Disorder Prediction

In the field of bioinformatics, avaUability of disorder prediction algorithms has enabled proteome-scale analysis of disorder propensity and correlation of disorda- with function [17-24]. Ordered and disordered proteins have diffeent roles in cellular processes. Whereas ordered proteins tend to be 

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Figure 17.11 Residue-averaged hydrogen exchange half-life (b) correlates well with other measurements of secondary structure (c) and (d) NMR measurements of residual structure based on secondary chemical shifts [48] and (e) a helical propensity prediction using ACADIR [49-51]. A PONDR disorder prediction [2, 3], shown in (f), was not able to identify residual structure. Secondary structure elements shown in (a) indicate a-helical (boxes), loop (lines), and unstructured (dotted lines) thatACTR adopts in complex with CBP [29]. Reprinted with kind permission from Springer Science+Business Media from Figure 17.5 in Ref [S3] and any original (first) notice displayed with material...

Deng, X., Eickholt, J., Cheng, J. (2012) A comprehensive overview of computationeil protein disorder prediction methods. Mol Biosyst, 8(1), 114-121. 

Introducing disorder - predicting when chemical reactions occur... 

The Ag (100) surface is of special scientific interest, since it reveals an order-disorder phase transition which is predicted to be second order, similar to tire two dimensional Ising model in magnetism [37]. In fact, tire steep intensity increase observed for potentials positive to - 0.76 V against Ag/AgCl for tire (1,0) reflection, which is forbidden by symmetry for tire clean Ag(lOO) surface, can be associated witli tire development of an ordered (V2 x V2)R45°-Br lattice, where tire bromine is located in tire fourfold hollow sites of tire underlying fee (100) surface tills stmcture is depicted in tlie lower right inset in figure C2.10.1 [15]. 

Two point defects may aggregate to give a defect pair (such as when the two vacanc that constitute a Schottky defect come from neighbouring sites). Ousters of defects ( also form. These defect clusters may ultimately give rise to a new periodic structure oi an extended defect such as a dislocation. Increasing disorder may alternatively give j to a random, amorphous solid. As the properties of a material may be dramatically alte by the presence of defects it is obviously of great interest to be able to imderstand th relationships and ultimately predict them. However, we will restrict our discussion small concentrations of defects. 

Figure 6 shows the field dependence of hole mobiUty for TAPC-doped bisphenol A polycarbonate at various temperatures (37). The mobilities decrease with increasing field at low fields. At high fields, a log oc relationship is observed. The experimental results can be reproduced by Monte Carlo simulation, shown by soHd lines in Figure 6. The model predicts that the high field mobiUty follows the following equation (37) where d = a/kT (p is the width of the Gaussian distribution density of states), Z is a parameter that characterizes the degree of positional disorder, E is the electric field, is a prefactor mobihty, and Cis an empirical constant given as 2.9 X lO " (cm/V). ...

It must be pointed out that deviations from such a simple relationship do occur. For example, since random copolymerisation tends to promote disorder, reduce molecular packing and also reduce the interchain forces of attraction, the Tg of copolymers is often lower than would be predicted by the linear relationship. Examples are also known where the Tg of the copolymer is higher than predicted. This could occur where hydrogen bonding or dipole attraction is possible between dissimilar comonomer residues in the chain but not between similar residues, i.e. special interchain forces exist with the copolymers. 

With block copolymers two types of effect have been observed. In some instances a transition corresponding to each block is observable whilst in other cases a single transition is observed, usually close to that predicted by a linear relationship even where random copolymers show large deviations. This is because the blocks reduce both the contacts between dissimilar comonomer residues and also the disorder of the molecules which occurs in random copolymer systems. 

The electrical conductivity is proportional to n. Equation 1.168 therefore predicts an electrical conductivity varying as p. Experimental results show proportionality to p and this discrepancy is probably due to incomplete disorder of cation vacancies and positive holes. An effect of this sort (deviation from ideal thermodynamic behaviour) is not allowed for in the simple mass action formula of equation 1.167. 

In the above consideration it has been tacitly assumed that the charge carrier mobility docs not depend on the electric field. This is a good approximation for molecular crystals yet not for disordered systems in which transport occurs via hopping. Abkowitz et al. [37] have solved that problem for a field dependence of ft of the form p-po (FIFU) and trap-free SCL conduction. Their treatment predicts... 

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