Abstract

A PRACTICAL OVERVIEW OF QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP

Anu Grover*, Dr. Manish Grover and Dr. Komal Sharma

ABSTRACT

Quantitative structure-activity relationship (QSAR) modeling pertains to the construction of predictive models of biological activities as a function of structural and molecular information of drug molecules. A cherished goal of chemists for generations has been to create molecules with specific properties. Finding new drugs, in particular, is an important part of the new initiatives in health care. However, it is an extremely challenging process due to the complexities involved.[1] Traditionally, a combination of serendipity and empiricism has been the basis of new drug discovery. Trial and error synthesis of compounds and their random screening for activity have proved to be both time-consuming and uneconomical. Further, therapeutic effects and hazards to health are assessed using a series of experimental and in-vivo tests. However, usage of animal models is often subject to ethical (and financial) considerations. Therefore, alternative methods have been under development to reduce the requirement of animals in testing.[2] The explosive development of computer technology and methodologies to calculate molecular properties increasingly made it possible to use computer techniques to aid the drug discovery process. This review aims to cover the essential concepts and techniques that are relevant for performing QSAR/QSPR studies through the use of selected examples from previously done work and literature survery.

Keywords: quantitative structure-activity relationship, QSAR, quantitative structure-property relationship, QSPR, Drug research