Comparing and combining predictors of mostly disordered proteins.

By Christopher J. Oldfield, Yugong Cheng, Marc S. Cortese, C. Brown, Vladimir N Uversky, A. Keith Dunker. Biochemistry, 2005

513 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ca64721a616d555859120b0076407905bec8350d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

1. Vladimir N Uversky
2. Lukasz Kurgan
3. A. Keith Dunker
4. Burkhard Rost
5. Christopher J. Oldfield
6. Avner Schlessinger
7. Predrag Radivojac
8. Zoran Obradovic

In Molecular Biology

1. Vladimir N Uversky
2. Lukasz Kurgan
3. A. Keith Dunker
4. Burkhard Rost
5. Fanchi Meng
6. Avner Schlessinger
7. Christopher J. Oldfield
8. Zhenling Peng

Citations in the corpus

• Intrinsic Disorder Is a Common Feature of Hub Proteins from Four Eukaryotic Interactomes (2006, methodology): “Predictions of wholly ordered and wholly disordered proteins (Table 3) were made as previously described [25].”
• Intrinsically disordered proteins in human diseases: introducing the D2 concept. (2008, background): “The crucial role of IDPs in signaling is further supported by the fact that eukaryotic proteomes, with their extensive interaction networks, are highly enriched in IDPs, relative to bacteria and archaea (42, 97, 155).”
• Length-dependent prediction of protein intrinsic disorder (2006, background): “…applications, e.g. designing protein structure-function experiments [1,30], understanding the roles of disorder in cell-signalling and cancer-related proteins [31], improving prediction of protein phosphorylation sites [32], and improving the through-put of structural genomics pipelines [25,33].”
• Natively Unstructured Loops Differ from Other Loops (2007, background): “Moreover, this small fraction is not representative, as many unstructured regions described experimentally are missing from existing databases and are not identified by prediction methods [11].”
• Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions (2017, methodology): “There are several predictors of MoRFs including alpha-MoRFpred [124, 125], MoRFpred [126], MFSPSSMpred [127], MoRFChiBi [128], MoRFChiBiWeb [129], fMoRFpred [130], retro-MoRF [131], and DISOPRED3 [61].”
• Analysis of molecular recognition features (MoRFs). (2006, background): “This increased prediction of disorder in eukaryotes compared with the prokaryotes or the archaea has been hypothesized to be a consequence of the increased need for cell signaling and regulation.(15,22,24,25) The functional importance of protein disorder is further emphasized by its role in various ”
• Prediction of intrinsic disorder and its use in functional proteomics. (2007, methodology): “Another binary classifier is the cumulative distribution functions (CDF) analysis of disorder scores, which separates ordered and disordered sequences based on the per-residue disorder score retrieved by PONDR VLXT, and the optimal boundary (57,58).”
• Natively unstructured regions in proteins identified from contact predictions (2007, background): “However, many unstructured regions are neither covered by DisProt, nor by existing prediction methods ( Oldfield, et al., 2005 ).”
• Intrinsically Disordered Proteins and Their “Mysterious” (Meta)Physics (2019, background): “The natural abundance of intrinsic disorder was later supported by multiple comprehensive computational studies [3, 6, 17, 24, 44, 45], which are illustrated by Figure 1, where the correlation between the intrinsic disorder content and proteome size is shown for 3,484 viral, archaeal, bacterial, and”
• A decade and a half of protein intrinsic disorder: Biology still waits for physics (2013, unknown): “90 For example, based on the analysis of the conformational equilibrium of coarse-grained polypeptides as a function of sequence hydrophobicity, charge, and length it has been concluded that the variations in sequence hydrophobicity and charge define a coil-to-globule transition comparable to that s”
• Showing your ID: intrinsic disorder as an ID for recognition, regulation and cell signaling (2005, methodology): “…based on their amino acid sequence [the net charge-hydropathy distribution (Uversky et al., 2000) and the distribution of disorder prediction score derived from PONDR1 VL-XT (Romero et al., 1997a,b, 2001; Li et al., 1999b)] confirmed and enhanced these observations (Oldfield et al., 2005a).”