Prediction of Protein Binding Regions in Disordered Proteins

By Bálint Mészáros, István Simon, Zsuzsanna Dosztányi. 2009

587 citations recorded by the source corpus.

Many disordered proteins function via binding to a structured partner and undergo a disorder-to-order transition. The coupled folding and binding can confer several functional advantages such as the precise control of binding specificity without increased affinity. Additionally, the inherent flexibility allows the binding site to adopt various conformations and to bind to multiple partners. These features explain the prevalence of such binding elements in signaling and regulatory processes. In this work, we report ANCHOR, a method for the prediction of disordered binding regions. ANCHOR relies on the pairwise energy estimation approach that is the basis of IUPred, a previous general disorder prediction method. In order to predict disordered binding regions, we seek to identify segments that are in disordered regions, cannot form enough favorable intrachain interactions to fold on their own, and are likely to gain stabilizing energy by interacting with a globular protein partner. The performance of ANCHOR was found to be largely independent from the amino acid composition and adopted secondary structure. Longer binding sites generally were predicted to be segmented, in agreement with available experimentally characterized examples. Scanning several hundred proteomes showed that the occurrence of disordered binding sites increased with the complexity of the organisms even compared to disordered regions in general. Furthermore, the length distribution of binding sites was different from disordered protein regions in general and was dominated by shorter segments. These results underline the importance of disordered proteins and protein segments in establishing new binding regions. Due to their specific biophysical properties, disordered binding sites generally carry a robust sequence signal, and this signal is efficiently captured by our method. Through its generality, ANCHOR opens new ways to study the essential functional sites of disordered proteins.

Subfields: Molecular Biology

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Citations in the corpus

IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding (2018, methodology): “Besides the general disorder tendency, two additional terms were also incorporated into the method that estimate the energy associated with interaction with a globular protein and with the local disordered sequence environment (28).”
Sequence-based determinants and prediction of fuzzy interactions in protein complexes. (2020, methodology): “Current algorithms only address the problem of disorder-to-order transitions of linear peptides [24 e 26], but cannot characterize the continuum of interaction modes.”
DFLpred: High-throughput prediction of disordered flexible linker regions in protein sequences (2016, unknown): “For commercial re-use, please contact journals.permissions@oup.com Khan et al., 2013; Malhis and Gsponer, 2015; Meszaros et al., 2009; Peng and Kurgan, 2015; Yan et al., 2015) and RNA and DNA binding (Peng and Kurgan, 2015).”
Analyzing Protein Disorder with IUPred2A (2020, methodology): “The ANCHOR method is based on a similar biophysical approach and recognizes specific regions that undergo disorder-to-order transition upon binding (Mészáros, Simon, & Dosztányi, 2009).”
ProViz—a web-based visualization tool to investigate the functional and evolutionary features of protein sequences (2016, unknown): “Complementary computed results from bioinformatics tools are also presented, including disorder predictions (20,21), binding site predictions (37), SLiM consensus matches (9) and residue relative conservation scores (38,39).”
p53 Proteoforms and Intrinsic Disorder: An Illustration of the Protein Structure–Function Continuum Concept (2016, methodology): “Positions of the disorder-based binding sites (molecular recognition features, MoRFs) found by the ANCHOR algorithm [190,191] are shown as gray shaded areas.”
Intrinsically Semi-disordered State and Its Role in Induced Folding and Protein Aggregation (2013, methodology): “To quantify the relation between semi-disorder and induced folding, we employ the ANCHOR dataset [22] that is a collection of binding regions in disordered proteins that fold upon binding.”
Computational identification of MoRFs in protein sequences (2015, background): “…and MoRFs in protein sequences including MoRFpred (Disfani et al., 2012), MFSPSSMpred (Fang et al., 2013), PepBindPred (Khan et al., 2013); ANCHOR (Mészá ros et al., 2009), SLiMpred (Mooney et al., 2012), SLiMDisc (Davey et al., 2006), SLiMFinder (Edwards et al., 2007) and Retro-MoRFs (Xue et…”
MobiDB 3.0: more annotations for intrinsic disorder, conformational diversity and interactions in proteins (2017, background): “Anchor predicts binding regions located in disordered proteins, providing LIP annotations for all proteins in the database.”