"Knowledge of diverse domains will be relevant"

Supreet Deshpande, CEO, VLife Sciences Technologies, Pune

The term bioinformatics is often used for everything related to computer applications in research. In its broadest yet correct definition, bioinformatics can be termed as IT applications which make such collection, arrangement, interconnection, annotation, search and analysis of these huge datasets relating to biology and relating them with other existing data for scientists to develop newer approaches for drug discovery and other life sciences applications.

During the course of Human Genome Project in the late 90s, which was aimed at deciphering human genes, huge amount of data got created. This data opened up new approaches for research in the areas of genomics and proteomics and scientists all over the world started new experiments, each of which further created more data. Such huge data required automated collection, arrangement and search applications to unlock the information contained therein for designing better drugs and identifying new drug targets. To handle existing data, new IT applications were created. This new branch of science is called bioinformatics.

The IT industry celebrated the birth of bioinformatics since it gave them the most awaited chance to develop faster tools to process the massive data that was created. Leading companies in the world took up the cause of popularizing bioinformatics as they saw large opportunity for their database products and high-end servers. Somewhere in the midst of the jubilant mood of the IT industry, the primary and pragmatic focus of bioinformatics, that is to facilitate the drug discovery, was sidelined.

The IT version of the bioinformatics success story was so powerful that even before any sizable success attributable to this approach could be obtained by researchers, the spending allocated by the big pharma companies into this approach formed a large percentage of their technology budgets. As a result, several companies mushroomed in quick time and this number multiplied quickly as entry barrier was very low. Anyone who could do data-management in IT also, had a bioinformatics division.

However, when the expected contribution of this approach towards new drug discovery was illusive, pressure mounted on bioinformatics companies. Somewhere under this stress, these bioinformatics companies lost the sense of the very purpose of their existence of helping in designing better drugs and ended up into a rut of creating more data from available data, for survival and more complex tools which were not user-friendly. This data deluge and confusion thereof hastened the closure of many companies.

Students need to remember that the serious companies in drug discovery enabling technologies never joined the bioinformatics bandwagon. Those companies instead paid attention to the core purpose of this field of knowledge and aimed at developing technologies that facilitated drug discovery. One such example is computational drug discovery technology. It is based on 3D structural simulation, not data mining as in bioinformatics. It enables a novel discovery approach for medicinal chemists and molecular biologists to pursue drug discovery through direct methods-designing a molecule for a drug target protein or through indirect methods-finding molecules similar to those which are effective through structural and parametric comparisons. It also allows study interactions of proteins and small molecules at a structural level in 3D simulated environment to identify how molecules can be designed for better effectiveness, less side effects. The benefits of the technology are considerably lower cost of early stage research and faster time compared to conventional experimental process. Bioinformatics has ample open opportunities for inquiring minds.

In this knowledge-intensive field, not only the technological expertise but also the knowledge of diverse domains such as biology, pure sciences, mathematics and logic is very relevant. Students who possess this diverse domain expertise along with the technological know-how of bioinformatics tools have great scope in the field. What it means that those who can understand the core focus of the field, that is drug discovery, and have ability to reorient themselves pragmatically have a bright future in the field. Globally, the contribution to drug discovery has not lost its value. Rather students will have a more challenging workplace in this field.

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