Spectroscopic QSAR Methods and Self-Organizing Molecular Field Analysis for Relating Molecular Structure and Estrogenic Activity

Theoretical study of nitrodibenzofurans: A possible relationship between molecular properties and mutagenic activity

In this study we present a theoretical investigation of the molecular properties of nitrodibenzofurans (NDFs) and dinitrodibenzofurans (DNDFs) and their relation to mutagenic activity. Equilibrium geometries, relative energies, vertical ionization potentials (IP), vertical electron activities (EA), electronic dipole polarizabilities, and dipole moments of all NDFs and three DNDFs calculated by Density Functional Theory (DFT) methods are reported. The Ziegler/Rauk Energy Decomposition Analysis (EDA) is employed for a direct estimate of the variations of the orbital interaction and steric repulsion terms corresponding to the nitro group and the oxygen of the central ring of NDFs. The results indicate differences among NDF isomers for the cleavage of the related bonds and steric effects in the active site. The results show a good linear relationship between polarizability (<α>), anisotropy of polarizability (Δα), the summation of IR intensities (ΣIIR) and the summation of Raman activities (ΣARaman) over all 3N-6 vibrational modes and experimental mutagenic activities of NDF isomers in Salmonella typhimurium TA98 strain. The polarizability changes with respect to the νsNO+CN vibrational mode are in correlation with the mutagenic activities of NDFs and suggest that intermolecular interactions are favoured along this coordinate.

Electronic properties of environmental pollutants and their mutagenic activity: Nitro derivatives of azaphenanthrenes

The physico-chemical properties of nitroazaphenanthrene isomers: 4-nitro-9-azaphenanthrene (4-N-9-Aph), 5-nitro-9-azaphenanthrene (5-N-9-Aph), 6-nitro-4-azaphenanthrene (6-N-4-Aph), 8-nitro-1-azaphenanthrene (8-N-1-Aph), and 8-nitro-4-azaphenanthrene (8-N-4-Aph) have been investigated theoretically using Density Functional Theory (DFT) calculations. Equilibrium geometries, relative stability, ionization potentials, electron affinities, molecular electrostatic potentials, dipole moments, electric polarizabilities, and vibrational properties of these isomers are presented. Averaged O-N-C-C dihedral angle, dipole moment, polarizability, the summation of IR intensities (∑IIR) and the summation of Raman activities (∑ARaman) over all 3N-6 vibrational degrees of freedom are sensitive to the structure of isomers. A very good linear relationship between ∑ARaman values (R=1.00) and the Salmonella typhimurium strain TA98(-S9) mutagenic activity of the investigated nitroazaphenanthrene isomers (Tokiwa et al., 2003) reveals a very important role of inductive and dispersive forces on the mutagenic pathways of the investigated isomers.

Theoretical study of the molecular properties of dimethylanthracenes as properties for the prediction of their biodegradation and mutagenicity

There is little information available on methyl derivatives of anthracene and their interaction with the enzymes of bacterial consortia that could be found in petroleum sludge. In this study a theoretical investigation of all dimethylanthracenes (DMA) isomers and their relation to biodegradation are presented. Equilibrium geometries, ionization potentials (IP), electronic affinities (EA), dipole moments and electronic dipole polarizabilities of DMA isomers calculated by Density Functional Theory (DFT) methods are reported. The calculated IP and EA values vary little along the series of isomers. The polarizability values (〈α〉, Δα, and αyy) increase on passing from meso,meso- and α,meso- to β,β-DMA isomers. The computed polarizability values of DMAs can be used as predictors in determining differences in biodegradation rates of DMAs. The summation over Raman activity ∑ARaman over 3N-6 vibrational modes is sensitive to the position of the methyl substituent. The ∑ARaman values of 1-methylanthracene (MA), 2-MA, 2,9-DMA and 9,10-DMA are consistent with observed mutagenic activities in Salmonella Typhimurium strains TA98 and TA100.

The molecular properties of nitrobenzanthrone isomers and their mutagenic activities

The mutagenic activity of five mono-substituted nitrobenzanthrones (NBA) has been determined in the Ames assay (Takamura-Enya et al., 2006). In the present study, a theoretical investigation of the electronic properties of all mono-substituted NBA isomers and their relation to mutagenic activity are presented. Equilibrium geometries, vertical ionization potentials (VIP), vertical electron affinities (VEA), relative energies, dipole moments and electronic dipole polarizabilities, and the IR and Raman spectra of NBA isomers calculated by Density Functional Theory (DFT) methods are presented. The position of the nitro group affects the spectral features of the IR and Raman spectra of the NBA isomers. The results show that a good linear relationship exists between the summation of Raman activities (∑ARaman) over all the 3N-6 vibrational modes and the mutagenic activity of the NBA isomers in Salmonella typhimurium strains. The spectroscopic results suggest that the unknown mutagenic activities of 4-NBA, 5-NBA, 6-NBA, 8-NBA and 10-NBA are predicted to follow the order 4-NBA>10-NBA>5-NBA>8-NBA>6-NBA.

Prediction of mutagenic activity of nitrophenanthrene and nitroanthracene isomers by simulated IR and Raman spectra

This paper expands upon our original work on nitroanthracenes in (Alparone, A., Librando, V., 2012. Spectrochim. Acta A 89, 129-136) on the series of nitrophenanthrene isomers. Geometries, electric properties, IR and Raman spectra of 1-, 2-, 3-, 4- and 9-nitrophenanthrene (1-NP, 2-NP, 3-NP, 4-NP and 9-NP) were obtained and analyzed using Density Functional Theory calculations. The balance between steric and π-conjugative interactions determines the order of stability 4-NP<1-NP~9-NP<2-NP∼3-NP. IR and Raman spectral zones between 1000 and 1600 cm(-1) show intense bands noticeably affected by the position of the substituent, being potentially useful to discriminate and monitor the investigated isomers. Dipole moments, summations of IR intensity (ΣI(IR)) and Raman activity (ΣA(Raman)) over the 3N-6 vibrational modes are sensitive to the structure, increasing steadily from the non-planar to the planar isomers. Good linear relationships between the ΣI(IR) (r=0.90) and ΣA(Raman) (r=0.99) against the Salmonella typhimurium strain TA98 mutagenic activity of nitrophenanthrenes and isomeric nitroanthracenes are found. On the basis of the structural and vibrational properties, 4-NP seems to have not mutagenic activity, while the unknown TA98 mutagenic potency of 1-nitroanthracene is predicted to be between that of 9-NP and 3-NP. Calculated ΣI(IR) and ΣA(Raman) values could be used as molecular descriptors for QSARs applications of series of isomers.

Discovery of estrogen receptor modulators: a review of virtual screening and SAR efforts

IMPORTANCE OF THE FIELD

Virtual screening (VS) coupled with structural biology is a significantly important approach to increase the number and enhance the success of projects in lead identification stage of drug discovery process. Recent advances and future directions in estrogen therapy have resulted in great demand for identifying the potential estrogen receptor (ER) modulators with more activity and selectivity.

AREAS COVERED IN THIS REVIEW

This review presents the current state of the art in VS and structure-activity relationship of ER modulators in recent discovery, and discusses the strengths and weaknesses of the technology.

WHAT THE READER WILL GAIN

Readers will gain an overview of the current platforms of in silico screening for discovery of ER modulators; they will learn which structural information is significantly correlated with the bioactivity of ER modulators and what novel strategies should be considered for the creation of more effective chemical structures.

TAKE HOME MESSAGE

With the goal of reducing toxicity and/or improving efficacy, challenges to the successful modeling of endocrine agents are proposed, providing new paradigms for the design of ER inhibitors.

QSAR Prediction of Estrogen Activity for a Large Set of Diverse Chemicals under the Guidance of OECD Principles

A large number of environmental chemicals, known as endocrine-disrupting chemicals, are suspected of disrupting endocrine functions by mimicking or antagonizing natural hormones, and such chemicals may pose a serious threat to the health of humans and wildlife. They are thought to act through a variety of mechanisms, mainly estrogen-receptor-mediated mechanisms of toxicity. However, it is practically impossible to perform thorough toxicological tests on all potential xenoestrogens, and thus, the quantitative structure--activity relationship (QSAR) provides a promising method for the estimation of a compound's estrogenic activity. Here, QSAR models of the estrogen receptor binding affinity of a large data set of heterogeneous chemicals have been built using theoretical molecular descriptors, giving full consideration to the new OECD principles in regulation for QSAR acceptability, during model construction and assessment. An unambiguous multiple linear regression (MLR) algorithm was used to build the models, and model predictive ability was validated by both internal and external validation. The applicability domain was checked by the leverage approach to verify prediction reliability. The results obtained using several validation paths indicate that the proposed QSAR model is robust and satisfactory, and can provide a feasible and practical tool for the rapid screening of the estrogen activity of organic compounds.

SAR and QSAR modeling of endocrine disruptors

A number of xenobiotics by mimicking natural hormones can disrupt crucial functions in wildlife and humans. These chemicals termed endocrine disruptors are able to exert adverse effects through a variety of mechanisms. Fortunately, there is a growing interest in the study of these structurally diverse chemicals mainly through research programs based on in vitro and in vivo experimentations but also by means of SAR and QSAR models. The goal of our study was to retrieve from the literature all the papers dealing with structure-activity models on endocrine disruptor xenobiotics. A critical analysis of these models was made focusing our attention on the quality of the biological data, the significance of the molecular descriptors and the validity of the statistical tools used for deriving the models. The predictive power and domain of application of these models were also discussed.

On the Use of 1H and 13C 1D NMR Spectra as QSPR Descriptors

Recently, 1D NMR and IR spectra have been proposed as descriptors containing 3D information. And, as such, said to be suitable for making QSAR and QSPR models where 3D molecular geometries matter, for example, in binding affinities. This paper presents a study on the predictive power of 1D NMR spectra-based QSPR models using simulated proton and carbon 1D NMR spectra. It shows that the spectra-based models are outperformed by models based on theoretical molecular descriptors and that spectra-based models are not easy to interpret. We therefore conclude that the use of such NMR spectra offers no added value.

Improving the performance of SOMFA by use of standard multivariate methods

Self-Organizing Molecular Field Analysis (SOMFA) comes with a built-in regression methodology, the Self-Organizing Regression (SOR), instead of relying on external methods such as PLS. In this article we present a proof of the equivalence between SOR and SIMPLS with one principal component. Thus, the modest performance of SOMFA on complex datasets can be primarily attributed to the low performance of the SOMFA regression methodology. A multi-component extension of the original SOR methodology (MCSOR) is introduced, and the performances of SOR, MCSOR and SIMPLS are compared using several datasets. The results indicate that in general the performance of SOMFA models is greatly improved if SOR is replaced with a more sophisticated regression method. The results obtained for the Cramer (CBG) dataset further underline the fact that it is a very poor benchmark dataset and should not be used to evaluate the performance of QSAR techniques.

Consensus kNN QSAR: a versatile method for predicting the estrogenic activity of organic compounds in silico. A comparative study with five estrogen receptors and a large, diverse set of ligands

Quantitative structure-activity relationships (QSARs) have proved increasingly useful for predicting the biological activities of molecules (e.g., their binding affinities to different receptors) and can be used in environmental chemistry as a preliminary tool for screening the activities of untested molecules, producing valuable information on which compounds should be tested more thoroughly with experimental affinity assays or in animals. The predictive ability of the consensus kNN QSAR method is corroborated here using a diverse set of 245 compounds, which have been assayed for their relative binding affinities to the estrogen receptor of four species: human (ER alpha and ER beta), calf, mouse, and rat. Leave-one-out cross-validation (LOO-CV) and gamma-randomization tests were applied to the QSAR models for internal validation, and separate training and test sets were used for external validation. The internal predictive abilities of the consensus models for all five data sets were convincing, with cross-validated correlation coefficients (LOO-CV q2 values) varying from 0.69 (human ER beta data) to 0.79 (human ER alpha data). The external predictive abilities were also encouraging, as the predictive r2 scores (pr-r2 values) varied from 0.62 (human ER beta data) to 0.77 (calf and mouse data). The results indicate that consensus kNN QSAR is a feasible method for rapid screening of the estrogenic activity of organic compounds.