The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Studying functional dynamics in bio-molecules using accelerated molecular dynamics
Abstract
Many biologically important processes such as enzyme catalysis, signal transduction, ligand binding and allosteric regulation occur on the micro- to millisecond time-scale. Despite the sustained and rapid increase in available computational power and the development of efficient simulation algorithms, molecular dynamics (MD) simulations of proteins and bio-machines are generally limited to time-scales of tens to hundreds of nano-seconds. In this perspective article we present a comprehensive review of Accelerated Molecular Dynamics (AMD), an extended biased potential molecular dynamics approach that allows for the efficient study of bio-molecular systems up to time-scales several orders of magnitude greater than those accessible using standard classical MD methods, whilst still maintaining a fully atomistic representation of the system. Compared to many other approaches, AMD affords efficient enhanced conformational space sampling without any a priori understanding of the underlying free energy surface, nor does it require the specific prior definition of a reaction coordinate or a set of collective variables. Successful applications of the AMD method, including the study of slow time-scale functional dynamics in folded proteins and the conformational behavior of natively unstructured proteins are discussed and an outline of the different variants and extensions to the standard AMD approach is presented.
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Cites
T RANSITION P ATH S AMPLING : Throwing Ropes Over Rough Mountain Passes, in the Dark
Bolhuis, P. G., Chandler, D., Dellago, C., & Geissler, P. L. (2002) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.53.082301.113146 · Cited by 1,972
Structure of tumor suppressor p53 and its intrinsically disordered N-terminal transactivation domain
Wells, M., Tidow, H., Rutherford, T. J., Markwick, P., Jensen, M. R., Mylonas, E., Svergun, D. I., Blackledge, M., & Fersht, A. R. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0801353105 · Cited by 434
Self-citationOpen-to-closed transition in apo maltose-binding protein observed by paramagnetic NMR
Tang, C., Schwieters, C. D., & Clore, G. M. (2007) · Nature · doi:10.1038/nature06232 · Cited by 416
Cited by
Improved Reweighting of Accelerated Molecular Dynamics Simulations for Free Energy Calculation
Miao, Y., Sinko, W., Pierce, L., Bucher, D., Walker, R. C., & McCammon, J. A. (2014) · Journal of Chemical Theory and Computation · doi:10.1021/ct500090q · Cited by 455
Self-citationAllostery in Its Many Disguises: From Theory to Applications
Wodak, S. J., Paci, E., Dokholyan, N. V., Berezovsky, I. N., Horovitz, A., Li, J., Hilser, V. J., Bahar, I., Karanicolas, J., Stock, G., et al. (2019) · Structure · doi:10.1016/j.str.2019.01.003 · Cited by 404
Self-citationControlling Allosteric Networks in Proteins
Dokholyan, N. V. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00544 · Cited by 260
Accelerated molecular dynamics simulations of protein folding
Miao, Y., Feixas, F., Eun, C., & McCammon, J. A. (2015) · Journal of Computational Chemistry · doi:10.1002/jcc.23964 · Cited by 202
Self-citationExploring the role of receptor flexibility in structure-based drug discovery
Feixas, F., Lindert, S., Sinko, W., & McCammon, J. A. (2014) · Biophysical Chemistry · doi:10.1016/j.bpc.2013.10.007 · Cited by 156
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Metadata
- Authors
- Markwick, P. R. L., & McCammon, J. A.
- Venue
- Physical Chemistry Chemical Physics
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2011
- Volume
- 13
- Issue
- 45
- Pages
- 20053
- ISSN
- 1463-9076 (ISSN-L)
- 1463-9084
- OpenAlex
- W2093407764
- Cited by
- 168
- References
- 3
- FWCI
- 4.00
- Type
- journal article
- Language
- en
- Open access
- closed
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