A Monte Carlo method for conformational analysis of saccharides

Thomas Peters; Bernd Meyer; Rainer Stuike-Prill; Ray Somorjai; Jean Robert Brisson

doi:10.1016/0008-6215(93)87005-D

A Monte Carlo method for conformational analysis of saccharides

Thomas Peters^*, Bernd Meyer, Rainer Stuike-Prill, Ray Somorjai, Jean Robert Brisson

^*Korrespondierende/r Autor/-in für diese Arbeit

Institut für Chemie und Metabolomics

124 Zitate (Scopus)

Abstract

A Metropolis Monte Carlo (MMC) algorithm was applied to explore conformational spaces spanned by the exocyclic dihedral angles of four disaccharides α-d-Man(1 → 3)α-d-Man(1 → O)Me (1), α-d-Man(1 → 2)-α-d-Man(1 → O)Me (2), methyl β-cellobioside (3), and methyl β-maltoside (4). The simulation method uses the HSEA force field and randomly samples the conformational space with an automatic preference for low-energy states. In comparison to a systematic grid search, MMC offers a much more convenient and efficient protocol for the computation of ensemble average values of experimentally accessible NMR parameters such as NOE effects or ³J coupling constants. Energy barriers of a few kcal/mol were found to be surmounted easily when running the simulations with the temperature parameter set at room temperature, whereas passing significantly higher barriers required elevated temperature parameters. Ensemble average NOE values were calculated using the MMC technique and a conventional systematic grid search showing that the MMC method adequately samples the conformational spaces of 1-4. Theoretical NOEs derived for global or local minimum conformations are different from ensemble average values, and it is shown that averaged NOEs agree significantly better with experimental data. Ensemble average NOEs for 1 derived from MMC/HSEA, and previously reported MM2CARB and AMBER calculations all showed good agreement with experimental data, with MMC/HSEA giving the closest fit.

Originalsprache	Englisch
Zeitschrift	Carbohydrate Research
Jahrgang	238
Ausgabenummer	C
Seiten (von - bis)	49-73
Seitenumfang	25
ISSN	0008-6215
DOIs	https://doi.org/10.1016/0008-6215(93)87005-D
Publikationsstatus	Veröffentlicht - 15.01.1993

Fördermittel

The collaboration between T.P. and J.R.B. was financed by a NATO research grant CRG.890356. T.P. thanks the Deutsche Forschungsgemeinschaftf or a grant within the Sonderforschungsbereich 169. This work was supported in part by grants’ from the National Institutes of Health (l-P41-RR05351-01) and the advanced computational methods center of the University of Georgia (to R.S.P. and B.M.). We wish to thank Professor Klaus Bock for generous hospitality at the Carlsberg Laboratory, Copenhagen, and for discussionso f the simulation method described. We also appreciate the continuous encouragement of Dr. David Bundle, National Research Council of Canada, who accompanied the project at all stages of its development_ Professor Heinz Riiterjans, Institute of Biophysical Chemistry, University of Frankfurt, is thanked for providing access to the computing facilities in his laboratory.

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10.1016/0008-6215(93)87005-D

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title = "A Monte Carlo method for conformational analysis of saccharides",

abstract = "A Metropolis Monte Carlo (MMC) algorithm was applied to explore conformational spaces spanned by the exocyclic dihedral angles of four disaccharides α-d-Man(1 → 3)α-d-Man(1 → O)Me (1), α-d-Man(1 → 2)-α-d-Man(1 → O)Me (2), methyl β-cellobioside (3), and methyl β-maltoside (4). The simulation method uses the HSEA force field and randomly samples the conformational space with an automatic preference for low-energy states. In comparison to a systematic grid search, MMC offers a much more convenient and efficient protocol for the computation of ensemble average values of experimentally accessible NMR parameters such as NOE effects or 3J coupling constants. Energy barriers of a few kcal/mol were found to be surmounted easily when running the simulations with the temperature parameter set at room temperature, whereas passing significantly higher barriers required elevated temperature parameters. Ensemble average NOE values were calculated using the MMC technique and a conventional systematic grid search showing that the MMC method adequately samples the conformational spaces of 1-4. Theoretical NOEs derived for global or local minimum conformations are different from ensemble average values, and it is shown that averaged NOEs agree significantly better with experimental data. Ensemble average NOEs for 1 derived from MMC/HSEA, and previously reported MM2CARB and AMBER calculations all showed good agreement with experimental data, with MMC/HSEA giving the closest fit.",

author = "Thomas Peters and Bernd Meyer and Rainer Stuike-Prill and Ray Somorjai and Brisson, \{Jean Robert\}",

note = "Funding Information: The collaboration between T.P. and J.R.B. was financed by a NATO research grant CRG.890356. T.P. thanks the Deutsche Forschungsgemeinschaftf or a grant within the Sonderforschungsbereich 169. This work was supported in part by grants{\textquoteright} from the National Institutes of Health (l-P41-RR05351-01) and the advanced computational methods center of the University of Georgia (to R.S.P. and B.M.). We wish to thank Professor Klaus Bock for generous hospitality at the Carlsberg Laboratory, Copenhagen, and for discussionso f the simulation method described. We also appreciate the continuous encouragement of Dr. David Bundle, National Research Council of Canada, who accompanied the project at all stages of its development\_ Professor Heinz Riiterjans, Institute of Biophysical Chemistry, University of Frankfurt, is thanked for providing access to the computing facilities in his laboratory.",

year = "1993",

month = jan,

day = "15",

doi = "10.1016/0008-6215(93)87005-D",

language = "English",

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T1 - A Monte Carlo method for conformational analysis of saccharides

AU - Peters, Thomas

AU - Meyer, Bernd

AU - Stuike-Prill, Rainer

AU - Somorjai, Ray

AU - Brisson, Jean Robert

N1 - Funding Information: The collaboration between T.P. and J.R.B. was financed by a NATO research grant CRG.890356. T.P. thanks the Deutsche Forschungsgemeinschaftf or a grant within the Sonderforschungsbereich 169. This work was supported in part by grants’ from the National Institutes of Health (l-P41-RR05351-01) and the advanced computational methods center of the University of Georgia (to R.S.P. and B.M.). We wish to thank Professor Klaus Bock for generous hospitality at the Carlsberg Laboratory, Copenhagen, and for discussionso f the simulation method described. We also appreciate the continuous encouragement of Dr. David Bundle, National Research Council of Canada, who accompanied the project at all stages of its development_ Professor Heinz Riiterjans, Institute of Biophysical Chemistry, University of Frankfurt, is thanked for providing access to the computing facilities in his laboratory.

PY - 1993/1/15

Y1 - 1993/1/15

N2 - A Metropolis Monte Carlo (MMC) algorithm was applied to explore conformational spaces spanned by the exocyclic dihedral angles of four disaccharides α-d-Man(1 → 3)α-d-Man(1 → O)Me (1), α-d-Man(1 → 2)-α-d-Man(1 → O)Me (2), methyl β-cellobioside (3), and methyl β-maltoside (4). The simulation method uses the HSEA force field and randomly samples the conformational space with an automatic preference for low-energy states. In comparison to a systematic grid search, MMC offers a much more convenient and efficient protocol for the computation of ensemble average values of experimentally accessible NMR parameters such as NOE effects or 3J coupling constants. Energy barriers of a few kcal/mol were found to be surmounted easily when running the simulations with the temperature parameter set at room temperature, whereas passing significantly higher barriers required elevated temperature parameters. Ensemble average NOE values were calculated using the MMC technique and a conventional systematic grid search showing that the MMC method adequately samples the conformational spaces of 1-4. Theoretical NOEs derived for global or local minimum conformations are different from ensemble average values, and it is shown that averaged NOEs agree significantly better with experimental data. Ensemble average NOEs for 1 derived from MMC/HSEA, and previously reported MM2CARB and AMBER calculations all showed good agreement with experimental data, with MMC/HSEA giving the closest fit.

AB - A Metropolis Monte Carlo (MMC) algorithm was applied to explore conformational spaces spanned by the exocyclic dihedral angles of four disaccharides α-d-Man(1 → 3)α-d-Man(1 → O)Me (1), α-d-Man(1 → 2)-α-d-Man(1 → O)Me (2), methyl β-cellobioside (3), and methyl β-maltoside (4). The simulation method uses the HSEA force field and randomly samples the conformational space with an automatic preference for low-energy states. In comparison to a systematic grid search, MMC offers a much more convenient and efficient protocol for the computation of ensemble average values of experimentally accessible NMR parameters such as NOE effects or 3J coupling constants. Energy barriers of a few kcal/mol were found to be surmounted easily when running the simulations with the temperature parameter set at room temperature, whereas passing significantly higher barriers required elevated temperature parameters. Ensemble average NOE values were calculated using the MMC technique and a conventional systematic grid search showing that the MMC method adequately samples the conformational spaces of 1-4. Theoretical NOEs derived for global or local minimum conformations are different from ensemble average values, and it is shown that averaged NOEs agree significantly better with experimental data. Ensemble average NOEs for 1 derived from MMC/HSEA, and previously reported MM2CARB and AMBER calculations all showed good agreement with experimental data, with MMC/HSEA giving the closest fit.

UR - https://www.scopus.com/pages/publications/0027511368

U2 - 10.1016/0008-6215(93)87005-D

DO - 10.1016/0008-6215(93)87005-D

M3 - Journal articles

C2 - 8431939

AN - SCOPUS:0027511368

SN - 0008-6215

VL - 238

SP - 49

EP - 73

JO - Carbohydrate Research

JF - Carbohydrate Research

IS - C

ER -

A Monte Carlo method for conformational analysis of saccharides

Abstract

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