Quantitative structure-chemical property applications

Rogers D and A J Hopfinger 1994. Application of Genetic Function Approximation to Quantitatir Structure-Activity Relationships and Quantitative Structure-Property Relationships. Journal Chemical Information and Computer Science 34 854-866. 

Applications of neural networks are becoming more diverse in chemistry [31-40]. Some typical applications include predicting chemical reactivity, acid strength in oxides, protein structure determination, quantitative structure property relationship (QSPR), fluid property relationships, classification of molecular spectra, group contribution, spectroscopy analysis, etc. The results reported in these areas are very encouraging and are demonstrative of the wide spectrum of applications and interest in this area. 

In a study by Andersson et al. [30], the possibilities to use quantitative structure-activity relationship (QSAR) models to predict physical chemical and ecotoxico-logical properties of approximately 200 different plastic additives have been assessed. Physical chemical properties were predicted with the U.S. Environmental Protection Agency Estimation Program Interface (EPI) Suite, Version 3.20. Aquatic ecotoxicity data were calculated by QSAR models in the Toxicity Estimation Software Tool (T.E.S.T.), version 3.3, from U.S. Environmental Protection Agency, as described by Rahmberg et al. [31]. To evaluate the applicability of the QSAR-based characterization factors, they were compared to experiment-based characterization factors for the same substances taken from the USEtox organics database [32], This was done for 39 plastic additives for which experiment-based characterization factors were already available. 

In this chapter, we will give a brief introduction to the basic concepts of chemoinformatics and their relevance to chemical library design. In Section 2, we will describe chemical representation, molecular data, and molecular data mining in computer we will introduce some of the chemoinformatics concepts such as molecular descriptors, chemical space, dimension reduction, similarity and diversity and we will review the most useful methods and applications of chemoinformatics, the quantitative structure-activity relationship (QSAR), the quantitative structure-property relationship (QSPR), multiobjective optimization, and virtual screening. In Section 3, we will outline some of the elements of library design and connect chemoinformatics tools, such as molecular similarity, molecular diversity, and multiple objective optimizations, with designing optimal libraries. Finally, we will put library design into perspective in Section 4. 

Quantitative Structure-Activity Relationship Design. Increasing economic pressures toward more, better, and cheaper pesticides have led to ihe development and application of the Quantitative Structure-Activity Relationship IQSARl paradigm and related experimental design principles for pesticides. Theoretically, quantitative delenninulion of the relationships between chemical structure and hiological and environmental properties of... 

In principle, quantum-chemical theory should be able to provide precise quantitative descriptions of molecular structures and their chemical properties however, due to mathematical and computational complexities this seems unlikely to be realized in the foreseeable future. Thus, researchers need to rely on approximate methods that have now become routine and have found wide applications. In many cases, errors due to the approximate nature of quantum-chemical calculations and the neglect of the solvation effects are largely transferable within structurally related series (Karelson and Lobanov, 1996). Thus, relative values of calculated descriptors can be meaningful even though their absolute values are not directly applicable. 

It should be possible to determine the hazardous properties of a substance from its molecular structure. The properties of pharmaceuticals are almost always first predicted using computational techniques such as Quantitative Structure-Activity Relationships9 (QSAR) before further product development [39]. Most industrial chemicals have been produced before these in-silico tools were available or readily accessible10. Of course, our current knowledge and understanding of science, let alone that of a risk assessor, also limits the application of such methods. 

Other Examples of the Use of Principal Properties Characterization by principal properties has been reported for classes of compounds in applications other than organic synthesis Aminoacids, where principal properties have been used for quantitative structure-activity relations (QSAR) of peptides [64], Environmentally hazardous chemicals, for toxicity studies on homogeneous subgroups [65]. Eluents for chromatography, where principal properties of solvent mixtures have been used for optimization of chromatographic separations in HPLC and TLC [66],... 

The impressive success of the Hammett equation in correlating literally hundreds of observed properties (17) (e.g., rate and equilibrium constants, spectroscopic properties, etc.) may be attributable to the multitude of interaction mechanisms that is implicitly embedded in the values of a. The validity of the separability and additivity axioms used in the derivation of extra-thermodynamic relationships is confirmed by the ability to separate experimentally multiple interaction mechanisms (e.g., inductive and resonance (19, 20, 21), polar and steric (10), enthalpic and entropic (22)). This separation fostered significant progress in the application of quantitative structure-activity relationships to the study of chemical mechanisms. For these relationships can now be expressed in terms of more basic properties of the molecules under study. 

In the last decades methods have been developed to describe quantitative structure-activity relationships and quantitative structure-property relationships, which deal with the modeling of relationships between structural and chemical or biological properties. The similarity of two compounds concerning their biological activity is one of the central tasks in the development of pharmaceutical products. A typical application is the retrieval of structures with defined biological activity from a database. Biological activity is of special interest in the development of drugs. 

Chen, J., Peijnenburg, W.J.G.M., Quan, X., Zhao, Y, Xue, D. and Yang, F. (1998a) The application of quantum chemical and statistical technique in developing quantitative structure-property relationships for the photohydrolysis quantum yields of substituted aromatic halides. Chemosphere, 37, 1169-1186. 

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