Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins
Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of co...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Shehu, Amarda [verfasserIn] Clementi, Cecilia [verfasserIn] Kavraki, Lydia E. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2007 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Algorithmica - New York, NY : Springer, 1986, 48(2007), 4 vom: 13. Juli, Seite 303-327 |
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| Übergeordnetes Werk: |
volume:48 ; year:2007 ; number:4 ; day:13 ; month:07 ; pages:303-327 |
| Links: |
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| DOI / URN: |
10.1007/s00453-007-0178-0 |
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| Katalog-ID: |
SPR006167403 |
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| 100 | 1 | |a Shehu, Amarda |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins |
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| 520 | |a Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales. | ||
| 650 | 4 | |a Polypeptide Chain |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Inverse Kinematic |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Energy Landscape |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Kinematic Chain |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Kinematic Constraint |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Clementi, Cecilia |e verfasserin |4 aut | |
| 700 | 1 | |a Kavraki, Lydia E. |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Algorithmica |d New York, NY : Springer, 1986 |g 48(2007), 4 vom: 13. Juli, Seite 303-327 |w (DE-627)253389704 |w (DE-600)1458414-1 |x 1432-0541 |7 nnns |
| 773 | 1 | 8 | |g volume:48 |g year:2007 |g number:4 |g day:13 |g month:07 |g pages:303-327 |
| 856 | 4 | 0 | |u https://dx.doi.org/10.1007/s00453-007-0178-0 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_SPRINGER | ||
| 912 | |a SSG-OPC-MAT | ||
| 912 | |a SSG-OPC-ASE | ||
| 912 | |a GBV_ILN_11 | ||
| 912 | |a GBV_ILN_20 | ||
| 912 | |a GBV_ILN_22 | ||
| 912 | |a GBV_ILN_23 | ||
| 912 | |a GBV_ILN_24 | ||
| 912 | |a GBV_ILN_31 | ||
| 912 | |a GBV_ILN_32 | ||
| 912 | |a GBV_ILN_39 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_60 | ||
| 912 | |a GBV_ILN_62 | ||
| 912 | |a GBV_ILN_63 | ||
| 912 | |a GBV_ILN_65 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_73 | ||
| 912 | |a GBV_ILN_74 | ||
| 912 | |a GBV_ILN_90 | ||
| 912 | |a GBV_ILN_95 | ||
| 912 | |a GBV_ILN_100 | ||
| 912 | |a GBV_ILN_101 | ||
| 912 | |a GBV_ILN_105 | ||
| 912 | |a GBV_ILN_110 | ||
| 912 | |a GBV_ILN_120 | ||
| 912 | |a GBV_ILN_138 | ||
| 912 | |a GBV_ILN_150 | ||
| 912 | |a GBV_ILN_151 | ||
| 912 | |a GBV_ILN_152 | ||
| 912 | |a GBV_ILN_161 | ||
| 912 | |a GBV_ILN_170 | ||
| 912 | |a GBV_ILN_171 | ||
| 912 | |a GBV_ILN_187 | ||
| 912 | |a GBV_ILN_213 | ||
| 912 | |a GBV_ILN_224 | ||
| 912 | |a GBV_ILN_230 | ||
| 912 | |a GBV_ILN_250 | ||
| 912 | |a GBV_ILN_267 | ||
| 912 | |a GBV_ILN_281 | ||
| 912 | |a GBV_ILN_285 | ||
| 912 | |a GBV_ILN_293 | ||
| 912 | |a GBV_ILN_370 | ||
| 912 | |a GBV_ILN_602 | ||
| 912 | |a GBV_ILN_636 | ||
| 912 | |a GBV_ILN_702 | ||
| 912 | |a GBV_ILN_2001 | ||
| 912 | |a GBV_ILN_2003 | ||
| 912 | |a GBV_ILN_2004 | ||
| 912 | |a GBV_ILN_2005 | ||
| 912 | |a GBV_ILN_2006 | ||
| 912 | |a GBV_ILN_2007 | ||
| 912 | |a GBV_ILN_2009 | ||
| 912 | |a GBV_ILN_2010 | ||
| 912 | |a GBV_ILN_2011 | ||
| 912 | |a GBV_ILN_2014 | ||
| 912 | |a GBV_ILN_2015 | ||
| 912 | |a GBV_ILN_2020 | ||
| 912 | |a GBV_ILN_2021 | ||
| 912 | |a GBV_ILN_2025 | ||
| 912 | |a GBV_ILN_2026 | ||
| 912 | |a GBV_ILN_2027 | ||
| 912 | |a GBV_ILN_2031 | ||
| 912 | |a GBV_ILN_2034 | ||
| 912 | |a GBV_ILN_2037 | ||
| 912 | |a GBV_ILN_2038 | ||
| 912 | |a GBV_ILN_2039 | ||
| 912 | |a GBV_ILN_2044 | ||
| 912 | |a GBV_ILN_2048 | ||
| 912 | |a GBV_ILN_2049 | ||
| 912 | |a GBV_ILN_2050 | ||
| 912 | |a GBV_ILN_2055 | ||
| 912 | |a GBV_ILN_2057 | ||
| 912 | |a GBV_ILN_2059 | ||
| 912 | |a GBV_ILN_2061 | ||
| 912 | |a GBV_ILN_2064 | ||
| 912 | |a GBV_ILN_2065 | ||
| 912 | |a GBV_ILN_2068 | ||
| 912 | |a GBV_ILN_2070 | ||
| 912 | |a GBV_ILN_2086 | ||
| 912 | |a GBV_ILN_2088 | ||
| 912 | |a GBV_ILN_2093 | ||
| 912 | |a GBV_ILN_2106 | ||
| 912 | |a GBV_ILN_2107 | ||
| 912 | |a GBV_ILN_2108 | ||
| 912 | |a GBV_ILN_2110 | ||
| 912 | |a GBV_ILN_2111 | ||
| 912 | |a GBV_ILN_2112 | ||
| 912 | |a GBV_ILN_2113 | ||
| 912 | |a GBV_ILN_2116 | ||
| 912 | |a GBV_ILN_2118 | ||
| 912 | |a GBV_ILN_2119 | ||
| 912 | |a GBV_ILN_2122 | ||
| 912 | |a GBV_ILN_2129 | ||
| 912 | |a GBV_ILN_2143 | ||
| 912 | |a GBV_ILN_2144 | ||
| 912 | |a GBV_ILN_2147 | ||
| 912 | |a GBV_ILN_2148 | ||
| 912 | |a GBV_ILN_2152 | ||
| 912 | |a GBV_ILN_2153 | ||
| 912 | |a GBV_ILN_2188 | ||
| 912 | |a GBV_ILN_2190 | ||
| 912 | |a GBV_ILN_2232 | ||
| 912 | |a GBV_ILN_2336 | ||
| 912 | |a GBV_ILN_2446 | ||
| 912 | |a GBV_ILN_2470 | ||
| 912 | |a GBV_ILN_2472 | ||
| 912 | |a GBV_ILN_2507 | ||
| 912 | |a GBV_ILN_2522 | ||
| 912 | |a GBV_ILN_2548 | ||
| 912 | |a GBV_ILN_4012 | ||
| 912 | |a GBV_ILN_4035 | ||
| 912 | |a GBV_ILN_4037 | ||
| 912 | |a GBV_ILN_4046 | ||
| 912 | |a GBV_ILN_4112 | ||
| 912 | |a GBV_ILN_4125 | ||
| 912 | |a GBV_ILN_4126 | ||
| 912 | |a GBV_ILN_4242 | ||
| 912 | |a GBV_ILN_4246 | ||
| 912 | |a GBV_ILN_4249 | ||
| 912 | |a GBV_ILN_4251 | ||
| 912 | |a GBV_ILN_4305 | ||
| 912 | |a GBV_ILN_4306 | ||
| 912 | |a GBV_ILN_4307 | ||
| 912 | |a GBV_ILN_4313 | ||
| 912 | |a GBV_ILN_4322 | ||
| 912 | |a GBV_ILN_4323 | ||
| 912 | |a GBV_ILN_4324 | ||
| 912 | |a GBV_ILN_4325 | ||
| 912 | |a GBV_ILN_4326 | ||
| 912 | |a GBV_ILN_4328 | ||
| 912 | |a GBV_ILN_4333 | ||
| 912 | |a GBV_ILN_4334 | ||
| 912 | |a GBV_ILN_4335 | ||
| 912 | |a GBV_ILN_4336 | ||
| 912 | |a GBV_ILN_4338 | ||
| 912 | |a GBV_ILN_4393 | ||
| 912 | |a GBV_ILN_4700 | ||
| 936 | b | k | |a 54.00 |q ASE |
| 951 | |a AR | ||
| 952 | |d 48 |j 2007 |e 4 |b 13 |c 07 |h 303-327 | ||
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2007 |
| allfields |
10.1007/s00453-007-0178-0 doi (DE-627)SPR006167403 (SPR)s00453-007-0178-0-e DE-627 ger DE-627 rakwb eng 004 ASE 510 004 ASE 54.00 bkl Shehu, Amarda verfasserin aut Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales. Polypeptide Chain (dpeaa)DE-He213 Inverse Kinematic (dpeaa)DE-He213 Energy Landscape (dpeaa)DE-He213 Kinematic Chain (dpeaa)DE-He213 Kinematic Constraint (dpeaa)DE-He213 Clementi, Cecilia verfasserin aut Kavraki, Lydia E. verfasserin aut Enthalten in Algorithmica New York, NY : Springer, 1986 48(2007), 4 vom: 13. Juli, Seite 303-327 (DE-627)253389704 (DE-600)1458414-1 1432-0541 nnns volume:48 year:2007 number:4 day:13 month:07 pages:303-327 https://dx.doi.org/10.1007/s00453-007-0178-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 48 2007 4 13 07 303-327 |
| spelling |
10.1007/s00453-007-0178-0 doi (DE-627)SPR006167403 (SPR)s00453-007-0178-0-e DE-627 ger DE-627 rakwb eng 004 ASE 510 004 ASE 54.00 bkl Shehu, Amarda verfasserin aut Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales. Polypeptide Chain (dpeaa)DE-He213 Inverse Kinematic (dpeaa)DE-He213 Energy Landscape (dpeaa)DE-He213 Kinematic Chain (dpeaa)DE-He213 Kinematic Constraint (dpeaa)DE-He213 Clementi, Cecilia verfasserin aut Kavraki, Lydia E. verfasserin aut Enthalten in Algorithmica New York, NY : Springer, 1986 48(2007), 4 vom: 13. Juli, Seite 303-327 (DE-627)253389704 (DE-600)1458414-1 1432-0541 nnns volume:48 year:2007 number:4 day:13 month:07 pages:303-327 https://dx.doi.org/10.1007/s00453-007-0178-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 48 2007 4 13 07 303-327 |
| allfields_unstemmed |
10.1007/s00453-007-0178-0 doi (DE-627)SPR006167403 (SPR)s00453-007-0178-0-e DE-627 ger DE-627 rakwb eng 004 ASE 510 004 ASE 54.00 bkl Shehu, Amarda verfasserin aut Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales. Polypeptide Chain (dpeaa)DE-He213 Inverse Kinematic (dpeaa)DE-He213 Energy Landscape (dpeaa)DE-He213 Kinematic Chain (dpeaa)DE-He213 Kinematic Constraint (dpeaa)DE-He213 Clementi, Cecilia verfasserin aut Kavraki, Lydia E. verfasserin aut Enthalten in Algorithmica New York, NY : Springer, 1986 48(2007), 4 vom: 13. Juli, Seite 303-327 (DE-627)253389704 (DE-600)1458414-1 1432-0541 nnns volume:48 year:2007 number:4 day:13 month:07 pages:303-327 https://dx.doi.org/10.1007/s00453-007-0178-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 48 2007 4 13 07 303-327 |
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10.1007/s00453-007-0178-0 doi (DE-627)SPR006167403 (SPR)s00453-007-0178-0-e DE-627 ger DE-627 rakwb eng 004 ASE 510 004 ASE 54.00 bkl Shehu, Amarda verfasserin aut Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales. Polypeptide Chain (dpeaa)DE-He213 Inverse Kinematic (dpeaa)DE-He213 Energy Landscape (dpeaa)DE-He213 Kinematic Chain (dpeaa)DE-He213 Kinematic Constraint (dpeaa)DE-He213 Clementi, Cecilia verfasserin aut Kavraki, Lydia E. verfasserin aut Enthalten in Algorithmica New York, NY : Springer, 1986 48(2007), 4 vom: 13. Juli, Seite 303-327 (DE-627)253389704 (DE-600)1458414-1 1432-0541 nnns volume:48 year:2007 number:4 day:13 month:07 pages:303-327 https://dx.doi.org/10.1007/s00453-007-0178-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 48 2007 4 13 07 303-327 |
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10.1007/s00453-007-0178-0 doi (DE-627)SPR006167403 (SPR)s00453-007-0178-0-e DE-627 ger DE-627 rakwb eng 004 ASE 510 004 ASE 54.00 bkl Shehu, Amarda verfasserin aut Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales. Polypeptide Chain (dpeaa)DE-He213 Inverse Kinematic (dpeaa)DE-He213 Energy Landscape (dpeaa)DE-He213 Kinematic Chain (dpeaa)DE-He213 Kinematic Constraint (dpeaa)DE-He213 Clementi, Cecilia verfasserin aut Kavraki, Lydia E. verfasserin aut Enthalten in Algorithmica New York, NY : Springer, 1986 48(2007), 4 vom: 13. Juli, Seite 303-327 (DE-627)253389704 (DE-600)1458414-1 1432-0541 nnns volume:48 year:2007 number:4 day:13 month:07 pages:303-327 https://dx.doi.org/10.1007/s00453-007-0178-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.00 ASE AR 48 2007 4 13 07 303-327 |
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Enthalten in Algorithmica 48(2007), 4 vom: 13. Juli, Seite 303-327 volume:48 year:2007 number:4 day:13 month:07 pages:303-327 |
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Polypeptide Chain Inverse Kinematic Energy Landscape Kinematic Chain Kinematic Constraint |
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Algorithmica |
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Shehu, Amarda @@aut@@ Clementi, Cecilia @@aut@@ Kavraki, Lydia E. @@aut@@ |
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2007-07-13T00:00:00Z |
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Shehu, Amarda |
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Shehu, Amarda ddc 004 ddc 510 bkl 54.00 misc Polypeptide Chain misc Inverse Kinematic misc Energy Landscape misc Kinematic Chain misc Kinematic Constraint Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins |
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004 ASE 510 004 ASE 54.00 bkl Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins Polypeptide Chain (dpeaa)DE-He213 Inverse Kinematic (dpeaa)DE-He213 Energy Landscape (dpeaa)DE-He213 Kinematic Chain (dpeaa)DE-He213 Kinematic Constraint (dpeaa)DE-He213 |
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ddc 004 ddc 510 bkl 54.00 misc Polypeptide Chain misc Inverse Kinematic misc Energy Landscape misc Kinematic Chain misc Kinematic Constraint |
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ddc 004 ddc 510 bkl 54.00 misc Polypeptide Chain misc Inverse Kinematic misc Energy Landscape misc Kinematic Chain misc Kinematic Constraint |
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Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins |
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Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins |
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Shehu, Amarda Clementi, Cecilia Kavraki, Lydia E. |
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sampling conformation space to model equilibrium fluctuations in proteins |
| title_auth |
Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins |
| abstract |
Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales. |
| abstractGer |
Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales. |
| abstract_unstemmed |
Abstract This paper proposes the Protein Ensemble Method (PEM) to model equilibrium fluctuations in proteins where fragments of the protein polypeptide chain can move independently of one another. PEM models global equilibrium fluctuations of a polypeptide chain by combining local fluctuations of consecutive overlapping fragments of the chain. Local fluctuations are computed by a probabilistic exploration that exploits analogies between proteins and robots. All generated conformations are subjected to energy minimization and then are weighted according to a Boltzmann distribution. Using the theory of statistical mechanics the Boltzmann-weighted fluctuations corresponding to each fragment are combined to obtain fluctuations for the entire protein. The agreement obtained between PEM-modeled fluctuations, wet-lab experiment and guided simulation measurements, indicates that PEM is able to reproduce with high accuracy protein equilibrium fluctuations that occur over a broad range of timescales. |
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4 |
| title_short |
Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins |
| url |
https://dx.doi.org/10.1007/s00453-007-0178-0 |
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true |
| author2 |
Clementi, Cecilia Kavraki, Lydia E. |
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Clementi, Cecilia Kavraki, Lydia E. |
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| doi_str |
10.1007/s00453-007-0178-0 |
| up_date |
2024-07-03T21:17:56.126Z |
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| score |
7.3991566 |