Chemo Informatics QSAR Analysis of Nitroaromatic Compounds Toxicity

The use of information technology and management has become a critical part of the drug discovery process. The rational design of new drug molecules involves input from various branches of science. In this context the information and management of bio and chemical information have become the integral part. In addition, it is of utmost importance to enrich potential libraries with those molecules which could be converted to suitable drug candidates or omited as toxins. During the practice of chemoinformatics, it has been realized that molecular diversity is an essential feature to characterize the reactivity of the molecules. In addition, a paradigm shift in structureactivity relationship has resulted in the integration of various descriptors and quantum chemical descriptors based drug development activities into early stages of lead discovery. In particular, various descriptors are being developed and used to help identify and screen out compounds that are unlikely to become drugs/toxins. This paper highlights the development of recent DFT based chemical reactivity descriptors and the application of these descriptors towards the prediction of chemical reactivity, especially in the prediction of toxicity and biological activities of nitroaromatic compounds. I.INTRODUCTION The data base development, management and analysis of biological information are defined as bioinformatics which includes various database management tools, analysis tools and molecular modeling. The term “chemoinformatics” has been introduced in the Annual Reports of Medicinal Chemistry in 1998 by Brown. Chemoinformatics is the amalgamation of those chemical information resources to transform data into vital information and chemical information into knowledge for the intended purpose of making better decisions faster in the area of drug lead identification and organization. In fact, both bioinformatics and chemoinformatics are generic terms that encompass the design, creation, organization, management, retrieval, analysis, dissemination, visualization and use of chemical and biological information. Chemi-informatics, chemometrics, computational chemistry, chemical informatics, and chemical information management/science are some of the related areas of chemoinformatics. The development of future chemical informatics systems will require a workforce with a solid grounding in chemistry and an expert understanding of the available computer technology. Chemical, agrochemical, pharmaceutical, and biotechnology branches of science require extensive input from both bioinformatics and chemoinformatics. The quantitative structureactivity relationship (QSAR) and the quantitative structureproperty relationship (QSPR) are the important tools of the bio-chemo-informatics which can be built essentially based on the data generated from the molecular modeling and computational chemistry. The QSAR and QSPR attempt to find a mathematical relationship between chemical structure and biological activity or chemical property for a series of homologous compounds. These series of homologous compounds are called the training set. The generated mathematical equation can be used to predict the activity or property of any new compound, which has been built from the chosen training set. Numerous descriptors have been used to develop QSAR and QSPR for different applications. In this regard it is necessary to mention the noteworthy contribution made by Hansch and coworkers to the development and growth of this area of activity. Nitroaromatic compounds are important materials or intermediates of explosives, pesticides, organic synthesis, and dyestuffs etc. With the development of industry, thousands of these compounds have being introduced into the environment every year and QSAR analysis on the toxicity of these compounds can provide us with valuable information. Hence, in the present investigation experimental toxicity values of 18 nitroaromatics to the algae (Scenedesmus obliguus) have been probed with DFT based descriptors. The DFT offers a strong foundation for various qualitative concepts in the chemical reactivity. 7 Popular qualitative chemical concepts such as electronegativity and hardness have been widely used in understanding various aspects of chemical reactivity. Recently, Geerlings and co workers have reviewed the tremendous development in the application of conceptual density functional theory to variety of chemical and biological problems. Although conceptual density functional theory has been used in numerous investigations to probe the chemical reactivity and site selectivity, their applications in the area of structureactivity relationship aspects of biochemoinformatics are limited. Some of the important contributions in this area are highlighted in the following section. Based on the success of these DFT descriptors as revealed in the previous studies 8, 9 and also due to their simple calculation procedure, the usefulness of the DFT descriptors in the QSAR parlance has been probed in detail.