Artículo
Novel Lennard-Jones Parameters for Cysteine and Selenocysteine in the AMBER Force Field
Pedron, Federico Nicolás
; Messias Da Silva, Andresa
; Zeida, Ari; Roitberg, Adrián E.; Estrin, Dario Ariel
Fecha de publicación:
01/2023
Editorial:
American Chemical Society
Revista:
Journal of Chemical Information and Modeling
ISSN:
1549-9596
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
Cysteine is a common amino acid with a thiol group that plays a pivotal role in a variety of scenarios in redox biochemistry. In contrast, selenocysteine, the 21st amino acid, is only present in 25 human proteins. Classical force-field parameters for cysteine and selenocysteine are still scarce. In this context, we present a methodology to obtain Lennard-Jones parameters for cysteine and selenocysteine in different physiologically relevant oxidation and protonation states. The new force field parameters obtained in this work are available at https://github.com/MALBECC/AMBER-parameters-database. The parameters were adjusted to reproduce water radial distribution functions obtained by density functional theory ab initio molecular dynamics. We validated the results by evaluating the impact of the choice of parameters on the structure and dynamics in classical molecular dynamics simulations of representative proteins containing catalytic cysteine/selenocysteine residues. There are significant changes in protein structure and dynamics depending on the parameters choice, specifically affecting the residues close to the catalytic sites.
Palabras clave:
selenocysteine
,
Lennard Jones parameters
,
Amber force field
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Articulos(INQUIMAE)
Articulos de INST.D/QUIM FIS D/L MATERIALES MEDIOAMB Y ENERGIA
Articulos de INST.D/QUIM FIS D/L MATERIALES MEDIOAMB Y ENERGIA
Citación
Pedron, Federico Nicolás; Messias Da Silva, Andresa; Zeida, Ari; Roitberg, Adrián E.; Estrin, Dario Ariel; Novel Lennard-Jones Parameters for Cysteine and Selenocysteine in the AMBER Force Field; American Chemical Society; Journal of Chemical Information and Modeling; 63; 2; 1-2023; 595-604
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