20
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Unfolding mechanism of thrombin-binding aptamer revealed by molecular dynamics simulation and Markov State Model

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Thrombin-binding aptamer (TBA) with the sequence 5′GGTTGGTGTGGTTGG3′ could fold into G-quadruplex, which correlates with functionally important genomic regionsis. However, unfolding mechanism involved in the structural stability of G-quadruplex has not been satisfactorily elucidated on experiments so far. Herein, we studied the unfolding pathway of TBA by a combination of molecular dynamics simulation (MD) and Markov State Model (MSM). Our results revealed that the unfolding of TBA is not a simple two-state process but proceeds along multiple pathways with multistate intermediates. One high flux confirms some observations from NMR experiment. Another high flux exhibits a different and simpler unfolding pathway with less intermediates. Two important intermediate states were identified. One is similar to the G-triplex reported in the folding of G-quadruplex, but lack of H-bonding between guanines in the upper plane. More importantly, another intermediate state acting as a connector to link the folding region and the unfolding one, was the first time identified, which exhibits higher population and stability than the G-triplex-like intermediate. These results will provide valuable information for extending our understanding the folding landscape of G-quadruplex formation.

          Related collections

          Most cited references48

          • Record: found
          • Abstract: found
          • Article: not found

          Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics.

          To meet the challenge of modeling the conformational dynamics of biological macromolecules over long time scales, much recent effort has been devoted to constructing stochastic kinetic models, often in the form of discrete-state Markov models, from short molecular dynamics simulations. To construct useful models that faithfully represent dynamics at the time scales of interest, it is necessary to decompose configuration space into a set of kinetically metastable states. Previous attempts to define these states have relied upon either prior knowledge of the slow degrees of freedom or on the application of conformational clustering techniques which assume that conformationally distinct clusters are also kinetically distinct. Here, we present a first version of an automatic algorithm for the discovery of kinetically metastable states that is generally applicable to solvated macromolecules. Given molecular dynamics trajectories initiated from a well-defined starting distribution, the algorithm discovers long lived, kinetically metastable states through successive iterations of partitioning and aggregating conformation space into kinetically related regions. The authors apply this method to three peptides in explicit solvent-terminally blocked alanine, the 21-residue helical F(s) peptide, and the engineered 12-residue beta-hairpin trpzip2-to assess its ability to generate physically meaningful states and faithful kinetic models.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Transition-path theory and path-finding algorithms for the study of rare events.

            Transition-path theory is a theoretical framework for describing rare events in complex systems. It can also be used as a starting point for developing efficient numerical algorithms for analyzing such rare events. Here we review the basic components of transition-path theory and path-finding algorithms. We also discuss connections with the classical transition-state theory.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              MSMBuilder2: Modeling Conformational Dynamics at the Picosecond to Millisecond Scale.

              Markov State Models provide a framework for understanding the fundamental states and rates in the conformational dynamics of biomolecules. We describe an improved protocol for constructing Markov State Models from molecular dynamics simulations. The new protocol includes advances in clustering, data preparation, and model estimation; these improvements lead to significant increases in model accuracy, as assessed by the ability to recapitulate equilibrium and kinetic properties of reference systems. A high-performance implementation of this protocol, provided in MSMBuilder2, is validated on dynamics ranging from picoseconds to milliseconds.
                Bookmark

                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                05 April 2016
                2016
                : 6
                : 24065
                Affiliations
                [1 ]Faculty of Chemistry, Sichuan University , Chengdu 610064, People’s Republic of China
                Author notes
                Article
                srep24065
                10.1038/srep24065
                4820715
                27045335
                b9e24cbe-0d33-405e-a364-8787e7dce967
                Copyright © 2016, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 11 January 2016
                : 16 March 2016
                Categories
                Article

                Uncategorized
                Uncategorized

                Comments

                Comment on this article