Extension of the pairwise-contact energy parameters for proteins with the local environments of amino acids

2005 ◽  
Vol 351 (2-4) ◽  
pp. 439-447 ◽  
Author(s):  
Muyoung Heo ◽  
Mookyung Cheon ◽  
Eun-Joung Moon ◽  
Suhkmann Kim ◽  
Kwanghoon Chung ◽  
...  
Keyword(s):  
Amino Acids ◽  
Energy Parameters ◽  
Local Environments

Inference of the solvation energy parameters of amino acids using maximum entropy approach

2008 ◽  
Vol 129 (3) ◽  
pp. 035102 ◽  
Author(s):  
Trinh X. Hoang ◽  
Flavio Seno ◽  
Antonio Trovato ◽  
Jayanth R. Banavar ◽  
Amos Maritan
Keyword(s):  
Amino Acids ◽  
Maximum Entropy ◽  
Solvation Energy ◽  
Energy Parameters

Development of CHARMM Additive Potential Energy Parameters for α-Methyl Amino Acids

2021 ◽  
Author(s):  
Anthony J. Pane ◽  
Wenbo Yu ◽  
Asaminew Aytenfisu ◽  
Jude Tunyi ◽  
Richard M. Venable ◽  
...  
Keyword(s):  
Amino Acids ◽  
Potential Energy ◽  
Energy Parameters

scholarly journals Calculation and Comparison of Energy Interaction and Intensity Parameters for the Interaction of Nd(III) with DL-Valine, DL-Alanine and β-Alanine in Presence and Absence of Ca2+/Zn2+ in Aqueous and Different Aquated Organic Solvents Using 4f-4f Transition Spectra as Probe

2009 ◽  
Vol 2009 ◽  
pp. 1-9 ◽  
Author(s):  
H. Debecca Devi ◽  
Ch. Sumitra ◽  
Th. David Singh ◽  
N. Yaiphaba ◽  
N. Mohondas Singh ◽  
...  
Keyword(s):  
Amino Acids ◽  
Oscillator Strength ◽  
Organic Solvents ◽  
Electric Dipole ◽  
Spectral Energy ◽  
Ligand Interaction ◽  
Energy Parameters ◽  
Energy Interaction ◽  
Intensity Parameters ◽  
Presence And Absence

Absorption difference and comparative absorption spectrophotometric studies involving 4f-4f transitions of Nd(III) and different amino acids: DL-valine, DL-alanine, and β-alanine in presence and absence of Ca(II) and Zn(II) in aqueous and different aquated organic solvents have been carried out. Variations in the spectral energy parameters: Slater-Condon (FK) factor, Racah (EK), Lande factor (ξ4f), nephelauxetic ratio (β), bonding (b1/2), percentage covalency (δ) are calculated to explore the mode of interaction of Nd(III) with different amino acids: DL-valine, DL-alanine, and β-alanine. The values of experimentally calculated oscillator strength (P) and computed values of Judd-Ofelt electric dipole intensity parameters, Tλ (λ = 2,4,6), are also determined for different 4f-4f transitions. The variation in the values of P and Tλ parameters explicitly shows the relative sensitivities of the 4f-4f transitions as well as the specific correlation between relative intensities, ligand structures, and nature of Nd(III)-ligand interaction.

scholarly journals Beyond stability constraints: a biophysical model of enzyme evolution with selection for stability and activity

2018 ◽  
Author(s):  
Julian Echave
Keyword(s):  
Amino Acids ◽  
Packing Density ◽  
Solvent Accessibility ◽  
Enzyme Evolution ◽  
Biophysical Model ◽  
Solvent Exposure ◽  
Local Environments ◽  
Distance Dependence ◽  
Selection For ◽  
Functionally Diverse

AbstractProteins trace trajectories in sequence space as their amino acids become substituted by other amino acids. The number of substitutions per unit time, the rate of evolution, varies among sites because of biophysical constraints. Several properties that characterize sites’ local environments have been proposed as biophysical determinants of site-specific evolutionary rates. Thus, rate increases with increasing solvent exposure, increasing flexibility, and decreasing local packing density. For enzymes, rate increases also with increasing distance from the protein’s active residues, presumably due to functional constraints. The dependence of rates on solvent accessibility, packing density, and flexibility has been mechanistically explained in terms of selection for stability. However, as I show here, a stability-based model fails to reproduce the observed rate-distance dependence, overestimating rates close to the active residues and underestimating rates of distant sites. Here, I pose a new biophysical model of enzyme evolution with selection for stability and activity (MSA) and compare it with a stability-based counterpart (MS). Testing these models on a structurally and functionally diverse dataset of monomeric enzymes, I found that MSA fits observed rates better than MS for most proteins. While both models reproduce the observed dependence of rates on solvent accessibility, packing, and flexibility, MSA fits these dependencies somewhat better. Importantly, while MS fails to reproduce the dependence of rates on distance from the active residues, MSA accounts for the rate-distance dependence quantitatively. Thus, the variation of evolutionary rate among enzyme sites is mechanistically underpinned by natural selection for both stability and activity.

scholarly journals Probing Local Environments of Adenylate Kinase with Unnatural Amino Acids

2020 ◽  
Vol 118 (3) ◽  
pp. 39a
Author(s):  
Angelica Camilo ◽  
Scott H. Brewer ◽  
Christine M. Phillips-Piro
Keyword(s):  
Amino Acids ◽  
Adenylate Kinase ◽  
Unnatural Amino Acids ◽  
Local Environments

CLASSIFICATIONS OF AMINO ACIDS IN PROTEINS BY THE SELF-ORGANIZING MAP

2005 ◽  
Vol 16 (10) ◽  
pp. 1609-1616 ◽  
Author(s):  
MOOKYUNG CHEON ◽  
MUYOUNG HEO ◽  
IKSOO CHANG ◽  
CHOONGRAK KIM
Keyword(s):  
Amino Acids ◽  
Secondary Structure ◽  
Protein Structures ◽  
Building Blocks ◽  
Side Chain ◽  
Self Organizing Map ◽  
Energy Parameters ◽  
Physico Chemical ◽  
Body Energy ◽  
Self Organizing

We present the clustering properties of amino acids, which are building blocks of proteins, according to their physico-chemical characters. To classify the 20 kinds of amino acids, we employ a Self-Organizing Map (SOM) analysis for the Miyazawa-Jernigan (MJ) pairwise-contact matrix, the Environment-dependent One-body energy Parameters (EOP) and the one-body energy parameters incorporating the Ramachandran angle information (EOPR) over the EOP in proteins. We provide the new result of the SOM clustering for amino acids based on the EOPR and compare that with those from the MJ and the EOP matrix. All three kinds of energy parameters capture the leading role played by the hydrophobicity and the hydrophilicity of amino acids in protein folding. Our SOM analysis generally illustrates that both the EOP and the EOPR can provide the collective clustering of amino acids by the side chain characteristics and the secondary structure information. However, EOP is better at classifying amino acids according to their side chain characteristics whereas EOPR is better with secondary structure. We show that the EOP and the EOPR matrix manifests more detailed physico-chemical classification of amino acids than those from the MJ matrix, which does not contain a local environmental information of amino acids in the protein structures.

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