Publications

Detailed Information

The Atomistic Mechanism of Conformational Transition of Adenylate Kinase Investigated by Lorentzian Structure-Based Potential

Cited 15 time in Web of Science Cited 14 time in Scopus
Authors

Lee, Ju Yong; Joo, Kee Hyoung; Brooks, Bernard R.; Lee, Joo Young

Issue Date
2015-07
Publisher
American Chemical Society
Citation
Journal of Chemical Theory and Computation, Vol.11 No.7, pp.3211-3224
Abstract
We present a new all-atom structure-based method to study protein conformational transitions using Lorentzian attractive interactions based on native structures. The variability of each native contact is estimated based on evolutionary information using a machine learning method. To test the validity of this approach, we have investigated the conformational transition of adenylate kinase (ADK). The intrinsic boundedness of the Lorentzian attractive interactions facilitated frequent conformational transitions, and consequently we were able to observe more than 1000 structural interconversions between the open and closed states of ADK out of a total of 6 mu s MD simulations. ADK has three domains: the nucleoside monophosphate (NMP) binding domain, the LID-domain, and the CORE domain, which catalyze the interconversion between ATP and ADP. We identified two transition states: a more frequent LID-closed-NMP-open (TS1) state and a less frequent LID-open-NMP-closed (TS2) state. The transition was found to be symmetric in both directions via TS1. We also obtained an off-pathway metastable state that was previously observed with physics-based all-atom simulations but not with coarse-grained models. In the metastable state, the LID domain was slightly twisted and formed contacts with the NMP domain. Our model correctly identified a total of 14 out of the top 16 residues with highest fluctuation by NMR experiment, thus showing excellent agreement with experimental NMR relaxation data and overwhelmingly better results than existing models.
ISSN
1549-9618
URI
https://hdl.handle.net/10371/201533
DOI
https://doi.org/10.1021/acs.jctc.5b00268
Files in This Item:
There are no files associated with this item.
Appears in Collections:

Related Researcher

  • Graduate School of Convergence Science & Technology
  • Dept. of Molecular and Biopharmaceutical Sciences
Research Area AI models for drug discovery, Free energy calculation, Molecular dynamics, 분자동역학, 신약개발을 위한 AI 모델, 자유에너지 계산

Altmetrics

Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Share