Valence Connectivity Research Articles

Target analysis, occurrence and cytotoxicity of halogenated polyhydroxyphenols as emerging disinfection byproducts in drinking water

Halogenated aromatic disinfection byproducts (DBPs) in drinking water, such as halogenated phenols, have received widespread attention due to their high toxicity and ubiquitous occurrence in recent years. This study identified a group of emerging halogenated aromatic DBPs, known as halogenated polyhydroxyphenols (HPPs), and investigated their occurrence and cytotoxicity. We developed a highly sensitive solid-phase extraction ultra-performance liquid chromatography-tandem mass spectrometry (SPE-UPLC-MS/MS) method under multiple reaction monitoring (MRM) mode, with recoveries ranging from 86 to 115% and method detection limits (MDLs) ranging from 0.10 to 1.87 ng/L for the analysis of 15 HPPs. Eleven of these HPP DBPs were detected in collected drinking water samples using this method with detection frequencies ranging from 14 to 100% and a maximum concentration of 24 ng/L. The IC50 of the 15 HPPs in Chinese hamster ovary (CHO-K1) cells were ranged from 15.13 µM to 6.08×103 µM. The tested HPPs with -CHO substitution exhibited higher cytotoxicity compared to those with -COOH substitution. The TIC-Tox values of HPPs were calculated to be higher than those of HPs, indicating a potential necessity to pay attention to HPP DBPs. A quantitative structure−activity relationship (QSAR) model was developed for the cytotoxicity of HPPs, which was shown to be significantly associated with acid dissociation constant (pKa) and total valence connectivity (TVCon). To the best of our knowledge, this study reported the analysis, occurrence, and cytotoxicity of HPP DBPs in drinking water for the first time.

An Interpretable Predictive Model for Health Aspects of Solvents via Rough Set Theory

This paper presents a machine learning (ML) approach to predict the potential health issues of solvents by uncovering the hidden relationship between substances and toxicity. Solvent selection is a crucial step in industrial processes. However, prolonged exposure to solvents has been found to pose significant risks to human health. To mitigate these hazards, it is crucial to develop a predictive model for health performance by identifying the contributing factors to solvent toxicity. This research aims to develop a predictive model for health issues related to solvent toxicity. Among various algorithms in ML, Rough Set Machine Learning (RSML) was chosen for this work due to its interpretable nature of the generated models. The models have been developed through data collection on the toxicity of various organic solvents, the construction of predictive models with decision rules, and model verification. The results reveal correlations between solvent toxicity and the Balaban index, valence connectivity index, Wiener index, and boiling points. The generated predictive model using RSML has successfully provided insightful observations about the correlation between human toxicity and molecular attributes.

2D QSAR STUDY OF FUSED 5,6-BICYCLIC HETEROCYCLES AS ANTI ALZHEIMER’S AGENTS USING TOPOLOGICAL PARAMETERS

Alzheimer’s disease (AD) is a degrading and irreversible neurodegenerative disorder associated with loss of brain functions. It is manifested clinically into psychological symptoms that collectively form cognitive dysfunction and the loss of thinking skills through the progressive degeneration of central nervous system neurons. Over the last decade, γ-secretase emerged as a promising target for the treatment of Alzheimer’s disease. The γ-secretase modulator compounds would be good candidates for AD therapeutics. In previous years, a series fused 5,6-bicyclic heterocycles were investigated as γ-secretase modulators or anti Alzheimer’s agents. In the present study, a quantitative structure activity relationship (QSAR) study of twenty-eight derivatives of fused 5,6-bicyclic heterocycles has been made with the help of topological parameters. The descriptors that have been used are solvent accessible surface area, valence connectivity indices of order 0, 1 and 2 and shape indices of order 1, 2 and 3. The best QSAR model for this set of derivatives has been obtained by using solvent accessible surface area as first descriptor, valence connectivity index (order-0) as second descriptor, valence connectivity index (order-1) as third descriptor and shape index (order-3) as fourth descriptor. The correlation coefficient (r 2 ) and cross validation coefficient (rCV2 ) for this model are 0.773037 and 0.688568, respectively.

CP-MLR/PLS directed quantitative structure-activity relationship study on the histamine H3 receptor binding affinity: The cyclohexylamine based series

The histamine H3 receptor binding affinities of cyclohexylamine derivatives has been analysed with the topological and molecular features from Dragon software. Analysis of the structural features in conjunction with the biological endpoints in combinatorial protocol in multiple linear regression (CP-MLR) led to the identification of 26 descriptors for modelling the activity. The study clearly suggested the role of atomic properties such as mass, electronegativity or charge content, polarizability, atomic van der Waals volume, average valence connectivity index chi-5 and absence of number of acceptor atoms for H-bonds (N, O, F) type functionality to optimise the histamine H3 receptor binding affinity of titled compounds. The models developed and the participating descriptors advocate that the substituent groups of the cylohexylamine moiety hold scope for further modification in the optimization of the H3 receptor binding affinity. Analysis of these descriptors in partial least squares (PLS) highlighted their relative significance in modulating the biological response. The selected descriptors are enriched with information corresponding to the activity when compared to the remaining ones. Applicability domain analysis revealed that the suggested model matches the high quality parameters with good fitting power and the capability of assessing external data and all of the compounds was within the applicability domain of the proposed model and were evaluated correctly.

PM3 Method based QSAR Study of the Derivatives of Thiadiazole and Quinoxaline for Antiepileptic Activity using Topological Descriptors

QSAR study of the derivatives of thiadiazole and quinoxaline has been performed for the antiepileptic activity using the topological descriptors viz., molar refractivity, shape index (basic kappa, order 1), shape index (basic kappa, order 2), shape index (basic kappa, order 3), valence connectivity index (order 0, standard), valence connectivity index (order 1, standard) and valence connectivity index (order 2, standard). In the best QSAR model, the descriptors are molar refractivity, shape index (basic kappa, order 1), shape index (basic kappa, order 3) and valence connectivity index (order 0, standard). In this QSAR model, the regression coefficient is 0.872435 and cross-validation coefficient is 0.832189, which indicate that this QSAR model can be used to predict the antiepileptic activity of any compound belonging to this series. QSAR model developed using single descriptor shape index (basic kappa, order 1) or shape index (basic kappa, order 3) or valence connectivity index (order 2, standard) also has good predictive power.

Quantitative structure-activity relationship study on the MMP-13 inhibitory activity of fused pyrimidine derivatives possessing a 1,2,4-Triazol-3-yl group as a ZBG

QSAR study has been carried out on the MMP-13 inhibitory activity of fused pyrimidine derivatives possessing a1,2,4-triazol-3-yl group as a ZBG in 0D- to 2D-Dragon descriptors. The derived QSAR models have revealed that the number of Sulfur atoms (descriptor nS), Balaban mean square distance index (descriptor MSD), molecular electrotopological variation (descriptor DELS), structural information content index of neighborhood symmetry of 2nd and 3rd order (descriptors SIC2 and SIC3), average valence connectivity index chi-4 (descriptor X4Av) in addition to 1st order Galvez topological charge index (descriptor JGI1) and global topological charge index (descriptor JGT) played a pivotal role in rationalization of MMP-13 inhibition activity of titled compounds. Atomic properties such as mass and volume in terms of atomic properties weighted descriptors MATS5m and MATS3v, and certain atom centred fragments such as CH2RX (descriptor C-006), X--CX--X (descriptor C-044), H attached to heteroatom (descriptor H-050) and H attached to C0(sp3) with 1X attached to next C (descriptor H-052) are also predominant to explain MMP-13 inhibition actions of fused pyrimidines. PLS analysis has also corroborated the dominance of CP-MLR identified descriptors. Applicability domain analysis revealed that the suggested model matches the high-quality parameters with good fitting power and the capability of assessing external data and all of the compounds was within the applicability domain of the proposed model and were evaluated correctly.

Prediction of High Performance Liquid Chromatography Retention Time for Some Organic Compounds Based on Ab initio QSPR Study

Analysis of the quantitative relationship between structure and characteristics of 18 polyaromatic hydrocarbons has been done by quantum Ab initio Quantitative Structure-Property Relationship (QSPR) study at Hartree Fock level of theory. Moment dipole was used as the quantum chemical descriptors, whereas molecular weight and number of rings were applied for constitutional descriptor and the valence connectivity index as steric descriptors. The compound’s electronic structure was studied by molecular modeling and retention time (Tr) data were obtained from the literature. Multi-linear regression analysis has been performed by randomly splitting the initial data set into on fitting data set and a test data set. The best result provided by QSPR analysis is the following model equation:
 log tR = 1.276 + 0.016MW+0.323Rc-0.423χ1-0.147χ2 with n =18 r=0.917 r2 =0.841 SE=0.182 Fcalc/Ftable = 5.408.
 The retention times of PAH compounds with two and three rings were successfully predicted by QSPR models.

Computational chemistry study of toxicity of some m-tolyl acetate derivatives insecticides and molecular design of structurally related products.

Molecular descriptors (including quantum chemical, topological and physicochemical descriptors) were calculated for five m-tolyl derivatives insecticides [namely, carbosulfan (CBS), carbofuran (CBF), isoprocab (IFP), methiocarb (MTC) and isocarbophos (ICP)]. Calculated quantum chemical parameters included the total energy, the electronic energy, the binding energy, the core-core repulsion energy, the heat of formation, the dipole moment and the frontier molecular orbital energies. All the calculated quantum chemical parameters (except dipole moment) exhibited strong correlation with the experimental LD50 values of the studied insecticides (at various Hamiltonians). Calculated topological parameters included the molecular topological index (MTI), polar surface area (PSA), total connectivity (TC), total valence connectivity (TVC), Wiener index (WI), topological diameter (TD) and Balaban index (BI). However, only MTI, PSA, WI and BI exhibited excellent correlation with the toxicological activity of the insecticides. Also among all the calculated physicochemical parameters [logP, surface area (SA), surface volume (SV), hydration energy (EHydr), polarizability (PLZ) and refractivity (RFT)], only SV, EHydr, PLZ and RFT were useful in establishing quantitative structure activity relationship (QSAR). Application of QSAR indicated that the calculated theoretical LD50 values for the studied insecticides displayed excellent correlation with experimentally derived LD50 values. However, best results were obtained from quantum chemical descriptors under modified neglect of atomic overlap (MNDO). The toxicity profile of the insecticides also correlated strongly with ionization energy, electron affinity, global softness and global harness. Reactive sites of each of the insecticides were established using Fukui function, Huckel charges and HOMO/LUMO diagrams. Six new molecules were proposed and their theoretical activities were estimated. The proposed molecules included 2-methyl-2-(methylthio)-2,3-dihydrobenzofuran-7-yl methylcarbamate, O-methyl O-2-((methylaminooxy)carbonyl)phenyl phosphoramidothioate, 2-((methylaminooxy)carbonyl)phenyl methylcarbamate, 2-(1-(methylthio)ethyl)phenyl methylcarbamate, N-methyl-O-(2-(methylthiooxy) benzoyl) hydroxyl amine and 4-methyl naphthalen-2-yl methylcarbamate. Some of the proposed molecules exhibited negative values of LD50 (indicating extreme toxicity) while two of them exhibited values that are comparable to existing insecticides.

In-silico & In-vitro Identification of Structure-Activity Relationship Pattern of Serpentine & Gallic Acid Targeting PI3Kγ as Potential Anticancer Target.

Natural products showed anticancer activity and often induce apoptosis or autophagy in cancer cells through the PI3K/Akt/mTOR signaling pathways. The potential of natural products as PI3Ks inhibitors has been reported, which suggest PI3Ks a promising anticancer target. Phosphoinositide 3-kinase is a family of related intracellular signal transducer enzymes or lipid kinases that regulate different cellular processes involved in cancer. To identify the molecular reason behind the similar target based activity of selected shikimate pathway metabolites on PI3Kγ, a detail structure-activity relationship study was performed. In the studied work, anticancer potential of plant molecules gallic acid and serpentine was evaluated against PI3Kγ isoform and compared with wortmannin, a steroid metabolite of the fungi and a non-specific covalent known inhibitor of PI3Ks by using in-silico QSAR, docking, ADMET, chemical isolation from plant, NMR and in-vitro activity. A predictive QSAR model was developed by applying multiple linear regression which revealed identification of key structural properties regulating the inhibitory activity of serpentine and gallic acid on PI3Kγ. The model exhibited acceptable statistical parameters such as r2 0.76, r2CV 0.72, and q2 0.55. Structural elucidation was done through NMR studies. Predicted activities were further evaluated through in-vitro testing of gallic acid and serpentine targeting PI3Kγ. The identified chemical features modulating the activity were amide, amine, and secondary amine groups counts, highest occupied molecule orbital (HOMO) energy and valence connectivity index (order 2). In-silico ADME and toxicity risk assessment was done for pharmacokinetic and bioavailability compliance evaluation.

Quantitative structural modeling on the wavelength interval (Δλ) in synchronous fluorescence spectroscopy

Emission fluorescence spectroscopy has an extremely restricted scope of application to analyze of complex mixtures since its selectivity is reduced by the extensive spectral overlap. Synchronous fluorescence spectroscopy (SFS) is a technique enables us to analyze complex mixtures with overlapped emission and/or excitation spectra. The difference of excitation and emission wavelength of compounds (interval wavelength or Δλ) is an important characteristic in SFS. Thus a multi-parameter model was constructed to predict Δλ in 63 fluorescent compounds and the regression coefficient in training set, cross validation and test set were 0.88, 0.85 and 0.91 respectively. Furthermore, the applicability and validity of model were evaluated using different statistical methods such as y-scrambling and applicability domain. It was concluded that increasing average valence connectivity, number of Al2-NH functional group and Geary autocorrelation (lag 4) with electronegative weights can lead to increasing Δλ in the fluorescent compounds. The current study obtained an insight into the structural properties of compounds effective on their Δλ as an important parameter in SFS.

Contribution of Modified Harary Index to Predict Kováts Retention Indices for a Set of PAHs

A quantitative structure–retention relationship (QSRR) study was performed to correlate descriptors representing molecular structures to the Kovats retention indices of polycyclic aromatic hydrocarbon compounds. The complete set of 37 compounds was divided randomly into a training set of 26 compounds and a test set of 11 compounds. In the pool of descriptors calculated using Dragon and Hyperchem software, the modified Harary index (\( H^{\prime\prime} \)) developed by our team was added. The best selected descriptors by genetic algorithm to build the three linear models were: the first-order Randic connectivity index (\( {}^{1}\chi \)), \( H^{\prime\prime} \) and the third-order valence connectivity index (\( {}^{3}\chi_{p}^{v} \)). The selected model was compared with the one built with \( {}^{1}\chi \), the first Harary index (implanted in Dragon H) and \( {}^{3}\chi_{p}^{v} \). Statistical analysis showed that the model with modified Harary index (R2 = 99.25, SD 5.82, F = 1517.74) produces better correlation with Kovats retention indices than the one implanted in Dragon (R2 = 98.20, SD 9.02, F = 626.09). The final QSRR was internally and externally validated. The leave-one-out, cross-validation, bootstrapping, and y-randomization test indicated that the final model is robust and has no chance correlation. The external validations indicated that the model with modified Harary index showed a good predictive power. The mechanistic interpretation of QSRR model was carried out according to the definition of descriptors. Therefore, the result meets the five principles recommended by the Organization for Economic Co-operation and Development for validation of QSRR model.

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.

Modelling of copper(II) binding to pentapeptides related to atrial natriuretic factor using the 3χv connectivity index / Modeliranje vezivanja bakra(II) za pentapeptide povezane s atrijalnim natriuretičkim faktorom pomoću indeksa povezanosti 3χv

Abstract Using molecular graph theory we studied the binding of NSFRY-NH2 and 12 related pentapeptide amides to Cu(II) as a model system for atrial natriuretic factor (ANF) peptide interactions with copper. Linear regression models based on the valence connectivity index of the 3rd order (3χv) reproduced experimental stability constants (log β) for 1N, 2N, 3N, and 4N coordinated complexes with the standard error of 0.30-0.39 log β units. We developed separate models for seven tyrosinic (N=28) and five non-tyrosinic peptides (N=20), and a common model for both kinds of peptides (N=48) with an indicator (dummy) variable. The results indicate additional aromatic stabilisation in 4N complexes due to metal cation-π interactions with tyrosine but not with the phenylalanine residue. We have also amended the log K and log K* values to correct miscalculations published by Janicka-Klos et al. in 2013

Wittig reaction (with ethylidene triphenylphosphorane) of oxo-hydroxy derivatives of 5β-cholanic acid: Hydrophobicity, haemolytic potential and capacity of derived ethylidene derivatives for solubilisation of cholesterol

Bile acid salts are biosurfactants which form mixed micelles with phospholipids in vertebrates. These mixed micelles are suitable for solubilisation of cholesterol. For therapeutic purposes some bile acid salts as sodium ursocholate are used. However, bile acid anions possess low capacity for solubilisation of cholesterol. Thus, synthesis of more hydrophobic and less membranotoxic bile acid derivatives is of the great interest. In this paper Wittig reaction between ethylidene triphenylphosphorane and different bile acids oxo derivatives is examined. Wittig reaction of bile acids has not been studied much. C12 oxo group is inert in this reaction. If Wittig reaction happens on C7 oxo group stereospecifically E ethylidene stereoisomer is obtained, while the same reaction on C3 oxo group leads to more reactive not sterospecific product. In this paper stereochemical course of investigated Wittig reactions is thoroughly analysed. Hydrophobicity of derived products is determined over the temperature (T) dependence on retention coefficients (k) in reversed phase high resolution chromatography. Using method of principle components on k=f(T) matrix it is found that values of first principle components best describe hydrophobicity of analysed bile acids, while the second principal component is responsible for their hydrophilicity. By in silico molecular descriptors: valence connectivity index of order 3 (X3v) and packing density index (PDI), linear regression equations are obtained that can be used to predict hydrophobicity (over retention coefficient) of bile acids that belong to set of more congeneric groups. Membranotoxicity is determined by haemolytic potential. Monoethylidene derivatives of bile acids (in the form of anions) have lower membranotoxicity than deoxycholic acids anion. Sodium salt of deoxycholic acid 7-ethylidene derivative has 11% greater capacity for solubilisation of cholesterol monohydrate than sodium salt of deoxycholic acid.

Comparison of Two Methods for the Estimation of Stability of Copper(II) Bis-Complexes with Aromatic Ligands Relevant to Alzheimer’s Disease

In order to compare the density functional theory (DFT) and the method with the molecular valence connectivity index of the 3rd order (3χv) in the estimation of stability constants log β2, we used copper(II) complexes with thioflavin-based intercalation compounds designed for application in Alzheimer's disease. Correlation of ten log β2 values calculated by DFT with 3χv yielded r=0.988 and S.E.=0.85. The correlations of indices I(NG), HOMA and 3χv with log β2, and the intercorrelations between the indices revealed the crucial influence of 3χv on the prediction of the stability of these complexes.

Prediction of standard absolute entropies for gaseous organic compounds

To predict the standard absolute entropies of gaseous organic compounds, the variable molecular connectivity index (mχk″) and Ring parameter (H), based on the adjacency matrix of molecular graphs, the variable atomic valence connectivity index (δi″), and the numbers of chain (cycle) atom of a molecule (niR) were proposed. The δi″, mχk″ and H are defined as: δi″=c·(Ziv−hi)·mi·2.89a/(Zi−Ziv+0.89)a, χkm"=∑j=1nm(∏i=1m+1δi'')j−y, and H=(ln(1.29+0.31niR))2.4. The optimal values of the parameters c, a, mi, and y included in definition of the δi″ and mχk″ can be found by the optimization method. The result shows that the definition of the δi″, for a skeletal atom, expresses both electronic and topological information, and can reflect the different chemical environment of the given atom. A four-parameter model can be constructed from the H and mχk″ by using the best subset regression analysis method and the model could be used to predict the standard absolute entropies of gaseous organic compounds accurately.

A model to estimate stability constants of amino acid chelates with Cu(II) and Ni(II) at different ionic strengths

The equation for the simultaneous prediction of stability constants at various ionic strengths for copper(II) and nickel(II) mono-complexes with α-amino acids was developed. It is based on valence connectivity index of the 3rd order ( 3χ v ) and specific ion interaction theory (SIT). The equation was tested on two sets of data. The first set consisted of 31 log K 1 values for copper(II) complexes with four α-amino acids (glycine, alanine, valine and leucine) measured at I = 0–2 mol dm − 3 . The second set encompassed 24 log K 1 values for nickel(II) complexes with seven α-amino acids (glycine, alanine, valine, leucine, 2-aminobutanoic, 2-aminopentanoic and 2-aminohexanoic acid) measured at I = 0–1 mol dm − 3 . Both sets yielded fair agreement with the experiment, with the standard error of estimate 0.09 and 0.10, for the first and the second set, respectively. Moreover, only two log K 1 values in each set were reproduced with an absolute error > 0.2.

Prediction of peptide IMS cross sections from extended molecular connectivity

It is shown that extended molecular connectivity encoded by the Kier–Hall second order valence connectivity index (2χv) provides an excellent single-parameter correlation with ion mobility spectroscopy (IMS) cross-sections of tripeptides. This second order index is particularly relevant to peptides, because it is calculated over all triatomic chains and thus encodes critical peptide fragments such as Ni–Cα–Ci, Cα–Ci–O, and Cα–Ci–Ni+1. Empirical intrinsic size parameters, reported by previous authors, are now rationalized in terms of extended molecular connectivity.

Estimation of Stability Constants of Copper(II) Complexes with α‐Amino Acids Using Connectivity Index 3χv. Common Model for the Binary and Ternary Complexes

AbstractModels for estimation of the first (K1), second (K2), and overall stability constant (β2) of copper(II) chelates with naturally occurring amino acids, based on the valence connectivity index of the 3rd order (3χv), were improved by introduction of a square term and a new graph representation for mono‐complexes (MLcor). The models gave SE=0.07, 0.05–0.07 and 0.05–0.08 for lg K1, lg K2 and lg β2 constants, respectively; models that encompass both binary and ternary bis‐complexes included indicator variable. We also validated our models on the test set which included two mono‐, two binary and two ternary Cu(II) chelates with α‐aminobutanoic acid and α‐aminopentanoic acid, not included into the calibration. The absolute differences between experimental and predicted stability constants were in the range of 0.01–0.16.

QSPR study of standard absolute entropies for gaseous organic compounds using novel molecular connectivity indexes and Ring parameter

For predicting the standard absolute entropies of gaseous organic compounds, variable molecular connectivity index χ ′ k m and Ring parameter H, based on adjacency matrix of molecular graphs, variable atomic valence connectivity index δ ′ i , and the numbers of chains (cycles) atomic of molecule n i R , were proposed. The optimal values of parameters c, a, m i , and y included in the definition of δ ′ i , and χ ′ k m can be found by optimization method. When c = 0.91, a = 1.3, and y = 0.22, a good four-parameter model can be constructed from H and χ ′ k m by using the best subsets regression analysis method for the standard absolute entropies of gaseous organic compounds. The results show that the MLR method can provide an accurate model for the prediction of the standard absolute entropies of gaseous organic compounds.