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Protein structure generation

At least one assignment is compatible with the intermediate 3D protein structure generated in the preceding cycle, (cycles 2,3,...)... [Pg.57]

The raw data for protein-structure generation is the protein sequence. In principle this data string encodes the 3D structure of the protein. How the protein folds is still unclear. Nevertheless, certain folding patterns are associated with specific sequence patterns, so it is possible to develop expert systems to provide 3D models of new folded proteins. Commercial software for homology modeling is widely available. [Pg.33]

The sampling problem Given two independent protein structures, generate putative structures of the complex. [Pg.70]

Shen Y, Lange O, Delaglio E, Rossi P, Aramini JA, Liu G, Eletsky A, Wu Y, Singarapu KK, Le-mak A, Ignatchenko A, Arrowsmith CH, Szyperski T, Montelione GT, Baker D, Bax A (2008) Consistent blind protein structure generation Horn NMR chemical shift data. Proc Natl Acad Sci USA 105(12) 4685 690... [Pg.413]

Step 1 A short conventional MD simulation (typically extending over a few lOOps) is performed to generate an ensemble of protein structures x 6 71 (each described by N atomic positions), which characterizes the initial conformational substate. The 2-dimensional sketch in Fig. 9 shows such an ensemble as a cloud of dots, each dot x representing one snapshot of the protein. [Pg.91]

A further milestone was achieved in 1977 by Richardson ct ah They could for the first time visualize a complete protein structure from X-ray ciystallography data 19h. A large numlier of structures were generated in the following years. [Pg.131]

In order to represent 3D molecular models it is necessary to supply structure files with 3D information (e.g., pdb, xyz, df, mol, etc.. If structures from a structure editor are used directly, the files do not normally include 3D data. Indusion of such data can be achieved only via 3D structure generators, force-field calculations, etc. 3D structures can then be represented in various display modes, e.g., wire frame, balls and sticks, space-filling (see Section 2.11). Proteins are visualized by various representations of helices, / -strains, or tertiary structures. An additional feature is the ability to color the atoms according to subunits, temperature, or chain types. During all such operations the molecule can be interactively moved, rotated, or zoomed by the user. [Pg.146]

Ithough knowledge-based potentials are most popular, it is also possible to use other types potential function. Some of these are more firmly rooted in the fundamental physics of iteratomic interactions whereas others do not necessarily have any physical interpretation all but are able to discriminate the correct fold from decoy structures. These decoy ructures are generated so as to satisfy the basic principles of protein structure such as a ose-packed, hydrophobic core [Park and Levitt 1996]. The fold library is also clearly nportant in threading. For practical purposes the library should obviously not be too irge, but it should be as representative of the different protein folds as possible. To erive a fold database one would typically first use a relatively fast sequence comparison lethod in conjunction with cluster analysis to identify families of homologues, which are ssumed to have the same fold. A sequence identity threshold of about 30% is commonly... [Pg.562]

B and W J Howe 1991. Computer Design of Bioactive Molecules - A Method for Receptor-Based Novo Ligand Design. Proteins Structure, Function and Genetics 11 314-328. i H L 1965. The Generation of a Unique Machine Description for Chemical Structures - A hnique Developed at Chemical Abstracts Service. Journal of Chemical Documentation 5 107-113. J 1995. Computer-aided Estimation of Symthetic Accessibility. PhD thesis. University of Leeds, itan R, N Bauman, J S Dixon and R Venkataraghavan 1987. Topological Torsion A New )lecular Descriptor for SAR Applications. Comparison with Other Descriptors. Journal of emical Information and Computer Science 27 82-85. [Pg.740]

D Bassohno-Klimas, RE Bniccolen. Application of a directed conformational search for generating 3-D coordinates for protein structures from a-carbon coordinates. Proteins 14 465-474, 1992. [Pg.304]

CWG van Gelder, EJJ Leusen, JAM Leunissen, JH Noordik. A molecular dynamics approach for the generation of complete protein structures from limited coordinate data. Proteins 18 174-185, 1994. [Pg.304]

It can be inferred from the first section of this chapter that many different forces work together in a delicate balance to determine the overall three-dimensional structure of a protein. These forces operate both within the protein structure itself and between the protein and the water solvent. How, then, does nature dictate the manner of protein folding to generate the three-dimensional... [Pg.160]

Applying the Board s decision to the data generated in the use of microarrays would suggest that a data structure is patentable if the data relate to the control of a microarray experiment or to the display of information obtained from a microarray experiment. Furthermore, as data relating to the DNA sequences or protein structure are not merely cognitive information, it is possible to argue that data structures containing the information on the DNA sequences or on the protein structure will be patentable. [Pg.709]


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