Force Field Modeling of Amino Acid Conformational Energies

2007 ◽  
Vol 3 (5) ◽  
pp. 1774-1788 ◽  
Author(s):  
Jakub Kaminský ◽  
Frank Jensen
Keyword(s):  
Amino Acid ◽  
Force Field ◽  
Field Modeling ◽  
Conformational Energies

Force field modeling of conformational energies: Importance of multipole moments and intramolecular polarization

2007 ◽  
Vol 107 (6) ◽  
pp. 1390-1395 ◽  
Author(s):  
Thomas D. Rasmussen ◽  
Pengyu Ren ◽  
Jay W. Ponder ◽  
Frank Jensen
Keyword(s):  
Force Field ◽  
Multipole Moments ◽  
Field Modeling ◽  
Conformational Energies

Statistical Force-Field for Structural Modeling Using Chemical Cross-Linking/mass Spectrometry Distance Constraints

2018 ◽  
Author(s):  
Allan J. R. Ferrari ◽  
Fabio C. Gozzo ◽  
Leandro Martinez
Keyword(s):  
Mass Spectrometry ◽  
Amino Acid ◽  
Force Field ◽  
Protein Structures ◽  
Protein Structure Determination ◽  
Structural Modeling ◽  
Cross Linking ◽  
Amino Acid Residues ◽  
Distance Constraints ◽  
Chemical Cross Linking

<div><p>Chemical cross-linking/Mass Spectrometry (XLMS) is an experimental method to obtain distance constraints between amino acid residues, which can be applied to structural modeling of tertiary and quaternary biomolecular structures. These constraints provide, in principle, only upper limits to the distance between amino acid residues along the surface of the biomolecule. In practice, attempts to use of XLMS constraints for tertiary protein structure determination have not been widely successful. This indicates the need of specifically designed strategies for the representation of these constraints within modeling algorithms. Here, a force-field designed to represent XLMS-derived constraints is proposed. The potential energy functions are obtained by computing, in the database of known protein structures, the probability of satisfaction of a topological cross-linking distance as a function of the Euclidean distance between amino acid residues. The force-field can be easily incorporated into current modeling methods and software. In this work, the force-field was implemented within the Rosetta ab initio relax protocol. We show a significant improvement in the quality of the models obtained relative to current strategies for constraint representation. This force-field contributes to the long-desired goal of obtaining the tertiary structures of proteins using XLMS data. Force-field parameters and usage instructions are freely available at http://m3g.iqm.unicamp.br/topolink/xlff <br></p></div><p></p><p></p>

scholarly journals New CHARMM force field parameters for dehydrated amino acid residues, the key to lantibiotic molecular dynamics simulations

RSC Advances ◽  
2014 ◽  
Vol 4 (89) ◽  
pp. 48621-48631 ◽  
Author(s):  
Eleanor R. Turpin ◽  
Sam Mulholland ◽  
Andrew M. Teale ◽  
Boyan B. Bonev ◽  
Jonathan D. Hirst
Keyword(s):  
Molecular Dynamics ◽  
Amino Acid ◽  
Force Field ◽  
Molecular Dynamics Simulations ◽  
Amino Acid Residues ◽  
Charmm Force Field ◽  
Force Field Parameters ◽  
Dynamics Simulations

Evaluating the Effects of Geometry and Charge Flux in Force Field Modeling

2018 ◽  
Vol 122 (19) ◽  
pp. 4647-4653 ◽  
Author(s):  
Elaheh Sedghamiz ◽  
Farhad Ghalami
Keyword(s):  
Force Field ◽  
Field Modeling ◽  
Charge Flux

scholarly journals Adsorption of Amino Acids on Graphene: Assessment of Current Force Fields

2019 ◽  
Author(s):  
Siva Dasetty ◽  
John K. Barrows ◽  
Sapna Sarupria
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Force Field ◽  
Force Fields ◽  
Principal Component ◽  
Free Energies ◽  
Adsorbed State ◽  
Free Energy Of Adsorption ◽  
Density Based Clustering ◽  
Structural Preferences

<div> <div> <div> <p>We compare the free energies of adsorption (∆Aads) and the structural preferences of amino acids obtained using the force fields — Amberff99SB-ILDN/TIP3P, CHARMM36/modified-TIP3P, OPLS-AA/M/TIP3P, and Amber03w/TIP4P/2005. The amino acid–graphene interactions are favorable irrespective of the force field. While the magnitudes of ∆Aads differ between the force fields, the trends in the free energy of adsorption with amino acids are similar across the studied force fields. ∆Aads positively correlates with amino acid–graphene and negatively correlates with graphene–water interaction energies. Using a combination of principal component analysis and density-based clustering technique, we grouped the structures observed in the graphene adsorbed state. The resulting population of clusters, and the conformation in each cluster indicate that the structures of the amino acid in the graphene adsorbed state vary across force fields. The differences in the conformations of amino acids are more severe in the graphene adsorbed state compared to the bulk state for all the force fields. Our findings suggest that while the thermodynamics of adsorption of proteins and peptides would be described consistently across different force fields, the structural preferences of peptides and proteins on graphene will be force field dependent. </p> </div> </div> </div>

Force Field Modelling of Conformational Energies

2004 ◽  
Vol 30 (11-12) ◽  
pp. 801-806 ◽  
Author(s):  
Thomas D. Rasmussen ◽  
Frank Jensen
Keyword(s):  
Force Field ◽  
Field Modelling ◽  
Conformational Energies
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