ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution.
ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution.
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DOI:
10.1021/acs.jctc.6b00319
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发表时间:
2016-09-13
影响因子:
5.5
通讯作者:
Doruker, Pemra
中科院分区:
文献类型:
--
作者:
Kurkcuoglu, Zeynep;Bahar, Ivet;Doruker, Pemra
Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events.
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影响因子:
6.8
作者:
Grant BJ;Gorfe AA;McCammon JA
通讯作者:
McCammon JA
DOI:
10.1038/nsb0495-303
发表时间:
1995-04-01
期刊:
NATURE STRUCTURAL BIOLOGY
影响因子:
--
作者:
ESNOUF, R;REN, JS;STUART, D
通讯作者:
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影响因子:
5.5
作者:
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通讯作者:
Perahia, David
DOI:
10.1073/pnas.0802496105
发表时间:
2008-07-29
影响因子:
11.1
作者:
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通讯作者:
Sternberg, Michael J. E.
影响因子:
5.6
作者:
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通讯作者:
Woolf TB