Tuberculosis continues to kill millions of people around the world every year, particularly those with weakened immune systems. Due to the limited number of new drugs developed for this disease in the past several decades, and by necessity the use of a small set of drugs, many strains of tuberculosis are highly resistant to antibiotics.
Particularly worrying is the spread of what is known as extensively drug resistant tuberculosis. This is tuberculosis that is not only resistant to the typical drugs doctors try first to treat the disease, but is also resistant to numerous drugs tried after these initital drugs fail.
Extensively drug resistant tuberculosis is difficult and dangerous to treat, because the only drugs available to treat it are of weak efficacy and are highly toxic. New drugs to treat tuberculosis are needed.
The drug discovery challenge.
The challenge of discovering new anti-tuberculosis drugs is common to drug development in general. The classical approach has been to synthesize new potential drugs, perhaps guided by theoretical and computational predictions, and try them out one by one.
Many potential drugs developed via this approach fail early on in testing, for readily observable reasons, such as a lack of chemical interaction with the intended target. Those that initially succeed often fail in subsequent testing, for reasons such as severe toxicity or undesired chemical interactions with unintended targets.
All of this testing requires much time and resources, and is a reason why it typically costs hundreds of millions of dollars to develop a new successful drug. However, if one were to screen a diverse set of drugs, currently used to treat other diseases, yet with the potential to treat the disease of interest, one could obtain a diverse set of drugs with a new mission.
Since basic pharmacological data has already been obtained for these drugs, the risk of drug failure is reduced. The speed of drug development has thus been increased, and its cost decreased.
This approach has been taken by Lei Xie, Philip Bourne (University of California, San Diego), and coworkers. They have discovered that a drug which is normally utilized in Parkinson's disease treatment shows promise for treating extensively drug resistant tuberculosis.
From Parkinson's disease to tuberculosis.
Levodopa is a molecule that occurs in nature. In the body, this molecule is converted into dopamine, a molecule that aids in nerve cell communication.
The drug molecule entacapone interrups this process by chemically binding to a certain enzyme, known as catechol-O-methyltransferase, preventing the chemical conversion of levodopa into dopamine. The passage of levodopa from the blood into the brain is therefore enhanced, where it can then be converted into dopamine.
Dopamine is unable to cross over from the blood into the brain on its own. Thus, entacapone enables more dopamine to enter the brain via an indirect mechanism.
In this work, the scientists utilized specialized software that implied the drug molecule entacapone can chemically bind to to an enzyme, known as inhibin alpha. This enzyme is found in tuberculosis bacteria, and is the primary target of some common anti-tuberculosis drugs.
Preliminary testing of drug efficacy.
The scientists applied standard cellular inhibition assays to evaluate the efficacy of entacapone against tuberculosis bacteria. They found that growth of the bacteria was inhibited by 99% when somewhere between 62.5 and 125 micrograms per milliliter of drug was added to the cells.
Utilizing standard enzyme inhibition assays, the scientists found that 50% of the activity of the inhibin alpha enzyme is inhibited at 24 micrograms per milliliter of entacapone. This is further evidence that entacapone is likely to be an effective drug against tuberculosis.
Conventional approaches would have overlooked entacapone.
Conventional drug discovery software would have overlooked entacapone as a drug for treating tuberculosis. At first glance, it possesses a very different two-dimensional structure relative to other anti-tuberculosis drugs.
However, there are some similarities. These include molecular size, chemical unit identity, and molecular shape.
Conventional benchtop drug discovery would probably have also overlooked entacapone, because it is not soluble in water. However, this property may help the molecule penetrate into tuberculosis bacteria, because the outer barrier of cells does not generally allow passage of water-soluble molecules.
Overall evaluation.
It should be possible to tinker with the molecular structure of the drug molecule entacapone, in order to increase its efficacy against tuberculosis. Scientists now have a lead molecule on which they can devise new, and possibly more effective, drug molecules against the disease.
They will owe their discoveries to specialized software that picked out a drug, currently used to safely treat Parkinson's disease, which would have been overlooked with conventional drug discovery approaches.
for more information:
Kinnings, S. L., Liu, N., Buchmeier, N., Tonge, P. J., Xie, L., & Bourne, P. E. (2009). Drug Discovery Using Chemical Systems Biology: Repositioning the Safe Medicine Comtan to Treat Multi-Drug and Extensively Drug Resistant Tuberculosis PLoS Computational Biology, 5 (7) DOI: 10.1371/journal.pcbi.1000423