The ability of proteins to fold into their native state is essential for cell function; misfolded proteins not only lose their function, but can also cause neurodegenerative diseases, including Alzheimer and Huntington. Study of protein folding can aid in preventing protein misfolding diseases and in designing proteins with novel functions. Although most cellular proteins fold on timescales of milliseconds to seconds, several small proteins have been designed and characterized experimentally to fold on a timescale of less than 20 µs. The project will employ Center-developed long-time MD simulation with NAMD to investigate: (1) the folding pathway of λ-repressor and (2) the effect of mutations on folding of the λ-repressor.

Spotlight: Everybody can Fold Proteins (Jan 2013)

Integrin-RGD binding under force

image size: 64.7KB
see also movie, 11.5MB
made with VMD

Every living cell relies on proteins to carry out its functional tasks; every protein needs to assume a proper shape in order to be operational for these tasks. How a protein, composed of a particular sequence of amino acids, could find its way to a proper shape is a fundamental, yet mysterious biological process. Researchers have sought to unravel atomistic details of protein folding processes through computer simulations, but modeling such processes is computationally demanding. It was only recently that some researchers have been able to observe in some case how proteins fold, but needed for the purpose the fastest computers available today. One of these computers is Anton, the expensive special-purpose supercomputer available essentially only to a single research group. Is there an affordable way to simulate protein folding? One solution could be coarse-grained methods. These methods save tremendous computational effort by replacing computational models that include all atomistic detail. However, the simplified models need to include a sufficiently accurate description of proteins for modeling folding processes. As reported recently, researchers have overcome the challenge by combining atomistic and coarse-grained descriptions. The new method is fast enough to follow movements of proteins long enough to see them fold, while requiring only readily available computer powers. The new method allowed researchers to analyze complete folding events for seven proteins, including a protein, called α3D (see movie, 11.5 M), that is one of the largest proteins ever folded computationally. More on our hybrid-resolution model website.

Related Spotlights

Related Publications
Related Research
Investigators
Publications Database
  • Disulfide bridges: bringing together frustrated structure in a bioactive peptide. Yi Zhang, Klaus Schulten, Martin Gruebele, Paramjit S. Bansal, David Wilson, and Norelle L. Daly. Biophysical Journal, 110:1744-1752, 2016.
  • Transient b-hairpin formation in a-synuclein monomer revealed by coarse-grained molecular dynamics simulation. Hang Yu, Wei Han, Wen Ma, and Klaus Schulten. Journal of Chemical Physics, 143:243142, 2015.
  • Comparing fast pressure jump and temperature jump protein folding experiments and simulations. Anna Jean Wirth, Yanxin Liu, Maxim B. Prigozhin, Klaus Schulten, and Martin Gruebele. Journal of the American Chemical Society, 137:7152-7159, 2015.
  • Observation of complete pressure-jump protein refolding in molecular dynamics simulation and experiment. Yanxin Liu, Maxim B. Prigozhin, Klaus Schulten, and Martin Gruebele. Journal of the American Chemical Society, 136:4265-4272, 2014.
  • Characterization of folding mechanisms of Trp-cage and WW-domain by network analysis of simulations with a hybrid-resolution model. Wei Han and Klaus Schulten. Journal of Physical Chemistry B, 117:13367-13377, 2013.
  • Misplaced helix slows down ultrafast pressure-jump protein folding. Maxim B. Prigozhin, Yanxin Liu, Anna Jean Wirth, Shobhna Kapoor, Roland Winter, Klaus Schulten, and Martin Gruebele. Proceedings of the National Academy of Sciences, USA, 110:8087-8092, 2013.
  • Structural characterization of l-repressor folding from all-atom molecular dynamics simulations. Yanxin Liu, Johan Strümpfer, Peter L. Freddolino, Martin Gruebele, and Klaus Schulten. Journal of Physical Chemistry Letters, 3:1117-1123, 2012.
  • Challenges in protein folding simulations. Peter L. Freddolino, Christopher B. Harrison, Yanxin Liu, and Klaus Schulten. Nature Physics, 6:751-758, 2010.
  • Going beyond clustering in MD trajectory analysis: an application to villin headpiece folding. Aruna Rajan, Peter L. Freddolino, and Klaus Schulten. PLoS One, 5:e9890, 2010. (12 pages).
  • Common structural transitions in explicit-solvent simulations of villin headpiece folding. Peter L. Freddolino and Klaus Schulten. Biophysical Journal, 97:2338-2347, 2009.
  • Force field bias in protein folding simulations. Peter L. Freddolino, Sanghyun Park, Benoit Roux, and Klaus Schulten. Biophysical Journal, 96:3772-3780, 2009.
  • Ten-microsecond molecular dynamics simulation of a fast-folding WW domain. Peter L. Freddolino, Feng Liu, Martin Gruebele, and Klaus Schulten. Biophysical Journal, 94:L75-L77, 2008.
  • Funded by a grant from
    the National Institute of
    General Medical Sciences
    of the National Institutes
    of Health