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Indicator in QSAR

Osmialowski, K. and Kaliszan, R. (1991). Studies of Performance of Graph Theoretical Indices in QSAR Analysis. Quant.Struct.-Act.Relat., 10,125-134. [Pg.625]

The use of topological indices in QSAR studies has been criticized (e.g. [158, 175, 173, 287, 387]). Good QSAR practice is violated in many papers ... [Pg.53]

At the time of going to press, two books are in the pipeline. One deals with reproductive and developmental toxicology while the other one discusses the long history of the topological indices in QSAR and QSPR and shows the new developments in the field. [Pg.11]

Topological Indices and Related Descriptors in QSAR and QSPR J. Devillers, A. T. [Pg.249]

Ivanduc, O., Balahan, A. T. The graph description of chemical structures. In Topological Indices and Related Descriptors in QSAR and QSPR, Devillers,). [Pg.106]

This chapter describes and classifies H-bond descriptors, and indicates possible areas of their application in QSAR studies and drug design. Similar analyses were presented in previous articles [3-5]. [Pg.129]

Devillers, J., Balaban, A. T. Topological indices and Related Descriptors In QSAR and QSPR, Gordon Breach, Amsterdam, 1999. [Pg.405]

In a first attempt to derive characterization factors with QSARs, the entire dataset of plastics additives was included, and aquatic ecotoxicity was predicted for two different trophic levels. This generated characterization factors that did not correspond well with the ones derived from experimental data [30]. Hardly surprising, but a clear indication that two trophic levels are unsufficient. A second attempt to derive characterization factors with QSARs are currently being performed [31]. In this second attempt, substances that are difficult to model in QSAR models have been removed from the dataset and the ecotoxicity has been predicted for three different trophic levels instead of two. However, results have not yet been obtained from this second attempt. If the results show that it is possible to derive reliable characterization factors by the use of QSARs, the current data gap regarding characterization factors for human toxicity and ecotoxicity could be... [Pg.16]

Finizio, A., Di Guardo, A., Vighi, M. (1994) Improved RP-HPLC determination of KqW for some chloroaromatic chemicals using molecular connectivity indices. SAR QSAR in Environ. Res. 2, 249-260. [Pg.51]

Three classes of calculated molecular descriptors, viz., topological and substruc-tural descriptors, geometrical (3-D) indices, and quantum chemical (QC) indices, have been extensively used in QSAR studies pertaining to drug discovery and environmental toxicology [8-12],... [Pg.481]

A review of literature would show that a suite of QC descriptors have also been used in QSARs for biological and toxicological correlations. Such indices have been derived both from semiempirical and ab initio (Hartree Fock and density functional theory) methods. In particular, in our QSAR studies, we have used the following levels of QC indices local and global electrophilicity indices [11],... [Pg.481]

Results in Table 31.3 indicate that the combination of TS and TC descriptors resulted in a highly predictive RR model = 0.895) the addition of three-dimensional and QC indices to the set of independent variables did not result in significant improvement in model quality. It may be noted that we have observed such results for various other physicochemical and biological properties including mutagenicity [25,54], boiling point [55], blood air partition coefficient [37], tissue air partition coefficient [46], etc. [24,30,45,56]. Only in limited cases, e.g., halocarbon toxicity [12], the addition of QC indices after TS and TC parameters resulted in significant improvement in QSAR model quality. [Pg.488]

Basak, S. C., Mills, D., Mumtaz, M. M., Balasubramanian, K. Use of topological indices in predicting aryl hydrocarbon receptor binding potency of dibenzofurans A hierarchical QSAR approach. Indian J. Chem. 2003, 42A, 1385-1391. [Pg.499]

Hall LH, Kier LB (1999) In Devillers J, Balaban AT (eds) Topological indices and related descriptors in QSAR and QSPR. Gordon and Breach, Reading, UK... [Pg.306]

Considerable literature developed around the ability of numerical indices derived from graph theoretical considerations to correlate with S AR data. This was a source of mystery to me for some time. A colleague, loan Motoc, from Romania, with experience in this arena and a very strong intellect, helped me understand the ability of various indices to be useful parameters in QSAR equations [19-21]. loan correlated various indices with more physically relevant (at least to me) variables such as surface area and molecular volume. Since computational time was at a premium during the early days of QSAR and such indices could be calculated with minimal computations, they played a useful role and continue to be used. As a chemist, however, I am much more comfortable with parameters such as surface area or volume. [Pg.6]

The chapter is divided into three sections the first part is concerned with the derivation of 3D-LogP descriptor and the selection of suitable parameters for the computation of the MLP values. This study was performed on a set of rigid molecules in order, at least initially, to avoid the issue of conformation-dependence. In the second part, both the information content and conformational sensitivity of the 3D-LogP description was established using a set of flexible acetylated amino acids and dipeptides. This initial work was carried out using log P as the property to be estimated/predicted. However, it should be made clear that, while the 3D-LogP descriptor can be used for the prediction of log P, this was not the primary intention behind its the development. Rather, as previously indicated, the rationale for this work was the development of a conformationally sensitive but alignment-free lipophilicity descriptor for use in QSAR model development. The use of log P as the property to be estimated/predicted enables one to establish the extent of information loss, if any, in the process used to transform the results of MLP calculations into a descriptor suitable for use in QSAR analyses. [Pg.218]

Some of the earliest QSAR studies on CYPs were performed by Basak (257), Murray (258), and Marshall (205). Gao et al. (259) explored the influence of electronic parameters of CYP substrates in 1996. The findings of Basak that electronic terms would cancel out have been proven wrong by many research papers published in the following decades. Tyrakowska et al. (260) indicated via QSARs based on calculated molecular orbital descriptors that the cat (maximum velocity converted per nmol of P450 per min) for CYP catalyzed C4-hydroxylation rates of aniline derivatives of different species (rats, rabbit, mice, and human) are closely related to the highest occupied molecular orbital energy (EHOMo)> r - 0-97. Several reviews published by Lewis et al. (212,216,228,261-265) and Ekins (240) should also be mentioned. [Pg.488]

The enormous cost of multiple-species, multiple-dose, lifetime evaluations of chronic effects has already made the task of carrying out hazard assessments of all chemicals in commercial use impossible. At the same time, quantitative structure activity relationship (QSAR) studies are not yet predictive enough to indicate which chemicals should be so tested and which chemicals need not be tested. In exposure assessment, continued development of analytical methods will permit ever more sensitive and selective determinations of toxicants in food and the environment, as well as the effects of chemical mixtures and the potential for interactions that affect the ultimate expression of toxicity. Developments in QSARs, in short-term tests based on the expected mechanism of toxic action and simplification of chronic testing procedures, will all be necessary if the chemicals to which the public and the environment are exposed are to be assessed adequately for their potential to cause harm. [Pg.523]

At this point, a considerable amount of theory on Hansch analysis has been presented with almost no examples of practice. The next three Case Studies will hopefully solidify ideas on Hansch analysis that have already been discussed. Each Case Study introduces a different idea. The first is an example of a very simple Hansch equation with a small data set. The second demonstrates the use of squared parameters in Hansch equations. The third and final Case Study shows how indicator variables are used in QSAR studies. If you are unfamiliar with performing linear regressions, be sure to read Appendix B on performing a regression analysis with the LINEST function in almost any common spreadsheet software. A section in the appendix describes in great detail how to derive Equations 12.20 through 12.22 in the first Case Study. [Pg.307]

At the maximum activity of the curve, the derivative equals 0. Solving Equation 12.24 at this point indicates a log P° of —1.20. If additional analogues were to be developed, the discovery team would use this information to include compounds with log P values close to —1.20. John Topliss of the University of Michigan was an early pioneer in QSAR. Topliss felt that the concept of log P° was one of the most important contributions of Hansch analysis to the field of medicinal chemistry.10... [Pg.310]

In summary, the standard series approach failed in these instances to offer indications as to how selectivity might be achieved. On the other hand, it was not necessary to synthesize any new compounds to obtain the required binding data. Furthermore, the investigations cannot be considered as failures that is, the results (1) provided data for the formulation of structure-affinity relationships for each of the two 5-HT receptor subtypes, (2) provided information of the selectivity characteristics of a large number of known tryptamines (e g., they showed that 5-HTQ lacks affinity for these receptors), and (3) afforded data that was used in QSAR studies to better understand what, and how, various structural features of the tryptamines contribute to their binding (or lack thereof) (101,103). [Pg.134]


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See also in sourсe #XX -- [ Pg.55 ]




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