Antioxidants are substances that protect cells from the damaging effects of oxygen radicals, which are chemicals that play a part in some diseases such as cancer and others. Antioxidants are expected to be promising drugs in the management of these diseases by removing oxidative stress. Most of the modeling approaches involved in designing new antioxidants is based on Quantitative Structure-Activity Relationship (QSAR). A number of QSAR studies have been conducted to elucidate the structural requirements of antioxidants for their activities in order to predict the potency of these compounds with regard to the targeted activity and to direct the synthesis of more potent analogues. The main focus of this chapter is on the QSAR modeling of antioxidant compounds. The authors provide different QSAR studies of antioxidant compounds and try to compare between them in terms of the best models obtained and their use in designing potential new drugs.
TopIntroduction
Generally, antioxidants are defined as molecules, which are capable of slowing down the oxidation mechanism of an oxidizable compound. At the same time, oxidation represents an essential part of aerobic life and our metabolism, since oxygen is the ultimate electron acceptor. Antioxidants play a significant role in cell protection against oxidative stress. Because of the ability of antioxidants, scientific evidence suggests that these molecules reduce the risk of chronic diseases including cancer and heart disease. Primary sources of naturally occurring antioxidants are whole grains, fruits, vegetables etc.
Therefore, much attention has been devoted recently to research into the role of plant-derived antioxidants in food and human health. The beneficial influence of many foodstuffs and beverages including fruits, vegetables, tea, coffee, and cacao on human health has been recently recognized to originate from their antioxidant activity.
In spite of the fact that there are many experimental techniques used to determine antioxidant activity of a given molecule, such techniques are not only time consuming but also costly. Alternatively, using Quantitative Structure-Activity Relationship method, one can screen a large number of compounds and check for their potency as an antioxidant. For this purpose, the most common methods used in vitro determination of antioxidant activity are reviewed and presented.
This chapter deals with Quantitative Structure-Activity Relationship (QSAR) of antioxidants. At first, the definition of an antioxidant is given including it’s mechanism of action and methods of antioxidant determination. The issue of computer aided drug design is then discussed, focusing on the quantitative structure activity relationship (QSAR). The QSAR section starts with history and the earliest efforts made in this field, types of descriptors, statistical analysis methods from a simple linear regression such as Multiple Linear Regression (MLR) to biased regression based on Principal Component Analysis (PCA), such as Partial Least Squares (PLS) to nonlinear techniques such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). Moreover, a part of this chapter is devoted to the validation of QSAR models, explaining the internal and external validations. At the end, different QSAR studies of the antioxidant compounds are discussed. These QSAR models were built on different types of compounds such as Flavonoids, Hydroxyphenylureas, curcumin analogues, Hydroxybenzalacetones, Phenolic derivatives bearing NO donor groups and Coumarin derivatives. Finally, it was concluded that more attention should go to the building of QSAR models for antioxidant activities in order to design more efficient drugs with potential antioxidant activity.