Intrinsically disordered proteins (IDPs) and IDP regions fail to form a stable structure, yet they exhibit biological activities. Their mobile flexibility and structural instability are encoded by their amino acid sequences. They recognize proteins, nucleic acids, and other types of partners; they accelerate interactions and chemical reactions between bound partners; and they help accommodate posttranslational modifications, alternative splicing, protein fusions, and insertions or deletions. Overall, IDP-associated biological activities complement those of structured proteins. Recently, there has been an explosion of studies on IDP regions and their functions, yet the discovery and investigation of these proteins have a long, mostly ignored history. Along with recent discoveries, we present several early examples and the mechanisms by which IDPs contribute to function, which we hope will encourage comprehensive discussion of IDPs and IDP regions in biochemistry textbooks. Finally, we propose future directions for IDP research.

Intrinsically disordered proteins and intrinsically disordered protein regions.

Motivation: Advances in high-throughput genotyping and next generation sequencing have generated a vast amount of human genetic variation data. Single nucleotide substitutions within protein coding regions are of particular importance owing to their potential to give rise to amino acid substitutions that affect protein structure and function which may ultimately lead to a disease state. Over the last decade, a number of computational methods have been developed to predict whether such amino acid substitutions result in an altered phenotype. Although these methods are useful in practice, and accurate for their intended purpose, they are not well suited for providing probabilistic estimates of the underlying disease mechanism.

Results: We have developed a new computational model, MutPred, that is based upon protein sequence, and which models changes of structural features and functional sites between wild-type and mutant sequences. These changes, expressed as probabilities of gain or loss of structure and function, can provide insight into the specific molecular mechanism responsible for the disease state. MutPred also builds on the established SIFT method but offers improved classification accuracy with respect to human disease mutations. Given conservative thresholds on the predicted disruption of molecular function, we propose that MutPred can generate accurate and reliable hypotheses on the molecular basis of disease for ~11% of known inherited disease-causing mutations. We also note that the proportion of changes of functionally relevant residues in the sets of cancer-associated somatic mutations is higher than for the inherited lesions in the Human Gene Mutation Database which are instead predicted to be characterized by disruptions of protein structure.

Availability: http://mutdb.org/mutpred 

Contact:predrag@indiana.edu; smooney@buckinstitute.org

Automated inference of molecular mechanisms of disease from amino acid substitutions

Johnny Habchi,†,‡ Peter Tompa,* Sonia Longhi,†,‡,* and Vladimir N. Uversky* †Aix-Marseille Universite,́ Architecture et Fonction des Macromolećules Biologiques (AFMB), UMR 7257, 13288, Marseille, France ‡CNRS, Architecture et Fonction des Macromolećules Biologiques (AFMB), UMR 7257, 13288, Marseille, France VIB Department of Structural Biology, Vrije Universiteit Brussel, 1050 Ixelles, Belgium Institute of Enzymology, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, H-1113, Hungary Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, Florida 33620, United States Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow Region, Russia

/pdf/introducing-protein-intrinsic-disorder-4fu2ss4mcf.pdf

Introducing Protein Intrinsic Disorder.

https://www.mrc-lmb.cam.ac.uk/genomes/mkayikci/MendeleyMadanPapers/2011_Current%20opinion%20in%20structural%20biology_Babu%20et%20al._Intrinsically%20disordered%20proteins%20regulation%20and%20disease.pdf

Intrinsically disordered proteins: regulation and disease

Parkinson’s disease (PD) coincides with a dramatic loss of dopaminergic neurons within the substantia nigra. A key player in the loss of dopaminergic neurons is oxidative stress. Dopamine (DA) metabolism itself is strongly linked to oxidative stress as its degradation generates reactive oxygen species (ROS) and DA oxidation can lead to endogenous neurotoxins whereas some DA derivatives show antioxidative effects. Therefore, DA metabolism is of special importance for neuronal redox-homeostasis and viability. In this review we highlight different aspects of dopamine metabolism in the context of PD and neurodegeneration. Since most reviews focus only on single aspects of the DA system, we will give a broader overview by looking at DA biosynthesis, sequestration, degradation and oxidation chemistry at the metabolic level, as well as at the transcriptional, translational and posttranslational regulation of all enzymes involved. This is followed by a short overview of cellular models currently used in PD research. Finally, we will address the topic from a medical point of view which directly aims to encounter PD.

/pdf/complexity-of-dopamine-metabolism-kgg8jy8ri3.pdf

Complexity of dopamine metabolism

Ubiquitination plays an important role in many cellular processes and is implicated in many diseases. Experimental identification of ubiquitination sites is challenging due to rapid turnover of ubiquitinated proteins and the large size of the ubiquitin modifier. We identified 141 new ubiquitination sites using a combination of liquid chromatography, mass spectrometry, and mutant yeast strains. Investigation of the sequence biases and structural preferences around known ubiquitination sites indicated that their properties were similar to those of intrinsically disordered protein regions. Using a combined set of new and previously known ubiquitination sites, we developed a random forest predictor of ubiquitination sites, UbPred. The class-balanced accuracy of UbPred reached 72%, with the area under the ROC curve at 80%. The application of UbPred showed that high confidence Rsp5 ubiquitin ligase substrates and proteins with very short half-lives were significantly enriched in the number of predicted ubiquitination sites. Proteome-wide prediction of ubiquitination sites in Saccharomyces cerevisiae indicated that highly ubiquitinated substrates were prevalent among transcription/enzyme regulators and proteins involved in cell cycle control. In the human proteome, cytoskeletal, cell cycle, regulatory, and cancer-associated proteins display higher extent of ubiquitination than proteins from other functional categories. We show that gain and loss of predicted ubiquitination sites may likely represent a molecular mechanism behind a number of disease-associatedmutations. UbPred is available at http://www.ubpred.org.

/pdf/identification-analysis-and-prediction-of-protein-1l09tobz8s.pdf

Identification, Analysis and Prediction of Protein Ubiquitination Sites

The pro-inflammatory cytokines, Tumor Necrosis Factor-alpha (TNFα) and Interleukin-1 (IL-1) mediate the innate immune response. Dysregulation of the innate immune response contributes to the pathogenesis of cancer, arthritis, and congestive heart failure. TNFα- and IL-1-induced changes in gene expression are mediated by similar transcription factors; however, TNFα and IL-1 receptor knock-out mice differ in their sensitivities to a known initiator (lipopolysaccharide, LPS) of the innate immune response. The contrasting responses to LPS indicate that TNFα and IL-1 regulate different processes. A large-scale proteomic analysis of TNFα- and IL-1-induced responses was undertaken to identify processes uniquely regulated by TNFα and IL-1. When combined with genomic studies, our results indicate that TNFα, but not IL-1, mediates cell cycle arrest. Keywords: Tumor Necrosis Factor-alpha • Interleukin-1 • Cell Cycle Arrest • Permeability Transition Pore • Protein Interaction Network • Mass Spectrometry • Microarray

/pdf/tumor-necrosis-factor-a-and-interleukin-1-induced-cellular-2c7u71jba9.pdf

Joshua W. Heyen

Papers

Identification, Analysis and Prediction of Protein Ubiquitination Sites

Tumor Necrosis Factor-α -and Interleukin-1-Induced Cellular Responses: Coupling Proteomic and Genomic Information