Modern drug design with advancement in QSAR: A review

Abstract

Over the last 20 years, extensive QSAR studies establish an attractive approach to the elucidation of the modern drug chemistry. In the recent years, constant increase in the performance of hardware and software transformed quantitative structure activity relationship (QSAR) and quantitative structure property relationship (QSPR) into powerful and widely used model for the prediction of many biological properties in the field of medicinal chemistry and bioinformatics. The aim of this article is to give an overview of the modern drug chemistry and the importance of various techniques used in the field of drug chemistry such as bioinformatics, QSAR/QSPR, cheminformatics. QSAR is an effective method in the field of medicinal research into rational drug design and mechanism of drug action. The review attempts to account the scenario of drug design and its related research while using different techniques i.e. QSAR. The paper also deals with the brief account of various methodologies in drug design such as, Artificial neural networks, Multiple linear regression analysis, Partial least squares and Principal component analysis. The paper further extends the different dimensions of QSAR viz. 1D, 2D, and 3D and so on. 3D- descriptors have a strong element of the molecular topology and regarded as essential tool and allow chemist to interpret the results in terms of chemical structure and biological manner. Many applications in computational drug design prediction of structure in the development of drugs purely depend on the 3D structure of the drug molecules. The importance and utility of the 3D QSAR discussed in details. Some of the method, which widely used in QSAR, has been discussed in brief.