This free-wheeling discussion between Science Alert’s Fiona McDonald and Vic Arcus (University of Waikato) and Greg Cook (University of Otago), with questions from the on-line audience, might give readers some a feel for the time and some of the factors involved in tackling a drug targeting effort, in this case for tuberculosis. It also offers an introduction to something that has always been important to me, from a different angle that I am interested in.
Tuberculosis is a common infection — it’s only second to HIV/AIDS as causing the greatest number of deaths by a single infectious agent. It mostly affects young adults and is “among the top three causes of death for women aged 15 to 44”, resulting in “about 10 million orphan children as a result of TB deaths among parents” a year if we use the 2010 figures as representative, according to the WHO fact sheet summary.
[embed width=”640″ height=”390″]http://www.youtube.com/watch?v=Rw1Zit3I5_4[/embed]
[If you’re not seeing the video, you can view it here.**]
One of the reasons I’d like to host this interview, besides that it features some New Zealand science, is that Vic talks about biophysics. He’s interested in it from the behaviour of proteins and systems. I have related interests but focused on genomes, which are physical structures too, structures that are altered reflecting on what genes are used in each particular type of cell and some diseases.
Biophysics is something uncomfortable for many laboratory biologists to approach;tThe maths and theory are quite different to what most biologists cover.
However physics has a great strength. It can be predictive, in the ‘true’ sense of a model predicting an outcome. (One of my—far too many!—pet gripes is people thinking that computational biology can’t predict anything. While a lot of things are challenging, it’s not some general truth. In fact, some things are done surprisingly well.)
Biology is awfully complex, however. As a result, it’s usual to simplify things and in simplifying you lose a lot of confidence in how well the model represents what really happens in the cell.
But if you pick particular systems carefully and treat them well you can do useful things.
Like Vic I’ve long held the hope there will increasingly be a space for more quantitative biology, looking at the physical ‘really how it is’ using (simple) physical models. Like many I’ve looked at proteins using computational approaches as a Ph.D. student. My interests today are how similar thinking might be applied to genomes to understand how they work and how we might understand and, perhaps, diagnose complex diseases through better understand genomes in their natural setting, as it were.*
Fellow sciblogger Siouxsie Wiles has written about Tb earlier, including an infographic of the basic facts.
Comments to and questions about the interview can be found on the YouTube channel below the video. (The first few pages of comments have a lot of repeated comments, just skip these.)
* I’m—slowly!—trying to gear up an ‘irregular’ theme on genomes, the things around them that make them work and current issues like personal genomics, clinical diagnosis, legal aspects and so on. More on this in a later post.
** I’ve manually edited this post to use ‘embed’ rather than ‘youtube’ to embed the video to try force it to show it, as it wasn’t earlier.
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