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Starting model

These predictive methods are very useful in many contexts for example, in the design of novel polypeptides for the identification of possible antigenic epitopes, in the analysis of common motifs in sequences that direct proteins into specific organelles (for instance, mitochondria), and to provide starting models for tertiary structure predictions. [Pg.352]

This linear scheme of signal transduction (Fig. 12) from hypothetical membrane receptors to [Ca " ] and IP3 increases, calcium-calmodulin interaction, kinases activation and gene transcription is clearly an oversimplification of the reality several receptors must exist that are connected to different transduction cascades that activate a series of defense genes. Cross-talking between the pathways further complicates the picture. However, this represents a starting model on which to elaborate more refined hypotheses. [Pg.147]

A starting model can be selected depending on the type of dense phase transport. Modeling a homogeneous dense phase would use the same approach as dilute phase with a new frictional term. This approach would have two contributions due to the gas alone and the linear combination with the solids contribution. [Pg.695]

An alternative approach to obtaining a starting model for the refinement that does not need NOE data is called molecular fragment replacement [71] and treats the protein of interest as overlapping fragments of 7 to 10 residues in length. A protein database is... [Pg.191]

Structure refinement is not simply the last step of solving a structure, but it is also a whole independent world on its own. On the one hand, refinement can be done on a structure which is assumed (known) from a source different from that outlined above. On the other hand, refinement is not simply a procedure resulting more accurate atomic coordinates, but also a way to verify the starting model. The model can only be accepted with high probability if it can be refined to a good match between measured and computed patterns. [Pg.192]

Fig. 2. The histone octamer. The 3.1 A X-ray diffraction data model of Arents et al. [20] is shown in secondary structure cartoon format. The core of the histone octamer is well defined, but more than 30% of the histone sequence is in regions without secondary structure. These are unfortunately the most interesting regions in terms of epigenetic signaling. 25% of the molecule located in the N-terminal tails (and the C-termini of H2A) in the 3.1 A octamer structure has no interpretable electron density. Despite these limitations, this structure is sufficient to use as a starting model for molecular replacement phasing of the NCP. (Image courtesy of E. Moudrianakis.)... Fig. 2. The histone octamer. The 3.1 A X-ray diffraction data model of Arents et al. [20] is shown in secondary structure cartoon format. The core of the histone octamer is well defined, but more than 30% of the histone sequence is in regions without secondary structure. These are unfortunately the most interesting regions in terms of epigenetic signaling. 25% of the molecule located in the N-terminal tails (and the C-termini of H2A) in the 3.1 A octamer structure has no interpretable electron density. Despite these limitations, this structure is sufficient to use as a starting model for molecular replacement phasing of the NCP. (Image courtesy of E. Moudrianakis.)...
Rigid maps depend on the exact choice of starting model (8,). Iirqportant minima on the energy surface are likely to be ignored since energies are high on most of the surface except near the starting shape. [Pg.12]

Figure 5. Conformational map for maltose, calculated with MMP2(85), using the methods that are described in the chapter herein by French, Tran and P6rez with four starting models. < ) and f were varied in steps of 20 . Contours are at intervals of one kcal/mol. Figure 5. Conformational map for maltose, calculated with MMP2(85), using the methods that are described in the chapter herein by French, Tran and P6rez with four starting models. < ) and f were varied in steps of 20 . Contours are at intervals of one kcal/mol.
With this option (the -1 option in the MM2 manual), the residues of the starting model are rotated rigidly (without internal change) to the first < ), P combination to be considered. After the first optimization finishes, the first torsion angle specified (eg. [Pg.197]

The effects of propagated distortions of the residue are shown in Figure 4, a CA map without contouring that was prepared with the standard driver. The gtgtRR starting model of cellobiose had an energy of 31.4 kcal/mol (its conformation was < ) = 20, - -60). ... [Pg.197]

Figure 2. The four starting models used for the study of cellobiose (lone pairs of electrons are not shown). Convention defines the R and C notation when the residue is in a conventional orientation and is viewed from above. The least energetic structure observed in this study is gtgtRR. This Figure and Figure 5 were drawn with CHEMX, developed and distributed by Chemical Design Ltd, Oxford, England. Figure 2. The four starting models used for the study of cellobiose (lone pairs of electrons are not shown). Convention defines the R and C notation when the residue is in a conventional orientation and is viewed from above. The least energetic structure observed in this study is gtgtRR. This Figure and Figure 5 were drawn with CHEMX, developed and distributed by Chemical Design Ltd, Oxford, England.
Figure 4. Energy values (Kcal/mol) for a gtgtRR starting model produced with MM2 and its standard option -1 dihedral driver. Figure 4. Energy values (Kcal/mol) for a gtgtRR starting model produced with MM2 and its standard option -1 dihedral driver.
Figure 5. a) The starting model of cellobiose (gtgtRR) after rigid rotation to -80, 0 -100. b) The result of attenpted optimization by MM2, c) The same linkage conformation, but the structure was taken from the study that produced the map in Figure 4. [Pg.200]

In the four sets of 324 points calculated, structures failed to optimize properly 37 times. Figure 6e shows the locations and the numbers of those models. All < ), P points that corresponded to improperly optimized conformations, when tested with other starting models, gave optimized energies at least 10 kcal above the minimum. [Pg.203]

The Strategy conveyed in this paper permits coherent results from an automated CA while using flexible residues. By testing all the starting models over the entire range of < ) and P, parallel sets of data were obtained that were submitted to a simple program for final analysis. This minimizes the personal time required to produce a... [Pg.203]

Figure 6a. MM2 "Final Steric Energy" values for all tested values of Phi and Psi. The value at each point is the lowest of the energies calculated for the four starting models. (The largest < ) and values are 160 ). Figure 6a. MM2 "Final Steric Energy" values for all tested values of Phi and Psi. The value at each point is the lowest of the energies calculated for the four starting models. (The largest < ) and values are 160 ).
The starting model at each point that gave the lowest gtgtRR, 2 gtgtCC, 3 - ggggRC and 4 - ggggRR). [Pg.204]


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See also in sourсe #XX -- [ Pg.198 ]




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Start-stop model

Starting the Model and Running a Base Case

The Starting Model

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