scholarly journals Assessing backbone solvation effects in the conformational propensities of amino acid residues in unfolded peptides

2015 ◽  
Vol 17 (38) ◽  
pp. 24917-24924 ◽  
Author(s):  
Niranjan V. Ilawe ◽  
Alexandra E. Raeber ◽  
Reinhard Schweitzer-Stenner ◽  
Siobhan E. Toal ◽  
Bryan M. Wong
Keyword(s):  
Amino Acid ◽  
Amino Acid Residues ◽  
Solvation Effects ◽  
Self Energy ◽  
Polyproline Ii ◽  
Water Water Water

Large energetic contributions to the stabilization of polyproline II result from peptide–water, water–water interactions, and changes of the solvent self-energy.

scholarly journals Glycine in Water Favors the Polyproline II State

Biomolecules ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1121 ◽  
Author(s):  
Brian Andrews ◽  
Shuting Zhang ◽  
Reinhard Schweitzer-Stenner ◽  
Brigita Urbanc
Keyword(s):  
Amino Acid ◽  
Spectroscopic Data ◽  
Heavy Atom ◽  
Conformational Space ◽  
Side Chain ◽  
Amino Acid Residues ◽  
Glycine Residue ◽  
Polyproline Ii ◽  
Conformational Preferences ◽  
Central Residue

Conformational preferences of amino acid residues in water are determined by the backbone and side-chain properties. Alanine is known for its high polyproline II (pPII) propensity. The question of relative contributions of the backbone and side chain to the conformational preferences of alanine and other amino acid residues in water is not fully resolved. Because glycine lacks a heavy-atom side chain, glycine-based peptides can be used to examine to which extent the backbone properties affect the conformational space. Here, we use published spectroscopic data for the central glycine residue of cationic triglycine in water to demonstrate that its conformational space is dominated by the pPII state. We assess three commonly used molecular dynamics (MD) force fields with respect to their ability to capture the conformational preferences of the central glycine residue in triglycine. We show that pPII is the mesostate that enables the functional backbone groups of the central residue to form the most hydrogen bonds with water. Our results indicate that the pPII propensity of the central glycine in GGG is comparable to that of alanine in GAG, implying that the water-backbone hydrogen bonding is responsible for the high pPII content of these residues.

Substrate Recognition by Vitamin K-Dependent Carboxylase

1987 ◽  
Vol 57 (01) ◽  
pp. 017-019 ◽  
Author(s):  
Magda M W Ulrich ◽  
Berry A M Soute ◽  
L Johan M van Haarlem ◽  
Cees Vermeer
Keyword(s):  
Amino Acid ◽  
Vitamin K ◽  
Substrate Recognition ◽  
Bovine Liver ◽  
Amino Acid Residues

SummaryDecarboxylated osteocalcins were prepared and purified from bovine, chicken, human and monkey bones and assayed for their ability to serve as a substrate for vitamin K-dependent carboxylase from bovine liver. Substantial differences were observed, especially between bovine and monkey d-osteocalcin. Since these substrates differ only in their amino acid residues 3 and 4, it seems that these residues play a role in the recognition of a substrate by hepatic carboxylase.

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>

Sign in / Sign up

Export Citation Format

Share Document