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Model proteins order, increased

At this time, approximately one-half of all sequences are delectably related to at least one protein of known structure [8-11]. Because the number of known protein sequences is approximately 500,000 [12], comparative modeling could in principle be applied to over 200,000 proteins. This is an order of magnitude more proteins than the number of experimentally determined protein structures (—13,000) [13]. Furthermore, the usefulness of comparative modeling is steadily increasing, because the number of different structural folds that proteins adopt is limited [14,15] and because the number of experimentally determined structures is increasing exponentially [16]. It is predicted that in less than 10 years at least one example of most structural folds will be known, making comparative modeling applicable to most protein sequences [6]. [Pg.275]

In the IVK-model, as K increases, the number of fitter neighbors decreases more quickly as the sequence becomes more optimized (Kauffman and Weinberger, 1989). Thus, in order to discover improved mutants, the number of mutants screened has to increase more rapidly on random landscapes as the sequence increases in fitness (Fig. 4). The rate of decrease for the number of uphill paths is greater for rugged landscapes due to the shortening of the walk length to local optima. This implies that a protein that is tolerant (a smoother landscape) can undergo more rounds of mutation and improvement. [Pg.125]

This equation results from the model characterised by Eqs. (2.84) - (2.88). Under dynamic conditions T < T , and protein molecules increase their number of adsorbed segments each occupying an area C0, while when > r. earlier adsorbed segments rearrange to leave the interface. The transfer between the different states may be described by a first order reaction... [Pg.304]

Quite the inverse occurs for water-dissolved protein of interest here that is, by the consilient mechanism, heating from below to above the folding transition increases the order of the model protein. Because heating increases protein order, the transition is called an inverse temperature transition. [Pg.38]

Despite the absorption of heat for the transition and the overall increase in entropy of -(-4.0 EU for the water plus protein, the protein component actually increases in order on raising the temperature. As unambiguously demonstrated by crystallization of a cyclic analog (see Figure 2.7), in this case the protein component of the water plus protein system becomes more ordered as the temperature is raised. For this and additional reasons, noted below in section 5.1.3, we call this transition exhibited by our model protein, poly (GVGVP), an inverse temperature transition. [Pg.107]

Our Model Proteins Increase Order on Raising the Temperature... [Pg.108]

A vital property of these model proteins is that they are more ordered above the transition temperature defined by the binodal or coexistence line in Figure 5.3. The polymer component of this water-polypeptide system becomes more ordered or structured on increased temperature from below to above the transition. This behavior is the inverse of that observed for most systems, as discussed above. In particular, we developed the term inverse temperature transition when the precursor protein and chemical fragmentation products of the mammalian elastic fiber changed from a dissolved state, and therefore when molecules were randomly dispersed in solution, to a state of parallel-aligned twisted filaments as the temperature was raised from below to above the phase transition. - ... [Pg.108]

Figure 5.3. Phase diagram for several elastic-contractile model proteins, showing an inverted curvature to the binodal or coexistence line (when compared with petroleum-based polymers) that is equivalent to the T,-divide, with the value of T, determined as noted in Figure 5.IB. Solubility is also inverted with insolubility above and solubility below the binodal line, that is, solubility is lost on raising the temperature whereas solubility is achieved by raising the temperature of most petroleum-based polymers in their solvents. Note that addition of a CHj group lowers the T,-divide and removal of the CH2 group raises the T,-divide. For these and the additional reason of increased ordering on increasing the temperature, the phase transitions of elastic-contractile model proteins are called inverse temperature transitions. (The curve for poly[GVGVP] is adapted with permission from Manno et al. and Sciortino et al. ). Figure 5.3. Phase diagram for several elastic-contractile model proteins, showing an inverted curvature to the binodal or coexistence line (when compared with petroleum-based polymers) that is equivalent to the T,-divide, with the value of T, determined as noted in Figure 5.IB. Solubility is also inverted with insolubility above and solubility below the binodal line, that is, solubility is lost on raising the temperature whereas solubility is achieved by raising the temperature of most petroleum-based polymers in their solvents. Note that addition of a CHj group lowers the T,-divide and removal of the CH2 group raises the T,-divide. For these and the additional reason of increased ordering on increasing the temperature, the phase transitions of elastic-contractile model proteins are called inverse temperature transitions. (The curve for poly[GVGVP] is adapted with permission from Manno et al. and Sciortino et al. ).
Protein folding studies generally concern liquid-phase phenomena however, HDX reactions can also be conducted in the gas phase (e.g., [84-90] for an overview see [91]). For instance, multiply charged ions of several model proteins reacted with DjO in a vacuum following pseudo-first-order kinetics [85]. It was also observed that removing solvent significantly increased conformational rigidity. In other work, ions of bovine ubiquitin were... [Pg.298]

The choice of the particular upward pathway in the kinetic resolution of rac-19, that is, the specific order of choosing the sites in ISM, appeared arbitrary. Indeed, the pathway B C D F E, without utilizing A, was the first one that was chosen, and it led to a spectacular increase in enantioselectivity (Figure 2.15). The final mutant, characterized by nine mutations, displays a selectivity factor of E=115 in the model reaction [23]. This result is all the more remarkable in that only 20000 clones were screened, which means that no attempt was made to fully cover the defined protein sequence space. Indeed, relatively small libraries were screened. The results indicate the efficiency of iterative CASTing and its superiority over other strategies such as repeating cycles of epPCR. [Pg.42]


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See also in sourсe #XX -- [ Pg.108 , Pg.109 ]




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