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Freshly Baked Science

Breaking Bad (Design)

3rd October 2018

Computers. They’re everywhere. In our homes, on our commutes, in our hands, and increasingly used in our jobs too. Designing drugs is no different. Gone are the days of hoping to stumble upon a wonder drug (I mean there is still some praying involved, but not as much). For the past 50 years or so, computational chemistry has steadily gained the interest of research groups and pharmaceutical companies looking to speed up their drug discovery process and reduce costs. Many people imagine research chemists as the stereotypical old men with manic hair, running around in lab coats. This is still true in some cases, as I’m sure every chemistry building will have their crazy chemist, but computational simulations are advancing and bringing drug design out of the dark ages and into the 21st Century.

 

As the name suggests, computational chemistry uses computers to aid drug design for diseases or conditions. Drugs are designed to target specific proteins that cause the disease. Biologists identify what effect the target has on the disease and demonstrate how preventing or activating its function can stop the disease. With this knowledge, computational chemists can take a moveable, 3D computer image of the protein and find an area which, if targeted with a well-designed drug, could deactivate or activate the protein, preventing the disease it causes. When the target area of the protein is chosen, the chemists can design a drug that specifically compliments this area, no guessing required.

 

After initial design, the drug is tested for its ability to bind to the target (i.e. the affinity of the drug for the target). Traditionally this would be done in the lab, requiring many chemists, many hours and a lot of chemicals, potentially making useless drugs. Computational chemistry can overcome this too. We can generate this data computationally, eliminating the need for time consuming and expensive production. Computer modelling systems have been developed and are able to ‘fit’ the designed drugs within the protein target site and determine how well the drug interacts with the protein. You can run this for many possible drugs (i.e. a library of compounds) and the system will rank the drugs it has tested in order of best to worst. From this we can determine which of the drugs are more likely to have the desired effect against the target protein.

 

Using computers to aid drug design, along with the ability to predict which drugs are likely to work better than others without the need for lengthy production, speeds up the entire process. A typical research programme can take around 20 years before a drug gets to the market. Computational methods should cut the time it takes to bring a drug through the research phase dramatically. Computational chemistry also allows for more diverse drugs to be created, as more areas can be explored. The future is bright for computational chemistry and includes applications not only in drug

design and personalised medicines, but also in the creation of futuristic technologies such as wearable tech and new screen technology.

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If you enjoyed this article and you want to see more of this writing style, check out the author, Lauren Nelson's, blog here:

https://ashortscientist.wordpress.com/

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