It's complicated: Hidden protein folding complexity revealed by simple Markov state models

Dec 03, 2012 by Stuart Mason Dambrot feature
The dominant kinetics of BBA at 325 K. Rate timescales are marked on each edge. The NMR structure (PDB: 1fme) is shown in black. Full rate matrices with error estimates are given in SI Text. Copyright © PNAS, doi:10.1073/pnas.1201810109

(Phys.org)—Complex systems often exhibit metastable dynamical behavior – that is, the systems appears to be in an equilibrium state but are actually confined to part of the phase space, while at much longer time scales transition between other such metastable states. (Water provides two well-known examples of metastable dynamical behavior: the delays in both the evaporation of overheated water and the freezing of under-cooled water.) Analysis of this behavior has often focused on stochastic – and more recently, Markov – processes. In particular, Markov State Models (MSMs) have been particularly successful, due largely to their ability to model high-dimensional state spaces, biomolecules, and – again more recently – protein folding kinetics.

Moreover, MSMs have demonstrated quantitative agreement with experimental research. Now, scientists at Stanford University have developed two methods – Flux Robust Perron Cluster Analysis (FPCCA+) and Sliding Constraint Rate Estimation (SCRE) – that allowed them to create accurate rate models from simulations. The researchers then applied these techniques to a series of massive simulation datasets generated by either Anton (a special-purpose supercomputer for molecular dynamics simulation) or Folding@home, a distributed that runs protein folding, computational drug design, and other .

The dominant kinetics of HP35 (A), FiP35 (B), and GTT (C) are summarized as networks. Simulated structures are shown in rainbow. For HP35 (A), experimental structures are shown in black (crystal structure 2f4k) and gray (NMR structure 1vii). For FiP35 (B), experimental structures are shown in black (holo PDB: 1i8g) and gray (apo PDB: 1i6c). For GTT (C), the experimental holo structure is shown in black. Full rate matrices with error estimates are given in SI Text. Copyright © PNAS, doi:10.1073/pnas.1201810109

Professors Vijay S. Pande and Yu-Shan Lin, lead researcher Kyle A. Beauchamp, and researcher Robert McGibbon faxed a range of challenges in designing and executing their study. "The main challenge in developing new analysis methods like Flux Robust Perron Cluster Analysis and Sliding Constraint Rate Estimation was to understand the limitations of the current generation of tools," Pande tells Phys.org. "Once we identified the limitations of our current analysis methods, we could then develop ways to improve upon them," Pande continues. "The challenges of working with large datasets are something that we always keep in mind."

In fact, he adds, the team has developed their MSMBuilder software with such datasets in mind – so applying their methods to simulations from Folding@Home or Anton is generally straightforward. "Moving forward, we hope to develop future methodological advances that further increase our ability to model protein folding. I think we really focus on a two-step process that involves a lot of thinking about both methods and their application to biophysics."

(A). Near-native (gray: 361 K, rainbow: 300 K) conformations are compared for both HP35 datasets. The crystal structure (PDB:2f4k) is shown in black. (B). A 2D RMSD histogram suggests that the 300 K simulations populate both the native and near-native states, with a population ratio of approximately 9∶1. The line x ¼ y was used to separate the N and N’ states. Copyright © PNAS, doi:10.1073/pnas.1201810109

Expanding on how their findings suggest that some beta containing proteins can form long-lived native-like states with small register shifts, Pande notes that the presence of register shifts in multiple systems was a surprising and interesting discovery. "While we knew that such register shifts were possible, it was quite interesting to see them pop up across the whole spectrum of beta proteins in the dataset."

Regarding their view that their results demonstrate that even the simplest protein systems show folding and functional dynamics involving three or more states, Pande points out that their models help reconcile the apparent gap in complexity between protein folding simulation and experiment. "For the systems we studied, we detected multiple states," he notes. "However, we also found that the many-state behavior sometimes involves only small populations."

The scientists also see other areas of research that might benefit from their findings. "In the future," Pande concludes, "we hope similar methods could be used to understand protein dynamics in human disease."

Explore further: Researchers discover new strategy germs use to invade cells

More information: Simple few-state models reveal hidden complexity in protein folding, PNAS, October 30, 2012 vol. 109 no. 44 17807-17813, doi:10.1073/pnas.1201810109

Related Stories

Protein folding made easy

Jun 07, 2011

Protein folding has nothing to do with laundry. It is, in fact, one of the central questions in biochemistry. Protein folding is the continual and universal process whereby the long, coiled strings of amino ...

Software speeds up molecular simulations

Feb 04, 2009

(PhysOrg.com) -- Whether vibrating in place or taking part in protein folding to ensure cells function properly, molecules are never still. Simulating molecular motions provides researchers with information ...

Invention unravels mystery of protein folding

Sep 14, 2011

An Oak Ridge National Laboratory invention able to quickly predict three-dimensional structure of protein could have huge implications for drug discovery and human health.

Keeping an eye on the surroundings

Aug 13, 2008

Water is no passive spectator of biological processes; it is an active participant. Protein folding is thus a self-organized process in which the actions of the solvent play a key role. So far, the emphasis ...

Recommended for you

Researchers discover new strategy germs use to invade cells

Aug 20, 2014

The hospital germ Pseudomonas aeruginosa wraps itself into the membrane of human cells: A team led by Dr. Thorsten Eierhoff and Junior Professor Dr. Winfried Römer from the Institute of Biology II, members of the Cluster ...

Progress in the fight against harmful fungi

Aug 20, 2014

A group of researchers at the Max F. Perutz Laboratories has created one of the three world's largest gene libraries for the Candida glabrata yeast, which is harmful to humans. Molecular analysis of the Candida ...

How steroid hormones enable plants to grow

Aug 19, 2014

Plants can adapt extremely quickly to changes in their environment. Hormones, chemical messengers that are activated in direct response to light and temperature stimuli help them achieve this. Plant steroid ...

Surviving the attack of killer microbes

Aug 19, 2014

The ability to find food and avoid predation dictates whether most organisms live to spread their genes to the next generation or die trying. But for some species of microbe, a unique virus changes the rules ...

Histones and the mystery of cell proliferation

Aug 19, 2014

Before cells divide, they create so much genetic material that it must be wound onto spools before the two new cells can split apart. These spools are actually proteins called histones, and they must multiply ...

User comments : 0