquid phase sampling experiments. These novel experimental results are discussed and compared with available literature data. The measured VLE data for the CO2-DMC system are then modeled using the Prausnitz–Shair activity coefficient method, molecular connectivity index and the Peng–Robinson (PR) equation of state. To comprehensively evaluate DMC's ability to capture CO2, a continuous absorption and desorption experimental apparatus was designed. A range of operating conditions that can influence the CO2-DMC absorption and desorption processes are investigated, including liquid–gas ratio, absorption temperature, desorption temperature and N2 flow. Finally, this paper compares established CO2 capture absorbents with DMC using AspenPlus2006 process modeling and finds that DMC is a potential absorbent and has prospects for future applications.