Internal motions of aromatic amino acid side chains. Selective excitation nuclear relaxation and scalar coupling constant analysis on a model system

1979 ◽  
Vol 83 (25) ◽  
pp. 3249-3251 ◽  
Author(s):  
Neri. Niccolai ◽  
Enzo. Tiezzi
Keyword(s):  
Amino Acid ◽  
Aromatic Amino Acid ◽  
Selective Excitation ◽  
Model System ◽  
Scalar Coupling ◽  
Nuclear Relaxation ◽  
Coupling Constant ◽  
Internal Motions ◽  
Scalar Coupling Constant ◽  
Amino Acid Side Chains

Predicting the Strength of Stacking Interactions Between Heterocycles and Aromatic Amino Acid Side Chains

2019 ◽  
Author(s):  
Andrea N. Bootsma ◽  
Analise C. Doney ◽  
Steven Wheeler
Keyword(s):  
Amino Acid ◽  
Binding Sites ◽  
Aromatic Amino Acid ◽  
Aromatic Amino Acids ◽  
Biologically Active ◽  
Side Chains ◽  
Stacking Interactions ◽  
Inhibitor Binding ◽  
Protein Binding Sites ◽  
Amino Acid Side Chains

<p>Despite the ubiquity of stacking interactions between heterocycles and aromatic amino acids in biological systems, our ability to predict their strength, even qualitatively, is limited. Based on rigorous <i>ab initio</i> data, we have devised a simple predictive model of the strength of stacking interactions between heterocycles commonly found in biologically active molecules and the amino acid side chains Phe, Tyr, and Trp. This model provides rapid predictions of the stacking ability of a given heterocycle based on readily-computed heterocycle descriptors. We show that the values of these descriptors, and therefore the strength of stacking interactions with aromatic amino acid side chains, follow simple predictable trends and can be modulated by changing the number and distribution of heteroatoms within the heterocycle. This provides a simple conceptual model for understanding stacking interactions in protein binding sites and optimizing inhibitor binding in drug design.</p>

The Influence of the Aromatic Amino Acid Side-Chains on the Sign of the Soret Cotton Effect in Chironomus Hemoglobin (CTT III)

1972 ◽  
Vol 27 (5) ◽  
pp. 530-532 ◽  
Author(s):  
Jörg Fleischhauer ◽  
Axel Wollmer
Keyword(s):  
Amino Acid ◽  
Aromatic Amino Acid ◽  
Cotton Effect ◽  
Side Chain ◽  
Side Chains ◽  
Aromatic Side Chain ◽  
Rotational Strength ◽  
Amino Acid Side Chains ◽  
Atomic Coordinates

The origin of the positive Soret Cotton effect of myoglobin was calculated by Hsu and WOODY on the basis of a mechanism taking into account the coupling of the Soret and aromatic side-chain π—π* transitions. HUBER and coworkers have worked out the atomic coordinates of a monomeric insect hemoglobin which exhibits a negative Soret Cotton effect.It seemed of some importance to examine the capability of this mechanism to explain the observed inversion of sign. The calculations resulted indeed in a negative total rotational strength (—0,2 DBM), the main contributions arising from phenylalanine residues.

scholarly journals Scalar Coupling Constant Prediction Using Graph Embedding Local Attention Encoder

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 171100-171111
Author(s):  
Caiqing Jian ◽  
Xinyu Cheng ◽  
Jian Zhang ◽  
Lihui Wang
Keyword(s):  
Graph Embedding ◽  
Scalar Coupling ◽  
Coupling Constant ◽  
Scalar Coupling Constant

scholarly journals 4D APSY-HBCB(CG)CDHD experiment for automated assignment of aromatic amino acid side chains in proteins

2011 ◽  
Vol 51 (3) ◽  
pp. 313-318 ◽  
Author(s):  
Barbara Krähenbühl ◽  
Sebastian Hiller ◽  
Gerhard Wider
Keyword(s):  
Amino Acid ◽  
Aromatic Amino Acid ◽  
Automated Assignment ◽  
Side Chains ◽  
Amino Acid Side Chains

Predicting the Strength of Stacking Interactions Between Heterocycles and Aromatic Amino Acid Side Chains

2019 ◽  
Author(s):  
Andrea N. Bootsma ◽  
Analise C. Doney ◽  
Steven Wheeler
Keyword(s):  
Amino Acid ◽  
Binding Sites ◽  
Aromatic Amino Acid ◽  
Aromatic Amino Acids ◽  
Biologically Active ◽  
Side Chains ◽  
Stacking Interactions ◽  
Inhibitor Binding ◽  
Protein Binding Sites ◽  
Amino Acid Side Chains

<p>Despite the ubiquity of stacking interactions between heterocycles and aromatic amino acids in biological systems, our ability to predict their strength, even qualitatively, is limited. Based on rigorous <i>ab initio</i> data, we have devised a simple predictive model of the strength of stacking interactions between heterocycles commonly found in biologically active molecules and the amino acid side chains Phe, Tyr, and Trp. This model provides rapid predictions of the stacking ability of a given heterocycle based on readily-computed heterocycle descriptors. We show that the values of these descriptors, and therefore the strength of stacking interactions with aromatic amino acid side chains, follow simple predictable trends and can be modulated by changing the number and distribution of heteroatoms within the heterocycle. This provides a simple conceptual model for understanding stacking interactions in protein binding sites and optimizing inhibitor binding in drug design.</p>

Predicting the Strength of Stacking Interactions Between Heterocycles and Aromatic Amino Acid Side Chains

2019 ◽  
Author(s):  
Andrea N. Bootsma ◽  
Analise C. Doney ◽  
Steven Wheeler
Keyword(s):  
Amino Acid ◽  
Predictive Model ◽  
Conceptual Model ◽  
Aromatic Amino Acid ◽  
Side Chains ◽  
Stacking Interactions ◽  
Amino Acid Side Chains

Development of both a quantitative predictive model of stacking interactions of heterocycles with Phe, Tyr, and Trp side chains and a conceptual model to understand and maximize these interactions in the context of design.

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