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Item Conversation of Intrinsic Disorder in Protein Domains and Families(2005-08) Chen, Jessica Walton; Dunker, A. KeithProtein regions which lack a fixed structure are called ‘disordered’. These intrinsically disordered regions are not only very common in many proteins, they are also crucial to the function of many proteins, especially proteins involved in signaling and regulation. The goal of this work was to identify the prevalence, characteristics, and functions of conserved disordered regions within protein domains and families. A database was created to store the amino acid sequences of nearly one million proteins and their domain matches from the InterPro database, a resource integrating eight different protein family and domain databases. Disorder prediction was performed on these protein sequences. Regions of sequence corresponding to domains were aligned using a multiple sequence alignment tool. From this initial information, regions of conserved predicted disorder were found within the domains. The methodology for this search consisted of finding regions of consecutive positions in the multiple sequence alignments in which a 90% or more of the sequences were predicted to be disordered. This procedure was constrained to find such regions of conserved disorder prediction that were at least 20 amino acids in length. The results of this work were 3,653 regions of conserved disorder prediction, found within 2,898 distinct InterPro entries. Most regions of conserved predicted disorder detected were short, with less than 10% of those found exceeding 30 residues in length. Regions of conserved disorder prediction were found in protein domains from all available InterPro member databases, although with varying frequency. Regions of conserved disorder prediction were found in proteins from all kingdoms of life, including viruses. However, domains found in eukaryotes and viruses contained a higher proportion of long regions of conserved disorder than did domains found in bacteria and archaea. In both this work and previous work, eukaryotes had on the order of ten times more proteins containing long disordered regions than did archaea and bacteria. Sequence conservation in regions of conserved disorder varied, but was on average slightly lower than in regions of conserved order. Both this work and previous work indicate that in some cases, disordered regions evolve faster, in others they evolve slower, and in the rest they evolve at roughly the same rate. A variety of functions were found to be associated with domains containing conserved disorder. The most common were DNA/RNA binding, and protein binding. Many ribosomal protein families also were found to contain conserved disordered regions. Other functions identified included membrane translocation and amino acid storage for germination. Due to limitations of current knowledge as well as the methodology used for this work, it was not determined whether or not these functions were directly associated with the predicted disordered region. However, the functions associated with conserved disorder in this work are in agreement with the functions found in other studies to correlate to disordered regions. This work has shown that intrinsic disorder may be more common in bacterial and archaeal proteins than previously thought, but this disorder is likely to be used for different purposes than in eukaryotic proteins, as well as occurring in shorter stretches of protein. Regions of predicted disorder were found to be conserved within a large number of protein families and domains. Although many think of such conserved domains as being ordered, in fact a significant number of them contain regions of disorder that are likely to be crucial to their function.Item Intrinsic Disorder in Transcription Factors(2005-08) Liu, Jiangang (Al); Perumal, Narayanan B.Reported evidence suggested that high abundance of intrinsic disorder in eukaryotic genomes in comparison to bacteria and archaea may reflect the greater need for disorder-associated signaling and transcriptional regulation in nucleated cells. The major advantage of intrinsically disordered proteins or disordered regions is their inherent plasticity for molecular recognition, and this advantage promotes disordered proteins or disordered regions in binding their targets with high specificity and low affinity and with numerous partners. Although several well-characterized examples of intrinsically disordered proteins in transcriptional regulation have been reported and the biological functions associated with their corresponding structural properties have been examined, so far no specific systematic analysis of intrinsically disordered proteins has been reported. To test for a generalized prevalence of intrinsic disorder in transcriptional regulation, we first used the Predictor Of Natural Disorder Regions (PONDR VL-XT) to systematically analyze the intrinsic disorder in three Transcription Factor (TF) datasets (TFSPTRENR25, TFSPNR25, TFNR25) and two control sets (PDBs25 and RandomACNR25). PONDR VL-XT predicts regions of ≥30 consecutive disordered residues for 94.13%, 85.19%, 82.63%, 54.51%, and 18.64% of the proteins from TFNR25, TFSPNR25, TFSPTRENR25, RandomACNR25, and PDBs25, respectively, indicating significant abundance of intrinsic disorder in TFs as compared to the two control sets. We then used Cumulative Distribution Function (CDF) and charge-hydropathy plots to further confirm this propensity for intrinsic disorder in TFs. The amino acid compositions results showed that the three TF datasets differed significantly 5 from the two control sets. All three TF datasets were substantially depleted in order-promoting residues such as W, F, I, Y, and V, and significantly enriched in disorder-promoting residues such as Q, S, and P. H and C were highly over-represented in TF datasets because nearly a half of TFs contain several zinc-fingers and the most popular type of zinc-finger is C2H2. High occurrence of proline and glutamine in these TF datasets suggests that these residues might contribute to conformational flexibility needed during the process of binding by co-activators or repressors during transcriptional activation or repression. The data for disorder predictions on TF domains showed that the AT-hooks and basic regions of DNA Binding Domains (DBDs) were highly disordered (the overall disorder scores are 99% and 96% respectively). The C2H2 zinc-fingers were predicted to be highly ordered; however, the longer the zinc finger linkers, the higher the predicted magnitude of disorder. Overall, the degree of disorder in TF activation regions was much higher than that in DBDs. Our studies also confirmed that the degree of disorder was significantly higher in eukaryotic TFs than in prokaryotic TFs, and the results reflected the fact that the eukaryotes have well-developed elaborated gene transcription mechanism, and such a system is in great need of TF flexibility. Taken together, our data suggests that intrinsically disordered TFs or partially unstructured regions in TFs play key roles in transcriptional regulation, where folding coupled to binding is a common mechanism.Item PT symmetry breaking in the presence of random, periodic, long-range hopping(SPIE, 2016-09) Harter, Andrew K.; Assogba Onanga, Franck; Joglekar, Yogesh N.; Department of Physics, School of ScienceOver the past five years, open systems with balanced gain and loss have been investigated for extraordinary properties that are not shared by their closed counterparts. Non-Hermitian, Parity-Time (PT ) symmetric Hamiltonians faithfully model such systems. Such a Hamiltonian typically consists of a reflection-symmetric, Hermitian, nearest-neighbor hopping profile and a PT-symmetric, non-Hermitian, gain and loss potential, and has a robust PT -symmetric phase. Here we investigate the robustness of this phase in the presence of long-range hopping disorder that is not PT-symmetric, but is periodic. We find that the PT-symmetric phase remains robust in the presence of such disorder, and characterize the configurations where that happens. Our results are found using a tight-binding model, and we validate our predictions through the beam-propagation method.