3D computer model helps explain chemotherapy failure

Electrophoretic separations

3D computer model helps explain chemotherapy failure

21 Jun, 2012

Published over 14 years ago. See the latest and most current information on Electrophoretic separations.

Biochemistry researchers are using a 3D computer model to explain chemotherapy failure.

Researchers from Southern Methodist University are using a 3D computer model of the human protein P-glycoprotein, which is believed to play a fundamental role in chemotherapy failings in recurring cancers. Using the new model they have screened more than eight million potential drug compounds in the hunt for one that will help stop this failure.

They have unveiled a newly identified inhibitor which binds to P-glycoprotein. Biochemist John G. Wise said in a school news release: "This has been a good proof-of-principle.

"We've seen that running the compounds through the computational model is an effective way to rapidly and economically screen massive numbers of compounds to find a small number that can then be tested in the wet lab."

Through a supercomputer search, Mr Wise and his team have already managed to unveil a few hundred 'interesting' compounds, 30 of which have been used for testing in the laboratory.

Of these tests, there have been a handful selected which inhibit P-glycoprotein, which will now go into further testing. Even though the digital screening allowed the team to run over ten million computation hours in the past three years, at a rate of around 40,000 compounds per day, the odds are stacked against researchers trying to find a compound that will work.

"Out of a hundred good inhibitors that we might find, 99 of them might be extremely toxic and can't be used," Mr Wise admits.

"They metabolize too quickly, or they're too toxic, or they're not soluble enough in the acceptable solvents for humans. There are many different reasons why a drug can fail. Finding a handful has been a great confirmation that we're on the right track, but I would be totally amazed if one of the first we've tested was the one we're looking for."

But at such big rates, stumbling upon a needle in a haystack could be that little bit more likely.

Posted by Fiona Griffiths

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