URL of their paper in PLoS ONE: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjourna...
Great to see PLoS ONE getting awesome papers! Here's to opening of academia.
ORNL invention unravels mystery of protein folding
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Re: ORNL invention unravels mystery of protein folding
#12Why is there a patent on an algorithm that was developed using tax-payer money? Or maybe more importantly, why is it "available for licensing". Technically, I already own a small portion of the technique!
The Bayh-Dole Act is the reason that this can happen when the research is federally funded (in the US).
For sure - this horrible act is poison to progress in the sciences, and I believe has shown to be part of why medicine & med devices are so expensive.
Re: ORNL invention unravels mystery of protein folding
#13talk about deceptive titles.
i know this much: protein folding is to many the holy grail of biotech. because most(?) of the most successful biologics have been large proteins. because protein folding is so obscure, manufacturing large, complex proteins is non-trivial, difficult to scale up and to troubleshoot. (using computer buzzwords since this is hn.) there are a limited number of facilities in the world that can do it right. a delicate process to say the least.
a more accurate headline might be: patent granted to ornl for work on protein folding.
Re: ORNL invention unravels mystery of protein folding
#14Short URL to the patent at USPTO: http://1.usa.gov/plfTg3 I am not a specialist in protein folding, so take it with a grain of salt, but from the figures it does not look like method predicts actual configurations decoded from experiments. Patent itself acknowledges that (5.50): "the lack of computational prediction [...] can be attributed to problems arising form calculating molecular mechanics potentials (force-fie…
This paper is describing a way of analysing the output of molecular dynamics simulations of proteins, a series of 'snapshots' of the positions of the atoms in the protein over time.
Given the number of atoms in the molecule and the short time steps used, it's useful to be able to identify which parts of the protein (and when) in the simulation are doing something interesting and separate those from the random to-ing and fro-ing that you'd expect to occur as thousands of atoms move about. That's what this paper is describing.
It's not being applied to experimental data, and is one of many techniques used to analyse MD trajectories. I'm not an expert in these methods to assess how novel or useful this paper is compared to the others, but I would not expect that it's of interest to a layman.