Biomedical subjects

Yugong Cheng

Publications and source records attributed to Yugong Cheng.

5 recordsLinked to original sources

PubMed2006

Abundance of intrinsic disorder in protein associated with cardiovascular disease.

Evidence that many protein regions and even entire proteins lacking stable tertiary and/or secondary structure in solution (i.e., intrinsically disordered proteins) might be involved in protein-protein interactions, regulation, recognition, and signal transduction is rapidly accumulating. These signaling proteins play a crucial role in the development of several pathological conditions, including cancer. To test a hypothesis that intrinsic disorder is also abundant in cardiovascular disease (CVD), a data set of 487 CVD-related proteins was extracted from SWISS-PROT. CVD-related proteins are depleted in major order-promoting residues (Trp, Phe, Tyr, Ile, and Val) and enriched in some disorder-promoting residues (Arg, Gln, Ser, Pro, and Glu). The application of a neural network predictor of natural disordered regions (PONDR VL-XT) together with cumulative distribution function (CDF) analysis, charge-hydropathy plot (CH plot) analysis, and alpha-helical molecular recognition feature (alpha-MoRF) indicator revealed that CVD-related proteins are enriched in intrinsic disorder. In fact, the percentage of proteins with 30 or more consecutive residues predicted by PONDR VL-XT to be disordered was 57 +/- 4% for CVD-associated proteins. This value is close that described earlier for signaling proteins (66 +/- 6%) and is significantly larger than the content of intrinsic disorder in eukaryotic proteins from SWISS-PROT (47 +/- 4%) and in nonhomologous protein segments with a well-defined three-dimensional structure (13 +/- 4%). Furthermore, CDF and CH-plot analyses revealed that 120 and 36 CVD-related proteins, respectively, are wholly disordered. This high level of intrinsic disorder could be important for the function of CVD-related proteins and for the control and regulation of processes associated with cardiovascular disease. In agreement with this hypothesis, 198 alpha-MoRFs were predicted in 101 proteins from the CVD data set. A comparison of disorder predictions with the experimental structural and functional data for a subset of the CVD-associated proteins indicated good agreement between predictions and observations. Thus, our data suggest that intrinsically disordered proteins might play key roles in cardiovascular disease.

3',5'-Cyclic-AMP Phosphodiesterases↗

PubMed2006

Rational drug design via intrinsically disordered protein.

Despite substantial increases in research funding by the pharmaceutical industry, drug discovery rates seem to have reached a plateau or perhaps are even declining, suggesting the need for new strategies. Protein-protein interactions have long been thought to provide interesting drug discovery targets, but the development of small molecules that modulate such interactions has so far achieved a low success rate. In contrast to this historic trend, a few recent successes raise hopes for routinely identifying druggable protein-protein interactions. In this Opinion article, we point out the importance of coupled binding and folding for protein-protein signalling interactions generally, and from this and associated observations, we develop a new strategy for identifying protein-protein interactions that would be particularly promising targets for modulation by small molecules. This novel strategy, based on intrinsically disordered protein, has the potential to increase significantly the discovery rate for new molecule entities.

Chemistry, Pharmaceutical↗

PubMed2005

Coupled folding and binding with alpha-helix-forming molecular recognition elements.

Many protein-protein and protein-nucleic acid interactions involve coupled folding and binding of at least one of the partners. Here, we propose a protein structural element or feature that mediates the binding events of initially disordered regions. This element consists of a short region that undergoes coupled binding and folding within a longer region of disorder. We call these features "molecular recognition elements" (MoREs). Examples of MoREs bound to their partners can be found in the alpha-helix, beta-strand, polyproline II helix, or irregular secondary structure conformations, and in various mixtures of the four structural forms. Here we describe an algorithm that identifies regions having propensities to become alpha-helix-forming molecular recognition elements (alpha-MoREs) based on a discriminant function that indicates such regions while giving a low false-positive error rate on a large collection of structured proteins. Application of this algorithm to databases of genomics and functionally annotated proteins indicates that alpha-MoREs are likely to play important roles protein-protein interactions involved in signaling events.

Binding Sites↗

PubMed2005

Addressing the intrinsic disorder bottleneck in structural proteomics.

The Center for Eukaryotic Structural Genomics (CESG), as part of the Protein Structure Initiative (PSI), has established a high-throughput structure determination pipeline focused on eukaryotic proteins. NMR spectroscopy is an integral part of this pipeline, both as a method for structure determinations and as a means for screening proteins for stable structure. Because computational approaches have estimated that many eukaryotic proteins are highly disordered, about 1 year into the project, CESG began to use an algorithm (the Predictor of Naturally Disordered Regions, PONDR to avoid proteins that were likely to be disordered. We report a retrospective analysis of the effect of this filtering on the yield of viable structure determination candidates. In addition, we have used our current database of results on 70 protein targets from Arabidopsis thaliana and 1 from Caenorhabditis elegans, which were labeled uniformly with nitrogen-15 and screened for disorder by NMR spectroscopy, to compare the original algorithm with 13 other approaches for predicting disorder from sequence. Our study indicates that the efficiency of structural proteomics of eukaryotes can be improved significantly by removing targets predicted to be disordered by an algorithm chosen to provide optimal performance.

Algorithms↗

PubMed2005

Comparing and combining predictors of mostly disordered proteins.

Intrinsically disordered proteins and regions carry out varied and vital cellular functions. Proteins with disordered regions are especially common in eukaryotic cells, with a subset of these proteins being mostly disordered, e.g., with more disordered than ordered residues. Two distinct methods have been previously described for using amino acid sequences to predict which proteins are likely to be mostly disordered. These methods are based on the net charge-hydropathy distribution and disorder prediction score distribution. Each of these methods is reexamined, and the prediction results are compared herein. A new prediction method based on consensus is described. Application of the consensus method to whole genomes reveals that approximately 4.5% of Yersinia pestis, 5% of Escherichia coli K12, 6% of Archaeoglobus fulgidus, 8% of Methanobacterium thermoautotrophicum, 23% of Arabidopsis thaliana, and 28% of Mus musculus proteins are mostly disordered. The unexpectedly high frequency of mostly disordered proteins in eukaryotes has important implications both for large-scale, high-throughput projects and also for focused experiments aimed at determination of protein structure and function.

Algorithms↗