As order-related. The distribution Yj is hard to derive analytically, so we randomly generated 1,000 realizations and calculated the empirical p-value because the fraction of times these realizations were larger than Fj. We also calculated the mean j and common deviation j with the 1,000 realizations. We observed that, when KWj is significant, distribution of Yj resembles a Gaussian distribution with mean j and common deviation j. Working with the Gaussian approximation, we calculated the Zscore of KWj as (Fj – j) / j and its p-value as 1/2(1 – erf(Zj/2)), where erf() is the error function. The Gaussian approximation is useful considering the fact that making use of the fraction of 1,000 replicates is just not correct in estimating p-values below 0.01 or above 0.99. We report the Z-scores collectively with the empirical p-values within the benefits.Estimating correlation between long disordered regions and Swiss-Prot key phrases We applied the process described above to each on the 710 Swiss-Prot search phrases occurring each in more than 20 Swiss-Prot proteins. These 710 keywords and phrases can be grouped into 11 functional categories, that are listed in Table 1. We denote keywords with p-value 0.95 as disorder-related as well as the ones with p-value 0.05 as order-related. Keyword phrases with p-value among 0.95 and 0.05 are ambiguous. These functions could possibly depend on structured of disordered regions but simply exhibit signals which are too weak. Alternatively these functions may well depend on brief regions of disorder or may well need each ordered and disordered regions. The amount of key phrases strongly correlated with disorder and order is considerably larger than HDAC11 Inhibitor Species anticipated by the random model. This is evident by observing that, for any p-value threshold of 0.05, a random predictor would lead to about five ( 36) of order and 5 of disorder-related key phrases. These final results recommend that presence or absence of disordered regions is definitely an essential factor in majority of biological functions and processes. Overall, this analysis shows that 238 Swiss-Prot functional key phrases are disorder-related, whereas 302 are order-related. Interestingly, only two of your categories, “Biological Process” and “Ligand”, are enriched inJ Proteome Res. Author manuscript; available in PMC 2008 September 19.Xie et al.Pageorder-related key phrases, even though the remaining 9 are enriched in the disorder-related keywords. This result supports an earlier conjecture that disordered regions have a larger functional repertoire than the ordered regions.20 To further recognize these function-disorder relationships, we carried out manual literature mining and studied a large variety of person experimental examples. To organize the presentation of these results, the keywords and phrases from numerous functional categories, which are most considerably connected with protein order and disorder arranged into H2 Receptor Modulator Molecular Weight particular groups (Table 2 capable six). In each and every table, the disorder-function relationships are ranged by their Z-scores (see Supplies and Solutions). The Z-scores for all 710 functions are offered in Supplementary Components (see Table S1). One of many important goals here was to figure out for each example regardless of whether the indicated function was carried out by regions of disorder or regions of structure. Right after all, the keyword-disorder correlations established by the system of Figure 2 usually do not ascertain no matter if the indicated association implies direct involvement of disorder with function or not. Biological processes linked with intrinsically disordered proteins The set of leading 20 Swiss-Prot.