ANCHOR: web server for predicting protein binding regions in disordered proteins

By Zsuzsanna Dosztányi, Bálint Mészáros, István Simon. 2009

602 citations recorded by the source corpus.

Summary: ANCHOR is a web-based implementation of an original method that takes a single amino acid sequence as an input and predicts protein binding regions that are disordered in isolation but can undergo disorder-to-order transition upon binding. The server incorporates the result of a general disorder prediction method, IUPred and can carry out simple motif searches as well. Availability: The web server is available at http://anchor.enzim.hu. The program package is freely available for academic users. Contact: zsuzsa@enzim.hu

Subfields: Materials Chemistry, Molecular Biology, Renewable Energy, Sustainability and the Environment

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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, neutral): “The first publicly available method developed to recognize disordered binding regions was ANCHOR (28,29).”
MFSPSSMpred: identifying short disorder-to-order binding regions in disordered proteins based on contextual local evolutionary conservation (2013, neutral): “So far, because of the limited number of experimentally validated MoRFs, only four custom-built tools for predicting MoRFs are available: α-MoRF-PredI [5] and α-MoRF-PredII [6] are neural network-based predictors aimed at predicting α-MoRFs; ANCHOR [7] concentrates on the prediction of MoRFs which b”
p53 Proteoforms and Intrinsic Disorder: An Illustration of the Protein Structure–Function Continuum Concept (2016, positive): “Positions of the disorder-based binding sites (molecular recognition features, MoRFs) found by the ANCHOR algorithm [190,191] are shown as gray shaded areas.”
Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (2012, positive): “bilizing interactions upon binding to another globular protein as predicted by the ANCHOR package.(1483) A combination of”
DFLpred: High-throughput prediction of disordered flexible linker regions in protein sequences (2016, positive): “They include methods that address protein binding (Disfani et al., 2012; Dosztanyi et al., 2009; Fang et al., 2013; Jones and Cozzetto, 2014; VC The Author 2016.”
A highly conserved program of neuronal microexons is misregulated in autistic brains (2014, positive): “(G) Percent of residues overlapping binding motifs predicted by ANCHOR.”
MetaDisorder: a meta-server for the prediction of intrinsic disorder in proteins (2012, positive): “There are certain classes of disorder for which specialized predictors have been developed, for instance short vs. long disorder [28,29], and prediction of protein-binding regions in disordered proteins [52].”
Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions (2017, positive): “The first class are the methods that predict generic disordered protein binding regions which include ANCHOR [106, 120] and DisoRDPbind [121].”
MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins (2012, neutral): “Availability: http://biomine.ece.ualberta.ca/MoRFpred/; http://biomine.ece.ualberta.ca/MoRFpred/Supplement.pdf Contact: lkurgan@ece.ualberta.ca Supplementary information: Supplementary data are available at Bioinformatics online.”
Prediction of protein disorder based on IUPred (2018, positive): “ANCHOR enabled the prediction of essential functional sites of disordered proteins engaged in specific protein binding, offering an additional way to use the energy estimation methods to characterize disordered regions.(32,35)”
A comparison of algorithms for the identification of specimens using DNA barcodes: examples from gymnosperms (2007, neutral): “Methods to construct diagnoses from sequence data have been proposed recently (Borneman et al., 2001; Rash and Gusﬁeld, 2002; DasGupta et al., 2005a,b; Gibbs et al., 2005).”