Bend-twist-stretch model for coarse elastic network simulation of biomolecular motion

The empirical harmonic potential function of elastic network models (ENMs) is augmented by three- and four-body interactions as well as by a parameter-free connection rule. In the new bend-twist-stretch (BTS) model the complexity of the parametrization is shifted from the spatial level of detail to...

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Published inThe Journal of chemical physics Vol. 131; no. 7; p. 074112
Main Authors Stember, Joseph N., Wriggers, Willy
Format Journal Article
LanguageEnglish
Published United States American Institute of Physics 21.08.2009
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Online AccessGet full text
ISSN0021-9606
1089-7690
1520-9032
1089-7690
DOI10.1063/1.3167410

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Abstract The empirical harmonic potential function of elastic network models (ENMs) is augmented by three- and four-body interactions as well as by a parameter-free connection rule. In the new bend-twist-stretch (BTS) model the complexity of the parametrization is shifted from the spatial level of detail to the potential function, enabling an arbitrary coarse graining of the network. Compared to distance cutoff-based Hookean springs, the approach yields a more stable parametrization of coarse-grained ENMs for biomolecular dynamics. Traditional ENMs give rise to unbounded zero-frequency vibrations when (pseudo)atoms are connected to fewer than three neighbors. A large cutoff is therefore chosen in an ENM (about twice the average nearest-neighbor distance), resulting in many false-positive connections that reduce the spatial detail that can be resolved. More importantly, the required three-neighbor connectedness also limits the coarse graining, i.e., the network must be dense, even in the case of low-resolution structures that exhibit few spatial features. The new BTS model achieves such coarse graining by extending the ENM potential to include three-and four-atom interactions (bending and twisting, respectively) in addition to the traditional two-atom stretching. Thus, the BTS model enables reliable modeling of any three-dimensional graph irrespective of the atom connectedness. The additional potential terms were parametrized using continuum elastic theory of elastic rods, and the distance cutoff was replaced by a competitive Hebb connection rule, setting all free parameters in the model. We validate the approach on a carbon-alpha representation of adenylate kinase and illustrate its use with electron microscopy maps of E. coli RNA polymerase, E. coli ribosome, and eukaryotic chaperonin containing T-complex polypeptide 1, which were difficult to model with traditional ENMs. For adenylate kinase, we find excellent reproduction (>90% overlap) of the ENM modes and B factors when BTS is applied to the carbon-alpha representation as well as to coarser descriptions. For the volumetric maps, coarse BTS yields similar motions (70%–90% overlap) to those obtained from significantly denser representations with ENM. Our Python-based algorithms of ENM and BTS implementations are freely available.
AbstractList The empirical harmonic potential function of elastic network models (ENMs) is augmented by three- and four-body interactions as well as by a parameter-free connection rule. In the new bend-twist-stretch (BTS) model the complexity of the parametrization is shifted from the spatial level of detail to the potential function, enabling an arbitrary coarse graining of the network. Compared to distance cutoff-based Hookean springs, the approach yields a more stable parametrization of coarse-grained ENMs for biomolecular dynamics. Traditional ENMs give rise to unbounded zero-frequency vibrations when (pseudo)atoms are connected to fewer than three neighbors. A large cutoff is therefore chosen in an ENM (about twice the average nearest-neighbor distance), resulting in many false-positive connections that reduce the spatial detail that can be resolved. More importantly, the required three-neighbor connectedness also limits the coarse graining, i.e., the network must be dense, even in the case of low-resolution structures that exhibit few spatial features. The new BTS model achieves such coarse graining by extending the ENM potential to include three-and four-atom interactions (bending and twisting, respectively) in addition to the traditional two-atom stretching. Thus, the BTS model enables reliable modeling of any three-dimensional graph irrespective of the atom connectedness. The additional potential terms were parametrized using continuum elastic theory of elastic rods, and the distance cutoff was replaced by a competitive Hebb connection rule, setting all free parameters in the model. We validate the approach on a carbon-alpha representation of adenylate kinase and illustrate its use with electron microscopy maps of E. coli RNA polymerase, E. coli ribosome, and eukaryotic chaperonin containing T-complex polypeptide 1, which were difficult to model with traditional ENMs. For adenylate kinase, we find excellent reproduction (>90% overlap) of the ENM modes and B factors when BTS is applied to the carbon-alpha representation as well as to coarser descriptions. For the volumetric maps, coarse BTS yields similar motions (70%-90% overlap) to those obtained from significantly denser representations with ENM. Our Python-based algorithms of ENM and BTS implementations are freely available.
The empirical harmonic potential function of elastic network models (ENMs) is augmented by three- and four-body interactions as well as by a parameter-free connection rule. In the new bend-twist-stretch (BTS) model the complexity of the parametrization is shifted from the spatial level of detail to the potential function, enabling an arbitrary coarse graining of the network. Compared to distance cutoff-based Hookean springs, the approach yields a more stable parametrization of coarse-grained ENMs for biomolecular dynamics. Traditional ENMs give rise to unbounded zero-frequency vibrations when (pseudo)atoms are connected to fewer than three neighbors. A large cutoff is therefore chosen in an ENM (about twice the average nearest-neighbor distance), resulting in many false-positive connections that reduce the spatial detail that can be resolved. More importantly, the required three-neighbor connectedness also limits the coarse graining, i.e., the network must be dense, even in the case of low-resolution structures that exhibit few spatial features. The new BTS model achieves such coarse graining by extending the ENM potential to include three-and four-atom interactions (bending and twisting, respectively) in addition to the traditional two-atom stretching. Thus, the BTS model enables reliable modeling of any three-dimensional graph irrespective of the atom connectedness. The additional potential terms were parametrized using continuum elastic theory of elastic rods, and the distance cutoff was replaced by a competitive Hebb connection rule, setting all free parameters in the model. We validate the approach on a carbon-alpha representation of adenylate kinase and illustrate its use with electron microscopy maps of E. coli RNA polymerase, E. coli ribosome, and eukaryotic chaperonin containing T-complex polypeptide 1, which were difficult to model with traditional ENMs. For adenylate kinase, we find excellent reproduction (>90% overlap) of the ENM modes and B factors when BTS is applied to the carbon-alpha representation as well as to coarser descriptions. For the volumetric maps, coarse BTS yields similar motions (70%-90% overlap) to those obtained from significantly denser representations with ENM. Our Python-based algorithms of ENM and BTS implementations are freely available.The empirical harmonic potential function of elastic network models (ENMs) is augmented by three- and four-body interactions as well as by a parameter-free connection rule. In the new bend-twist-stretch (BTS) model the complexity of the parametrization is shifted from the spatial level of detail to the potential function, enabling an arbitrary coarse graining of the network. Compared to distance cutoff-based Hookean springs, the approach yields a more stable parametrization of coarse-grained ENMs for biomolecular dynamics. Traditional ENMs give rise to unbounded zero-frequency vibrations when (pseudo)atoms are connected to fewer than three neighbors. A large cutoff is therefore chosen in an ENM (about twice the average nearest-neighbor distance), resulting in many false-positive connections that reduce the spatial detail that can be resolved. More importantly, the required three-neighbor connectedness also limits the coarse graining, i.e., the network must be dense, even in the case of low-resolution structures that exhibit few spatial features. The new BTS model achieves such coarse graining by extending the ENM potential to include three-and four-atom interactions (bending and twisting, respectively) in addition to the traditional two-atom stretching. Thus, the BTS model enables reliable modeling of any three-dimensional graph irrespective of the atom connectedness. The additional potential terms were parametrized using continuum elastic theory of elastic rods, and the distance cutoff was replaced by a competitive Hebb connection rule, setting all free parameters in the model. We validate the approach on a carbon-alpha representation of adenylate kinase and illustrate its use with electron microscopy maps of E. coli RNA polymerase, E. coli ribosome, and eukaryotic chaperonin containing T-complex polypeptide 1, which were difficult to model with traditional ENMs. For adenylate kinase, we find excellent reproduction (>90% overlap) of the ENM modes and B factors when BTS is applied to the carbon-alpha representation as well as to coarser descriptions. For the volumetric maps, coarse BTS yields similar motions (70%-90% overlap) to those obtained from significantly denser representations with ENM. Our Python-based algorithms of ENM and BTS implementations are freely available.
Author Wriggers, Willy
Stember, Joseph N.
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Cites_doi 10.1006/jsbi.1998.4080
10.1016/j.neucom.2003.09.007
10.1002/(SICI)1097-0134(19981115)33:3<417::AID-PROT10>3.0.CO;2-8
10.1002/bip.360210318
10.1038/nature06893
10.1016/S0969-2126(01)00648-7
10.1103/PhysRevLett.77.1905
10.1016/0263-7855(96)00018-5
10.1038/296776a0
10.1021/bi00188a001
10.1016/S0092-8674(00)81515-9
10.1016/0022-2836(85)90230-X
10.1006/jmbi.1998.2232
10.1016/S0022-2836(02)00627-7
10.1016/S0022-2836(02)01426-2
10.1073/pnas.1632476100
10.1007/978-94-017-1120-3
10.1073/pnas.052054099
10.1016/S0969-2126(96)00018-4
10.1146/annurev.biophys.31.082901.134202
10.1109/72.238311
10.1016/S0959-440X(02)00315-9
10.1016/j.jmgm.2005.09.006
10.1002/jcc.1160
10.1080/08927020600771415
10.1093/protein/14.1.1
10.1073/pnas.0802496105
10.1146/annurev.biophys.35.040405.102010
10.1016/j.jmb.2008.01.027
10.1002/prot.20743
10.1021/ct050307u
10.1529/biophysj.105.065904
10.1073/pnas.082148899
10.1038/35018597
10.1016/S1359-0278(97)00024-2
10.1063/1.3027989
10.1002/prot.340100204
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Permanent address: D. E. Shaw Research, 120 W. 45th St., New York, NY 10036, USA. Electronic mail: willy.wriggers@deshawresearch.com.
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References (2023062604251256600_c42) 2000; 406
(2023062604251256600_c3) 1994; 33
(2023062604251256600_c1) 2006
(2023062604251256600_c2) 1991; 10
(2023062604251256600_c5) 1955
(2023062604251256600_c12) 1997; 2
(2023062604251256600_c35) 1991
(2023062604251256600_c45) 2001; 14
(2023062604251256600_c11) 1996; 77
2023062604251256600_c32
(2023062604251256600_c8) 1985; 181
(2023062604251256600_c36) 2006; 62
(2023062604251256600_c10) 1976
(2023062604251256600_c50) 1996; 14
van Gunsteren (2023062604251256600_c9) 1997
(2023062604251256600_c44) 2002; 12
(2023062604251256600_c20) 2003; 326
2023062604251256600_c29
(2023062604251256600_c43) 2003; 100
(2023062604251256600_c38) 1996; 4
(2023062604251256600_c41) 1999; 98
(2023062604251256600_c23) 2008; 377
(2023062604251256600_c16) 2006; 35
(2023062604251256600_c39) 2008; 453
(2023062604251256600_c15) 2002; 321
(2023062604251256600_c28) 1999; 125
(2023062604251256600_c37) 2008; 105
(2023062604251256600_c25) 1982
(2023062604251256600_c7) 1982; 296
(2023062604251256600_c27) 1999
(2023062604251256600_c4) 2001
(2023062604251256600_c31) 2004; 56
2023062604251256600_c18
(2023062604251256600_c22) 2002; 31
(2023062604251256600_c14) 2002; 23
(2023062604251256600_c30) 1998; 284
(2023062604251256600_c49) 2008; 61
2023062604251256600_c19
(2023062604251256600_c46) 2001; 9
(2023062604251256600_c6) 1982; 21
(2023062604251256600_c17) 2005; 89
(2023062604251256600_c47) 2006; 24
(2023062604251256600_c26) 2005
(2023062604251256600_c13) 1998; 33
(2023062604251256600_c33) 1993; 4
(2023062604251256600_c21) 2002; 99
(2023062604251256600_c24) 2006; 32
(2023062604251256600_c40) 2002; 99
(2023062604251256600_c48) 2006; 2
(2023062604251256600_c34) 2000
10917535 - Nature. 2000 Jul 20;406(6793):318-22
7066480 - Biopolymers. 1982 Mar;21(3):711-4
8805521 - Structure. 1996 Feb 15;4(2):147-56
11287673 - Protein Eng. 2001 Jan;14(1):1-6
11959502 - Curr Opin Struct Biol. 2002 Apr;12(2):231-8
16288462 - Proteins. 2006 Jan 1;62(1):152-8
18267757 - IEEE Trans Neural Netw. 1993;4(4):558-69
8744570 - J Mol Graph. 1996 Feb;14(1):33-8, 27-8
11566128 - Structure. 2001 Sep;9(9):779-88
9878345 - J Mol Biol. 1998 Dec 18;284(5):1247-54
12144786 - J Mol Biol. 2002 Aug 9;321(2):297-305
11913377 - J Comput Chem. 2002 Jan 15;23(1):119-27
16289973 - J Mol Graph Model. 2006 Jan;24(4):296-306
9829700 - Proteins. 1998 Nov 15;33(3):417-29
16689630 - Annu Rev Biophys Biomol Struct. 2006;35:115-33
12084922 - Proc Natl Acad Sci U S A. 2002 Jun 25;99(13):8620-5
21760758 - J Chem Theory Comput. 2006;2(3):464-471
10499798 - Cell. 1999 Sep 17;98(6):811-24
18641126 - Proc Natl Acad Sci U S A. 2008 Jul 29;105(30):10390-5
12878726 - Proc Natl Acad Sci U S A. 2003 Aug 5;100(16):9319-23
10063201 - Phys Rev Lett. 1996 Aug 26;77(9):1905-1908
18449192 - Nature. 2008 May 15;453(7193):415-9
8204609 - Biochemistry. 1994 Jun 7;33(22):6739-49
11988472 - Annu Rev Biophys Biomol Struct. 2002;31:303-19
11904365 - Proc Natl Acad Sci U S A. 2002 Apr 2;99(7):4296-301
2580101 - J Mol Biol. 1985 Feb 5;181(3):423-47
12559916 - J Mol Biol. 2003 Feb 14;326(2):485-92
10222274 - J Struct Biol. 1999 Apr-May;125(2-3):185-95
16055547 - Biophys J. 2005 Oct;89(4):2395-401
9218955 - Fold Des. 1997;2(3):173-81
18262542 - J Mol Biol. 2008 Mar 21;377(2):489-500
7070518 - Nature. 1982 Apr 22;296(5859):776-8
1896424 - Proteins. 1991;10(2):106-16
References_xml – volume: 125
  start-page: 185
  year: 1999
  ident: 2023062604251256600_c28
  publication-title: J. Struct. Biol.
  doi: 10.1006/jsbi.1998.4080
– volume-title: Statistical Mechanics
  year: 1976
  ident: 2023062604251256600_c10
– ident: 2023062604251256600_c29
– volume-title: Computational Geometry: Algorithms and Applications
  year: 2000
  ident: 2023062604251256600_c34
– volume: 56
  start-page: 365
  year: 2004
  ident: 2023062604251256600_c31
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2003.09.007
– volume-title: Molecular Vibrations
  year: 1955
  ident: 2023062604251256600_c5
– volume: 33
  start-page: 417
  year: 1998
  ident: 2023062604251256600_c13
  publication-title: Proteins: Struct., Funct., Bioinf.
  doi: 10.1002/(SICI)1097-0134(19981115)33:3<417::AID-PROT10>3.0.CO;2-8
– volume: 21
  start-page: 711
  year: 1982
  ident: 2023062604251256600_c6
  publication-title: Biopolymers
  doi: 10.1002/bip.360210318
– volume: 453
  start-page: 415
  year: 2008
  ident: 2023062604251256600_c39
  publication-title: Nature (London)
  doi: 10.1038/nature06893
– volume: 9
  start-page: 779
  year: 2001
  ident: 2023062604251256600_c46
  publication-title: Structure (London)
  doi: 10.1016/S0969-2126(01)00648-7
– volume: 77
  start-page: 1905
  year: 1996
  ident: 2023062604251256600_c11
  publication-title: Phys. Rev. Lett.
  doi: 10.1103/PhysRevLett.77.1905
– volume: 14
  start-page: 33
  year: 1996
  ident: 2023062604251256600_c50
  publication-title: J. Mol. Graphics
  doi: 10.1016/0263-7855(96)00018-5
– volume: 296
  start-page: 776
  year: 1982
  ident: 2023062604251256600_c7
  publication-title: Nature (London)
  doi: 10.1038/296776a0
– volume: 33
  start-page: 6739
  year: 1994
  ident: 2023062604251256600_c3
  publication-title: Biochemistry
  doi: 10.1021/bi00188a001
– volume-title: Twentieth Century Harmonic Analysis - A Celebration
  year: 2001
  ident: 2023062604251256600_c4
– year: 1999
  ident: 2023062604251256600_c27
– volume: 98
  start-page: 811
  year: 1999
  ident: 2023062604251256600_c41
  publication-title: Cell
  doi: 10.1016/S0092-8674(00)81515-9
– volume: 181
  start-page: 423
  year: 1985
  ident: 2023062604251256600_c8
  publication-title: J. Mol. Biol.
  doi: 10.1016/0022-2836(85)90230-X
– volume: 284
  start-page: 1247
  year: 1998
  ident: 2023062604251256600_c30
  publication-title: J. Mol. Biol.
  doi: 10.1006/jmbi.1998.2232
– volume: 321
  start-page: 297
  year: 2002
  ident: 2023062604251256600_c15
  publication-title: J. Mol. Biol.
  doi: 10.1016/S0022-2836(02)00627-7
– volume: 326
  start-page: 485
  year: 2003
  ident: 2023062604251256600_c20
  publication-title: J. Mol. Biol.
  doi: 10.1016/S0022-2836(02)01426-2
– volume: 100
  start-page: 9319
  year: 2003
  ident: 2023062604251256600_c43
  publication-title: Proc. Natl. Acad. Sci. U.S.A.
  doi: 10.1073/pnas.1632476100
– start-page: 284
  volume-title: Computer Simulation of Biomolecular Systems
  year: 1997
  ident: 2023062604251256600_c9
  doi: 10.1007/978-94-017-1120-3
– volume: 99
  start-page: 4296
  year: 2002
  ident: 2023062604251256600_c40
  publication-title: Proc. Natl. Acad. Sci. U.S.A.
  doi: 10.1073/pnas.052054099
– volume: 4
  start-page: 147
  year: 1996
  ident: 2023062604251256600_c38
  publication-title: Structure (London)
  doi: 10.1016/S0969-2126(96)00018-4
– volume: 31
  start-page: 303
  year: 2002
  ident: 2023062604251256600_c22
  publication-title: Annu. Rev. Biophys. Biomol. Struct.
  doi: 10.1146/annurev.biophys.31.082901.134202
– ident: 2023062604251256600_c18
– volume: 4
  start-page: 558
  year: 1993
  ident: 2023062604251256600_c33
  publication-title: IEEE Trans. Neural Netw.
  doi: 10.1109/72.238311
– volume: 12
  start-page: 231
  year: 2002
  ident: 2023062604251256600_c44
  publication-title: Curr. Opin. Struct. Biol.
  doi: 10.1016/S0959-440X(02)00315-9
– volume: 24
  start-page: 296
  year: 2006
  ident: 2023062604251256600_c47
  publication-title: J. Mol. Graphics Modell.
  doi: 10.1016/j.jmgm.2005.09.006
– volume: 23
  start-page: 119
  year: 2002
  ident: 2023062604251256600_c14
  publication-title: J. Comput. Chem.
  doi: 10.1002/jcc.1160
– volume-title: Physics of Continuous Matter
  year: 2005
  ident: 2023062604251256600_c26
– volume-title: Morphometric Tools for Landmark Data
  year: 1991
  ident: 2023062604251256600_c35
– volume: 32
  start-page: 803
  year: 2006
  ident: 2023062604251256600_c24
  publication-title: Mol. Simul.
  doi: 10.1080/08927020600771415
– ident: 2023062604251256600_c32
– volume: 14
  start-page: 1
  year: 2001
  ident: 2023062604251256600_c45
  publication-title: Protein Eng.
  doi: 10.1093/protein/14.1.1
– volume-title: Normal Mode Analysis
  year: 2006
  ident: 2023062604251256600_c1
– volume: 105
  start-page: 10390
  year: 2008
  ident: 2023062604251256600_c37
  publication-title: Proc. Natl. Acad. Sci. U.S.A.
  doi: 10.1073/pnas.0802496105
– volume-title: Mechanics - Course of Theoretical Physics
  year: 1982
  ident: 2023062604251256600_c25
– volume: 35
  start-page: 115
  year: 2006
  ident: 2023062604251256600_c16
  publication-title: Annu. Rev. Biophys. Biomol. Struct.
  doi: 10.1146/annurev.biophys.35.040405.102010
– volume: 377
  start-page: 489
  year: 2008
  ident: 2023062604251256600_c23
  publication-title: J. Mol. Biol.
  doi: 10.1016/j.jmb.2008.01.027
– volume: 62
  start-page: 152
  year: 2006
  ident: 2023062604251256600_c36
  publication-title: Proteins: Struct., Funct., Bioinf.
  doi: 10.1002/prot.20743
– ident: 2023062604251256600_c19
– volume: 2
  start-page: 464
  year: 2006
  ident: 2023062604251256600_c48
  publication-title: J. Chem. Theory Comput.
  doi: 10.1021/ct050307u
– volume: 89
  start-page: 2395
  year: 2005
  ident: 2023062604251256600_c17
  publication-title: Biophys. J.
  doi: 10.1529/biophysj.105.065904
– volume: 99
  start-page: 8620
  year: 2002
  ident: 2023062604251256600_c21
  publication-title: Proc. Natl. Acad. Sci. U.S.A.
  doi: 10.1073/pnas.082148899
– volume: 406
  start-page: 318
  year: 2000
  ident: 2023062604251256600_c42
  publication-title: Nature (London)
  doi: 10.1038/35018597
– volume: 2
  start-page: 173
  year: 1997
  ident: 2023062604251256600_c12
  publication-title: Folding Des.
  doi: 10.1016/S1359-0278(97)00024-2
– volume: 61
  start-page: 33
  year: 2008
  ident: 2023062604251256600_c49
  publication-title: Phys. Today
  doi: 10.1063/1.3027989
– volume: 10
  start-page: 106
  year: 1991
  ident: 2023062604251256600_c2
  publication-title: Proteins: Struct., Funct., Genet.
  doi: 10.1002/prot.340100204
– reference: 11904365 - Proc Natl Acad Sci U S A. 2002 Apr 2;99(7):4296-301
– reference: 12559916 - J Mol Biol. 2003 Feb 14;326(2):485-92
– reference: 1896424 - Proteins. 1991;10(2):106-16
– reference: 21760758 - J Chem Theory Comput. 2006;2(3):464-471
– reference: 9218955 - Fold Des. 1997;2(3):173-81
– reference: 11287673 - Protein Eng. 2001 Jan;14(1):1-6
– reference: 8805521 - Structure. 1996 Feb 15;4(2):147-56
– reference: 11959502 - Curr Opin Struct Biol. 2002 Apr;12(2):231-8
– reference: 8204609 - Biochemistry. 1994 Jun 7;33(22):6739-49
– reference: 10222274 - J Struct Biol. 1999 Apr-May;125(2-3):185-95
– reference: 9829700 - Proteins. 1998 Nov 15;33(3):417-29
– reference: 11988472 - Annu Rev Biophys Biomol Struct. 2002;31:303-19
– reference: 9878345 - J Mol Biol. 1998 Dec 18;284(5):1247-54
– reference: 10063201 - Phys Rev Lett. 1996 Aug 26;77(9):1905-1908
– reference: 18449192 - Nature. 2008 May 15;453(7193):415-9
– reference: 2580101 - J Mol Biol. 1985 Feb 5;181(3):423-47
– reference: 16689630 - Annu Rev Biophys Biomol Struct. 2006;35:115-33
– reference: 12144786 - J Mol Biol. 2002 Aug 9;321(2):297-305
– reference: 10499798 - Cell. 1999 Sep 17;98(6):811-24
– reference: 18267757 - IEEE Trans Neural Netw. 1993;4(4):558-69
– reference: 11566128 - Structure. 2001 Sep;9(9):779-88
– reference: 12084922 - Proc Natl Acad Sci U S A. 2002 Jun 25;99(13):8620-5
– reference: 16289973 - J Mol Graph Model. 2006 Jan;24(4):296-306
– reference: 16055547 - Biophys J. 2005 Oct;89(4):2395-401
– reference: 12878726 - Proc Natl Acad Sci U S A. 2003 Aug 5;100(16):9319-23
– reference: 11913377 - J Comput Chem. 2002 Jan 15;23(1):119-27
– reference: 10917535 - Nature. 2000 Jul 20;406(6793):318-22
– reference: 16288462 - Proteins. 2006 Jan 1;62(1):152-8
– reference: 7070518 - Nature. 1982 Apr 22;296(5859):776-8
– reference: 18262542 - J Mol Biol. 2008 Mar 21;377(2):489-500
– reference: 18641126 - Proc Natl Acad Sci U S A. 2008 Jul 29;105(30):10390-5
– reference: 8744570 - J Mol Graph. 1996 Feb;14(1):33-8, 27-8
– reference: 7066480 - Biopolymers. 1982 Mar;21(3):711-4
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Snippet The empirical harmonic potential function of elastic network models (ENMs) is augmented by three- and four-body interactions as well as by a parameter-free...
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SubjectTerms Adenylate Kinase - chemistry
Adenylate Kinase - metabolism
Biomechanical Phenomena
Chaperonins - chemistry
Chaperonins - metabolism
DNA-Directed RNA Polymerases - chemistry
DNA-Directed RNA Polymerases - metabolism
Elasticity
Escherichia coli - enzymology
Microscopy, Electron
Models, Molecular
Movement
Reproducibility of Results
Ribosomes - chemistry
Ribosomes - metabolism
Theoretical Methods and Algorithms
Title Bend-twist-stretch model for coarse elastic network simulation of biomolecular motion
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