Role of Advanced Computing in the Drug Discovery Process

The classical experimental approach to drug discovery is a tedious task for biological scientists as they are time-consuming and expensive. With the advent of advanced computing techniques such as artificial intelligence and high-performance computing, the problems of the traditional drug discovery approach can be circumvented. In particular, computational approaches help in analyzing and locating active binding sites and guide towards the selection of potential drug molecules that can effectively and specifically bind to these sites. Once lead molecules are identified, associated compounds can be chemically synthesized and tested. So the iterative time-consuming process of identifying potential drug molecules can be significantly reduced by implementing advanced computing techniques whereby it controls the spread of pandemic diseases. This chapter gives some of the popular high-performance techniques, automated statistical methods, and neural network algorithms for data mining in the drug discovery process along with their scope and application.