Structural model of protein

Phil. Trans. Roy. Soc. 232, 333-94 An early structural model of proteins. 

Structural models of protein and nucleic acid molecules derived by X-ray crystallography are exttemely interesting in themselves, each being a representative member of some architectural class of macromolecule shaped by evolutionary time and process toward the optimal completion of a specific cellular or metabolic task. They are nevertheless static objects. Because the catalytic functions they perform depend on dynamic events involving the interaction of the macromolecules with substrates, effectors, inhibitors, and other cellular components, we are constantly searching for techniques that will allow us to visualize the macromolecules in some intermediate stages of a biochemical or physiological activity. 

Wade, R.C. (2001) Derivation of QSARs using 3D structural models of protein-ligand complexes by COMBINE analysis, in Rationed Approaches to Drug Design (eds H.-D. Holtje and W. Sippl), Prous Science, Barcelona, Spain, pp. 23-28. 

Since only 20-40% of the protein sequences in a genome such as M. genitalium, M. Janaschii, M. tuberculosis have a sequence similarity that can exhibit their paralogy to proteins of known function [242, 258], we need to be able to make conclusions on proteins that exhibit much lower similarities to suitable model proteins. As the similarity between query sequence and model sequence decreases below a threshold of, say, 25% we cannot make safe conclusions on a common evolutionary origin of the query sequence and the model sequence any more. However, it turns out that, in many cases, we can still reliably predict the protein fold, and in several cases we can even generate detailed structural models of protein binding sites. Thus, especially in this similarity range, protein structure prediction can help to ascertain aspects of protein function [243, 246, 247]. 

Figure 3. Summary ofFe(II) EXAFS characterization for YJhl (A), the Yfhl/Heml5 complex (B) and for HemlS (C), Top Structural model of proteins with iron bound Middle Fourier transforms (black) and simulations (grey) of Fe EXAFS Bottom graphical representation of approximate iron coordination geometry.

Korkin, D., Davis, F.P., Alber, R, Luong, T., Shen, M.Y., Lucic, V., Kennedy, B.M., Sali, A. Structural modeling of protein interactions by analogy Application to PSD-95. PLoS Comput. Biol. 2006, 2, el53. 

Figure 4.7. Structural model of proteins complex, consisting from myosin head (HMM-Sl), actin (A), tropomyosin (TM), and the three troponins (In - T, I, and C, respectively), (a) "blocked" position - relaxation (b) "free" access of HMM-Sl to actin filaments - contraction.

P. J. Kundrotas, Z. Zhu, and I. A. Vakser, Hum. Genomics, 6, 7-10 (2012). GWIDD A Comprehensive Resource for Genome-wide Structural Modeling of Protein-Protein Interactions. 

Li FI, Winfreen N and Tang C 1996 Emergence of preferred structures in a simple model of protein folding Science 273 666-9... 

J.D. Bryngelson, When is a potential accurate enough for structure prediction Theory and application to a random heteropolymer model of protein folding, J. Ghem. Phys. 100 (1994), 6038-6045. 

A. Neumaier, Molecular modeling of proteins and mathematical prediction of protein structure, SIAM Rev. 39 (1997), 407-460. 

S. Sun, Reduced representation model of protein structure prediction statistical potential and genetic algorithms. Protein Sci. 2 (1993), 762-785. 

Li H, R Helling, C Tang and N Wingreen 1996. Emergence of Preferred Structures in a Simple Model of Protein Folding. Science 273 666-669. 

Sanchez K and A Sali 1998. Large-scale Protein Structure Modelling of the Saccharomyces cerevi. Genome. Proceedings of the National Academy of Sciences USA 95 13597-13602. 

This section briefly reviews prediction of the native structure of a protein from its sequence of amino acid residues alone. These methods can be contrasted to the threading methods for fold assignment [Section II.A] [39-47,147], which detect remote relationships between sequences and folds of known structure, and to comparative modeling methods discussed in this review, which build a complete all-atom 3D model based on a related known structure. The methods for ab initio prediction include those that focus on the broad physical principles of the folding process [148-152] and the methods that focus on predicting the actual native structures of specific proteins [44,153,154,240]. The former frequently rely on extremely simplified generic models of proteins, generally do not aim to predict native structures of specific proteins, and are not reviewed here. 

R Sanchez, A Sail. Large-scale protein structure modeling of the Saccharomyces cerevisiae genome. Proc Natl Acad Sci USA 95 13597-13602, 1998. 

CM Topham, A McLeod, E Eisenmenger, JP Overmgton, MS Johnson, TL Blundell. Erag-ment ranking in modelling of protein structure. Conformationally constrained environmental ammo acid substitution tables. J Mol Biol 229 194-220, 1993. 

N Srimvasan, TL Blundell. An evaluation of the performance of an automated procedure for comparative modelling of protein tertiary structure. Protein Eng 6 501-512, 1993. 

P Koehl, M Delame. A self consistent mean field approach to simultaneous gap closure and side-chain positioning m protein homology modelling. Nature Struct Biol 2 163-170, 1995. R Samudrala, J Moult. A graph-theoretic algorithm for comparative modeling of protein structure. J Mol Biol 279 287-302, 1998. 

Leucine residues 2, 5, 7, 12, 20, and 24 of the motif are invariant in both type A and type B repeats of the ribonuclease inhibitor. An examination of more than 500 tandem repeats from 68 different proteins has shown that residues 20 and 24 can be other hydrophobic residues, whereas the remaining four leucine residues are present in all repeats. On the basis of the crystal structure of the ribonuclease inhibitor and the important structural role of these leucine residues, it has been possible to construct plausible structural models of several other proteins with leucine-rich motifs, such as the extracellular domains of the thyrotropin and gonadotropin receptors. 

In 1972, S. J. Singer and G. L. Nicolson proposed the fluid mosaic model for membrane structure, which suggested that membranes are dynamic structures composed of proteins and phospholipids. In this model, the phospholipid bilayer is a fluid matrix, in essence, a two-dimensional solvent for proteins. Both lipids and proteins are capable of rotational and lateral movement. 

The aim of the second dimension depth is to consider protein 3D-stmctures to uncover structure-function relationships. Starting from the protein sequences, the steps in the depth dimension are structure prediction, homology modeling of protein structures, and the simulation of protein-protein interactions and ligand-complexes. 

Predicting a likely conformation or fold of a particular region of a protein with less or no sequence similarity to protein structures recorded in the PDB, is the main challenges for homology modeling of proteins. 

Once an electron density map has become available, atoms may be fitted into the map by means of computer graphics to give an initial structural model of the protein. The quality of the electron density map and structural model may be improved through iterative structural refinement but will ultimately be limited by the resolution of the diffraction data. At low resolution, electron density maps have very few detailed features (Fig. 6), and tracing the protein chain can be rather difficult without some knowledge of the protein structure. At better than 3.0 A resolution, amino acid side chains can be recognized with the help of protein sequence information, while at better than 2.5 A resolution solvent molecules can be observed and added to the structural model with some confidence. As the resolution improves to better than 2.0 A resolution, fitting of individual atoms may be possible, and most of the... 

Marti-Renom MA et al (2000) Comparative protein structure modeling of genes and genomes. Annu Rev Biophys Biomol Struct 29 291-325... 

Schueler-Furman O et al (2005) Progress on modeling of protein structures and interactions. Science 310(5748) 638-642... 

This simple three-state model of protein folding, shown schematically in Figure 7, ascribes a separate force to shaping the structure of each state. Local steric interactions trap the protein chain in a large ensemble of conformations with the correct topology hydrophobic interactions drive the chain to a smaller, more compact subset of conformations then dispersion forces supply the enthalpy loss required to achieve a relatively fixed and rigid ensemble of native conformations. 

For further details about the progress in the syntheses of the structural models of the clusters in MoFe protein, please see the other recent reviews,33 together with those dealing with the reactions of metal-sulfur clusters relating to the nitrogen-fixation chemistry.34... 

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