- Super microscopes and supercomputers provide snapshot of molecular motors
- Simulations in excess of million atoms required XSEDE resources
- Research lays foundation for developing cancer cures
It sounds like something out of Star Trek: Nano-sized robots self-assemble to form biological machines that do the work of living. And yet this is not science fiction – this really happens.
Every cell in our body has identical DNA, the twisted staircase of nucleic acids uniquely coded to each organism. Molecular machines take pieces of DNA called genes and make a brain cell when needed, instead of, say, a bone cell.
Scientists today are just starting to understand their structure and function using the latest microscopes and supercomputers.
Cryo-electron microscopy (cryo-EM) combined with supercomputer simulations have created the best model yet of a vital molecular machine, the human pre-initiation complex (PIC).
"For the first time, structures have been detailed of the complex groups of molecules that open human DNA," says study co-author Ivaylo Ivanov, associate professor of chemistry at Georgia State University.
Ivanov led the computational work that modeled the atoms of the different proteins that act like cogs of the PIC molecular machine.
The experiment began with images painstakingly taken of PIC. They were made by a group led by study co-author Eva Nogales, senior faculty scientist at Lawrence Berkeley National Laboratory.
Nogales' group used cryo-EM to freeze human PIC bound to DNA before zapping it with electron beams. Thanks to recent advances, cryo-EM can now image at near atomic resolution large and complicated biological structures that have proven too difficult to crystalize.
In all, over 1.4 million cryo-EM 'freeze frames' of PIC were processed using supercomputers at the National Energy Research for Scientific Computing Center (NERSC).
"Cryo-EM is going through a great expansion," Nogales says. "It is allowing us to get higher resolution of more structures in different states so that we can describe several pictures showing how they are moving. We don't see a continuum, but we see snapshots through the process of action."
Using eXtreme Science and Engineering Discovery Environment (XSEDE) resources, scientists next built an accurate model that made physical sense of the density maps of PIC.
To model complex molecular machines, including those for this study, Ivanov's team ran over four million core hours of simulations on the Stampede supercomputer at the Texas Advanced Computing Center (TACC).
The goal of all this computational effort is to produce atomic models that tell the full story of the structure and function of the protein complex of molecules. To get there, Ivanov's team took the twelve components of the PIC assembly and created homology models for each component that accounted for their amino acid sequences and their relation to similar known protein 3-D structures.
XSEDE was "absolutely necessary" for this modeling, says Ivanov. "When we include water and counter ions in addition to the PIC complex in a molecular dynamics simulation box, we get the simulation system size of over a million atoms. For that we need to go to a thousand cores. In this case, we went up to two thousand and forty-eight cores – for that we needed Stampede," Ivanov said.
One of the insights gained in the study is a working model of how PIC opens the otherwise stable DNA double helix for transcription. Imagine a cord made of two threads twisted around each other, Nogales explains. Hold one end very tightly, then grab the other and twist it in the opposite direction of the threading to unravel the cord. That's basically how the living machines that keep us alive do it.
Both scientists said that they are just beginning to get an atomic-level understanding of transcription, crucial to gene expression and ultimately disease.
"Many disease states come about because there are errors in how much a certain gene is being read and how much a certain protein with a certain activity in the cell is present," Nogales says. "Those disease states could be due to excess production of the protein, or conversely not enough. It is very important to understand the molecular process that regulates this production so that we can understand the disease state."
While this fundamental work does not directly produce cures, it does lay the foundation to help develop them in the future, said Ivanov. "In order to understand disease, we have to understand how these complexes function in the first place… A collaboration between computational modelers and experimental structural biologists could be very fruitful in the future. "
The results,"Near-atomic resolution visualization of human transcription promoter opening," were recently published in Nature.
The article was authored by Yuan He, Lawrence Berkeley National Laboratory and now at Northwestern University; Chunli Yan and Ivaylo Ivanov, Georgia State University; Jie Fang, Carla Inouye, Robert Tjian, Eva Nogales, UC Berkeley.
Funding came from the National Institute of General Medical Sciences (NIH) and the National Science Foundation.