Applications of Topological Indices in the Property/Bioactivity/Toxicity Prediction of Chemicals

Basak, Subhash C.; Mills, Denise; Gute, Brian D.; Grunwald, Gregory D.; Balaban, Alexandrù T.

doi:10.1533/9780857099617.113

Cited by 22 publications

(13 citation statements)

References 103 publications

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“…There are many classification methods for screening of the descriptor pool, such as an HM [1], cluster analysis [18], neural net classification [19], genetic algorithm [20], etc. In the present study, an HM method was used to select the descriptors, and to develop a linear model for the prediction of E 1/2 .…”

Section: Heuristic Methodsmentioning

confidence: 99%

QSPR study for the prediction of half-wave potentials of benzoxazines by heuristic method and radial basis function neural network

et al. 2009

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Abstract:The half-wave potential (E 1/2 ) is an important electrochemical property of organic compounds. In this work, a quantitative structureproperty relationship (QSPR) analysis has been conducted on the half-wave reduction potential (E 1/2 ) of 40 substituted benzoxazines by means of both a heuristic method (HM) and a non-linear radial basis function neural network (RBFNN) modeling method. The statistical parameters provided by the HM model (R 2 =0.946; F=152.576; RMSCV=0.0141) and the RBFNN model (R 2 =0.982; F=1034.171 and RMS =0.0209) indicated satisfactory stability and predictive ability. The obtained models showed that benzoxazines with larger Min valency of a S atom (MVSA), lower Relative number of H atom (RNHA) and Min n-n repulsion for a C-H bond (MnnRCHB) and Minimal Electrophilic Reactivity Index for a C atom (MERICA) can be more easily reduced . This QSPR approach can contribute to a better understanding of structural factors of the organic compounds that contribute to the E 1/2 , and can be useful in predicting the E 1/2 of other compounds. Warsaw and Springer-Verlag Berlin Heidelberg. © Versita

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Section: Heuristic Methodsmentioning

confidence: 99%

QSPR study for the prediction of half-wave potentials of benzoxazines by heuristic method and radial basis function neural network

et al. 2009

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“…Actually, topological indices are real numbers associated with graph of chemical compounds and are useful in quantitative structure-property relationships and quantitative structure-activity relationships. Topological indices predict some important properties of chemical structures even without using lab, for example, boiling point, viscosity, radius of gyration, and so on [1][2][3] can be obtained from the indices.…”

Section: Introductionmentioning

confidence: 99%

Distance-Based Polynomials and Topological Indices for Hierarchical Hypercube Networks

Gao

Ahmed

2021

Journal of Mathematics

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Topological indices are the numbers associated with the graphs of chemical compounds/networks that help us to understand their properties. The aim of this paper is to compute topological indices for the hierarchical hypercube networks. We computed Hosoya polynomials, Harary polynomials, Wiener index, modified Wiener index, hyper-Wiener index, Harary index, generalized Harary index, and multiplicative Wiener index for hierarchical hypercube networks. Our results can help to understand topology of hierarchical hypercube networks and are useful to enhance the ability of these networks. Our results can also be used to solve integral equations.

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“…A purely experimental approach to gain structural insights into how uranyl binds TF can be very challenging because uranyl has a strong tendency to undergo complex chemical speciation under physiological conditions , thus complicating definitive assignments. Although a number of computational approaches such as hierarchical quantitative structure−activity relationship (QSAR) methods have been employed to address chemotoxicity, in general − , thus far, uranyl−protein complexes have not been studied using a quantum mechanical approach, and no experimental structural parameters are available on the structure of the complex. Pible et al have modeled uranyl bound to TF, but this study was carried out using a low-level molecular mechanical approach and thus does not provide information on the quantum molecular properties nor the electronic structure or the IR spectra of the complex.…”

Section: Introductionmentioning

confidence: 99%

Structural Insights into the Binding of Uranyl with Human Serum Protein Apotransferrin Structure and Spectra of Protein−Uranyl Interactions

Benavides-Garcia

Balasubramanian

2009

Chem. Res. Toxicol.

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Ab initio quantum mechanical computational studies for the structure and IR spectra of the uranyl complex with human serum apotransferrin (TF) protein are carried out to model uranyl intake into the human cell through endocytosis and formation of a coordination complex with the protein binding sites. The computed IR spectra and structure of the uranyl-protein complex facilitate interpretation of the observed spectra and confirm the primary binding sites of the transferrin protein with the uranyl ion. Our computed equilibrium geometry and the IR spectra of the uranyl-TF complex reveal that uranyl ion is bound to two tyrosines, one aspartate group, and one carbonate ion. Our IR spectra indicate that histidine is not involved in binding to uranyl with transferrin protein. Our computations reveal a short, strong hydrogen bond, which could play an important role in the stabilization and formation of the uranyl-TF complex. Computed Laplacian charge plots indicate high chemical reactivity on this complex as both an electrophile and a nucleophile, facilitating binding to different receptors and thus entry into a number of target organs and the blood-brain barrier. The Mulliken charge density plots and the three-dimensional charge density plots suggest a donor-acceptor mechanism in the complex formation.

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Applications of Topological Indices in the Property/Bioactivity/Toxicity Prediction of Chemicals

Cited by 22 publications

References 103 publications

QSPR study for the prediction of half-wave potentials of benzoxazines by heuristic method and radial basis function neural network

QSPR study for the prediction of half-wave potentials of benzoxazines by heuristic method and radial basis function neural network

Distance-Based Polynomials and Topological Indices for Hierarchical Hypercube Networks

Structural Insights into the Binding of Uranyl with Human Serum Protein Apotransferrin Structure and Spectra of Protein−Uranyl Interactions

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