Book Chapter10.1016/S1043-9471(05)80049-7
[19] Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptors
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TL;DR: This chapter discusses the integrated methods for the construction of three-dimensional models and computational probing of structure–function relations in G protein-coupled receptors (GPCR) and expects increased rate of success achieved by molecular modeling and computational simulation methods in providing structural insights relevant to the functions of biological molecules.
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Abstract: Publisher Summary This chapter discusses the integrated methods for the construction of three-dimensional models and computational probing of structure–function relations in G protein-coupled receptors (GPCR). The rapid pace of cloning and expression of G protein-coupled receptors offers attractive opportunities to probe the structural basis of signal transduction mechanisms at the level of these cell-surface receptors. Major insights have emerged from comparisons and classifications of the amino acid sequences of GPCRs into families defined by evolutionary developments and adapted to perform selective functions. Structural data on GPCRs, based on biochemical, immunological, and biophysical approaches have validated consensus architecture of GPCRs with an extracellular N-terminus, a cytoplasmic C-terminus, and a transmembrane portion comprised of seven-transmembrane helical domains connected by loops. Developments in the molecular modeling and computational exploration of GPCR proteins indicate a tantalizing potential to alleviate some of these difficulties. These expectations are based on the increased rate of success achieved by molecular modeling and computational simulation methods in providing structural insights relevant to the functions of biological molecules.
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References
A simple method for displaying the hydropathic character of a protein
Jack Kyte,Russell F. Doolittle +1 more
TL;DR: A computer program that progressively evaluates the hydrophilicity and hydrophobicity of a protein along its amino acid sequence has been devised and its simplicity and its graphic nature make it a very useful tool for the evaluation of protein structures.
23.9K
Prediction of protein secondary structure at better than 70% accuracy.
Burkhard Rost,Chris Sander +1 more
TL;DR: A two-layered feed-forward neural network is trained on a non-redundant data base to predict the secondary structure of water-soluble proteins with a new key aspect is the use of evolutionary information in the form of multiple sequence alignments that are used as input in place of single sequences.
3.1K
Model for the structure of bacteriorhodopsin based on high-resolution electron cryo-microscopy.
TL;DR: A complete atomic model for bacteriorhodopsin between amino acid residues 8 and 225 has been built and suggests that pK changes in the Schiff base must act as the means by which light energy is converted into proton pumping pressure in the channel.
3K
The relation between the divergence of sequence and structure in proteins.
Cyrus Chothia,Arthur M. Lesk +1 more
TL;DR: The root mean square deviation in the positions of the main chain atoms, delta, is related to the fraction of mutated residues, H, by the expression: delta(A) = 0.40 e1.87H.
Analysis of membrane and surface protein sequences with the hydrophobic moment plot.
TL;DR: An algorithm has been developed which identifies alpha-helices involved in the interactions of membrane proteins with lipid bilayers and which distinguishes them from helices in soluble proteins, and suggests four transmembrane helices and a surface-seeking helix in fragment B, the moiety known to have trans Membrane function.
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