2013
DOI: 10.1021/ct400198q
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Hidden Conformation Events in DNA Base Extrusions: A Generalized-Ensemble Path Optimization and Equilibrium Simulation Study

Abstract: DNA base extrusion is a crucial component of many biomolecular processes. Elucidating how bases are selectively extruded from the interiors of double-strand DNAs is pivotal to accurately understanding and efficiently sampling this general type of conformational transitions. In this work, the on-the-path random walk (OTPRW) method, which is the first generalized ensemble sampling scheme designed for finite-temperature-string path optimizations, was improved and applied to obtain the minimum free energy path (MF… Show more

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Cited by 21 publications
(39 citation statements)
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References 76 publications
(153 reference statements)
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“…[9398] Some recent extensions have also been used in studies of reactive dynamics using CHIT. [46,47] For more details of these methods, we refer readers to recent reviews. [89,99]…”
Section: Free Energy-related Methodsmentioning
confidence: 99%
“…[9398] Some recent extensions have also been used in studies of reactive dynamics using CHIT. [46,47] For more details of these methods, we refer readers to recent reviews. [89,99]…”
Section: Free Energy-related Methodsmentioning
confidence: 99%
“…Regarding the original string method, two sampling issues are worth noting: (a) because images are independently explored, the on-the-path continuity of the environmental degrees of freedom cannot be guaranteed; (b) the CV degrees of freedom are restricted from regular MD sampling and thus it is challenging for a being-optimized path that represents an unfavorable mechanism to be switched into the correct reaction channel. To overcome these issues, we developed a generalized ensemble sampling based string path optimization method: the on-the-path random walk (OTPRW) algorithm 24,27 . In OTPRW, the CV-space pathway is represented by a set of λ -dependent functions Z ( λ ) = ( z 1 ( λ ),…, z m ( λ )), in which Z (0) = Z A and Z (1) = Z B , where the progressing parameter λ is set equal to the percentage of the on-the-path distance of the corresponding state from the starting point Z A .…”
Section: Generalized Ensemble Based String Optimization: the On-the-pmentioning
confidence: 99%
“…Through the biasing function f m ( λ ), which can be adaptively obtained via either the metadynamics 24 or the ABF method 27 , the target system, instead of being constrained on non-communicating images, can randomly walk along the instantaneous path to collect samples for the following path optimization. Thereby, the structural continuity of the environmental degrees of freedom can be naturally ensured; notably at a joint image state between two pathways, the system can switch from an unfavorable pathway to a better reaction channel (Figure 3).…”
Section: Generalized Ensemble Based String Optimization: the On-the-pmentioning
confidence: 99%
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