The last decade has witnessed an exponential growth of sequence information in the field of biological macromolecules such as proteins and nucleic acids and their interactions with other molecules. Computational analyses for structure-function predictions based on such information are increasingly becoming an essential and integral part of modern biology. With rapid advances in the area, there is a growing need to develop efficient versatile bioinformatics software packages, which are hypothesis driven. ?Gene to Drug? is an attempt in this pursuit and an integration of heterologous applications of different technologies developed in-house and their translation into in silico products that cater to a majority of bioinformatics applications. This paper briefly presents the science behind Gene to Drug and how grid services and high performance computing platforms can be harnessed to bridge the gap between biomolecular sequence, structure and function.