Computational Medicine: Is it the Best Bet for Drug Discovery
Computational Medicinewhich has been in existence since 1930 is finally getting its long waited due. Computational Medicine was earlier used to develop aeroplanes, chipsets and even bridges. Today, with large repository of data available in the healthcare sector, computational medicine is being used for drug discovery.
The advent of Computer-aided design (CAD) gave the initial push for the development of drugs by choosing molecules which had the ability to provide biological response. The 90’s era witnessed the introduction of improved software and hardware which could bring the theoretical knowledge into practice. Systems such as Guassian helped researchers to understand the finest of details such as dipole moments, geometrical structure and the energy of molecule. This led to the introduction of computational medicine in drug discovery. However, the concept still failed to succeed because of one major issue; the inability to completely decipher the protein-ligand introduction which still remains the fundamental concept of drug discovery.
The issue of not able to understand the protein-ligand interaction can be largely attributed to the lack of high computational power required. The computer performance required to understand the most basic receptor-ligand interaction is 0.5Gflop. If we are to talk about more complex processes, we are looking at computer performance of 1Tflop. It will require substantial degree of financial muscle to meet such massive requirements.
There is a future consisting of myriad of possibilities. The hope, the hype and the promise made can turn true if these obstacles are overcome. The root problem lies in understanding the protein-ligand interaction and how different modelling concepts can be developed to simplify the process. It’s going to be an arduous task for researchers and pharmaceutical companies which will surely keep the midnight oil burning in the labs.
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