PMID- 24296313
OWN - NLM
STAT- MEDLINE
DCOM- 20140808
LR  - 20140101
IS  - 1873-4243 (Electronic)
IS  - 1093-3263 (Linking)
VI  - 47
DP  - 2014 Feb
TI  - Efficient prediction of protein conformational pathways based on the hybrid 
      elastic network model.
PG  - 25-36
LID - S1093-3263(13)00185-X [pii]
LID - 10.1016/j.jmgm.2013.10.009 [doi]
AB  - Various computational models have gained immense attention by analyzing the 
      dynamic characteristics of proteins. Several models have achieved recognition by 
      fulfilling either theoretical or experimental predictions. Nonetheless, each 
      method possesses limitations, mostly in computational outlay and physical 
      reality. These limitations remind us that a new model or paradigm should advance 
      theoretical principles to elucidate more precisely the biological functions of a 
      protein and should increase computational efficiency. With these critical 
      caveats, we have developed a new computational tool that satisfies both physical 
      reality and computational efficiency. In the proposed hybrid elastic network 
      model (HENM), a protein structure is represented as a mixture of rigid clusters 
      and point masses that are connected with linear springs. Harmonic analyses based 
      on the HENM have been performed to generate normal modes and conformational 
      pathways. The results of the hybrid normal mode analyses give new physical 
      insight to the 70S ribosome. The feasibility of the conformational pathways of 
      hybrid elastic network interpolation (HENI) was quantitatively evaluated by 
      comparing three different overlap values proposed in this paper. A remarkable 
      observation is that the obtained mode shapes and conformational pathways are 
      consistent with each other. Our timing results show that HENM has some advantage 
      in computational efficiency over a coarse-grained model, especially for large 
      proteins, even though it takes longer to construct the HENM. Consequently, the 
      proposed HENM will be one of the best alternatives to the conventional 
      coarse-grained ENMs and all-atom based methods (such as molecular dynamics) 
      without loss of physical reality.
CI  - Copyright (c) 2013 Elsevier Inc. All rights reserved.
FAU - Seo, Sangjae
AU  - Seo S
AD  - SKKU Advanced Institute of Nanotechnology, Sungkyunkwan University, Suwon 
      440-746, Republic of Korea.
FAU - Jang, Yunho
AU  - Jang Y
AD  - Department of Mechanical and Industrial Engineering, University of Massachusetts, 
      Amherst, MA 01003, USA.
FAU - Qian, Pengfei
AU  - Qian P
AD  - School of Mechanical Engineering, Sungkyunkwan University, Suwon 440-746, 
      Republic of Korea.
FAU - Liu, Wing Kam
AU  - Liu WK
AD  - Department of Mechanical Engineering, Northwestern University, Evanston, IL 
      60208, USA.
FAU - Choi, Jae-Boong
AU  - Choi JB
AD  - SKKU Advanced Institute of Nanotechnology, Sungkyunkwan University, Suwon 
      440-746, Republic of Korea; School of Mechanical Engineering, Sungkyunkwan 
      University, Suwon 440-746, Republic of Korea.
FAU - Lim, Byeong Soo
AU  - Lim BS
AD  - School of Mechanical Engineering, Sungkyunkwan University, Suwon 440-746, 
      Republic of Korea.
FAU - Kim, Moon Ki
AU  - Kim MK
AD  - SKKU Advanced Institute of Nanotechnology, Sungkyunkwan University, Suwon 
      440-746, Republic of Korea; School of Mechanical Engineering, Sungkyunkwan 
      University, Suwon 440-746, Republic of Korea. Electronic address: 
      mkkim@me.skku.ac.kr.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20131101
PL  - United States
TA  - J Mol Graph Model
JT  - Journal of molecular graphics & modelling
JID - 9716237
RN  - 0 (Proteins)
SB  - IM
MH  - Algorithms
MH  - Humans
MH  - *Models, Molecular
MH  - *Models, Theoretical
MH  - Molecular Dynamics Simulation
MH  - *Protein Conformation
MH  - Proteins/*chemistry
MH  - Ribosomes/chemistry
OTO - NOTNLM
OT  - Elastic network interpolation
OT  - Elastic network model
OT  - Normal mode analysis
OT  - Pathway generation
OT  - Protein dynamics
EDAT- 2013/12/04 06:00
MHDA- 2014/08/13 06:00
CRDT- 2013/12/04 06:00
PHST- 2013/01/12 00:00 [received]
PHST- 2013/10/19 00:00 [revised]
PHST- 2013/10/22 00:00 [accepted]
PHST- 2013/12/04 06:00 [entrez]
PHST- 2013/12/04 06:00 [pubmed]
PHST- 2014/08/13 06:00 [medline]
AID - S1093-3263(13)00185-X [pii]
AID - 10.1016/j.jmgm.2013.10.009 [doi]
PST - ppublish
SO  - J Mol Graph Model. 2014 Feb;47:25-36. doi: 10.1016/j.jmgm.2013.10.009. Epub 2013 
      Nov 1.