From inhibitors to activators: rethinking drug action

Most small molecule drugs are designed to inhibit their target protein from carrying out its cellular function.  Drug discovery typically focuses on disrupting biochemical systems in cells in order to induce apoptosis (cell death) or reduce the activity of an overactive pathway.

Interestingly, it is becoming apparent that there may be a novel way of looking at the problem.  Instead of trying to muck up a cell’s function, new therapeutic approaches may seek to enhance the functioning of healthy biochemical pathways or systems that are under-activated owing to genetic mutation.

One example comes from the search for effective small molecule drugs against Parkinson’s disease (PD).  Several studies have recently shown that malfunctioning lysosomes are involved in the progression of PD by failing to clear waste and allowing the accumulation of misfolded proteins.   The lysosomal function is reduced in PD patients owing to mutations in a protein critical for proper functioning called PARK9.

Researchers are now looking for molecules that can stimulate the lysosomal autophagy pathway by interacting with PARK9 or other proteins.  By increasing the abnormally lowered activity of the pathway, it is hoped that increased clearance of PD-related plaques may be achieved.

Interestingly, a compound from traditional Chinese medicine (TCM) has been found to be activating towards autophagic activity and is now in development in the biotech industry.

More information can be found here:

http://www.alzforum.org/new/detail.asp?id=3172

Using R to create a dotplot with jittered x values

If you need to create a plot where you have a several groups of data that you want to distribute along the ‘y’ axis, but bin into one of several categories in x then you can do the following:

1) create a .csv file with your data in columns (you can use headers)

2) import the .csv file into R with: TEST <- read.table(“yourfile.csv”, sep=’,’, header=TRUE)

3) do the dotplot: dotplot(values ~ ind, data=stack(TEST), jitter.x=TRUE)

The important point here is the use of the “stack” function.  This converts vectors into factors; it also lets you create the type of dotplot where the data is plotted along ‘y’ while having the same ‘x’ value.

Saving current shims for an automation run

Here is an important tip if you are setting up an automation run using Bruker’s ICON-NMR software.  Before the run, lock and shim on your first sample.  Once you have a very good shim, write your shim settings (‘wsh’) to a new shimset called “automation.”  If you specify the “automation” shimset in the gradshim menu as the one to be used by ICON,  it will use this shimset as a starting point for automated shimming before each sample rather than a default shim.