Abstract
Contact and support
Need help, have a question, or want to contact the ResearchHub team?
© 2026 ResearchHub. Built for responsible scholarly connection.
Mohamed Fawzy, Joseph A. Marsh
Abstract
Authors
Institutions
No ROR-resolved institution is linked to this work yet.
Provenance
crossref
Confidence 100%
pubmed
Confidence 98%
europepmc
Confidence 96%
unpaywall
Confidence 95%
doaj
Confidence 92%
datacite
Confidence 0%
No local reference links have been materialized yet.
Conformations of intrinsically disordered proteins are influenced by linear sequence distributions of oppositely charged residues
10.1073/pnas.1304749110 · 2013
Roles, Characteristics, and Analysis of Intrinsically Disordered Proteins: A Minireview
2020
Functions of intrinsically disordered proteins through evolutionary lenses
10.1016/bs.pmbts.2021.06.017 · 2021
Tutorial: a guide for the selection of fast and accurate computational tools for the prediction of intrinsic disorder in proteins
10.1038/s41596-023-00876-x · 2023
Intrinsic protein disorder uncouples affinity from binding specificity
10.1002/pro.4455 · 2022
dbPTM: an information repository of protein post-translational modification
2006
p53 Proteoforms and Intrinsic Disorder: An Illustration of the Protein Structure-Function Continuum Concept
10.3390/ijms17111874 · 2016
Protein intrinsic disorder and structure-function continuum
10.1016/bs.pmbts.2019.05.003 · 2019
Intrinsically disordered proteins in human diseases: introducing the D2 concept
10.1146/annurev.biophys.37.032807.125924 · 2008
Intrinsically disordered protein
10.1016/s1093-3263(00)00138-8 · 2001
What does it mean to be natively unfolded?
10.1046/j.0014-2956.2001.02649.x · 2002
Effects of Sequence Composition, Patterning and Hydrodynamics on the Conformation and Dynamics of Intrinsically Disordered Proteins
10.3390/ijms24021444 · 2023
Guidelines for releasing a variant effect predictor
10.1186/s13059-025-03572-z · 2025
Disease-associated mutations disrupt functionally important regions of intrinsic protein disorder
10.1371/journal.pcbi.1002709 · 2012
Understanding the heterogeneous performance of variant effect predictors across human protein-coding genes
10.1038/s41598-024-76202-6 · 2024
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · 2021
Highly accurate protein structure prediction for the human proteome
10.1038/s41586-021-03828-1 · 2021
Systematic identification of conditionally folded intrinsically disordered regions by AlphaFold2
10.1073/pnas.2304302120 · 2023
AlphaFold2: A Role for Disordered Protein/Region Prediction?
10.3390/ijms23094591 · 2022
Intrinsic protein disorder and conditional folding in AlphaFoldDB
10.1002/pro.4466 · 2022
Critical assessment of protein intrinsic disorder prediction (CAID) - Results of round 2
10.1002/prot.26582 · 2023
Modularity of intrinsic disorder in the human proteome
10.1002/prot.22504 · 2010
ClinVar: public archive of relationships among sequence variation and human phenotype
10.1093/nar/gkt1113 · 2014
The mutational constraint spectrum quantified from variation in 141,456 humans
10.1038/s41586-020-2308-7 · 2020
Decoding Missense Variants by Incorporating Phase Separation via Machine Learning
10.1038/s41467-024-52580-3 · 2024
A Comprehensive Report of Intrinsically Disordered Regions in Inherited Retinal Diseases
10.3390/genes14081601 · 2023
Protein-Protein Interactions Mediated by Intrinsically Disordered Protein Regions Are Enriched in Missense Mutations
10.3390/biom10081097 · 2020
Intrinsic disorder in cell-signaling and cancer-associated proteins
10.1016/s0022-2836(02)00969-5 · 2002
Single-point mutations in disordered proteins: Linking sequence, ensemble, and function
10.1016/j.sbi.2025.102987 · 2025
Transcription Factors Activate Genes through the Phase-Separation Capacity of Their Activation Domains
10.1016/j.cell.2018.10.042 · 2018
Conformational ensembles of the human intrinsically disordered proteome
10.1038/s41586-023-07004-5 · 2024
Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure
10.1038/s41467-022-31686-6 · 2022
Diverse Molecular Mechanisms Underlying Pathogenic Protein Mutations: Beyond the Loss-of-Function Paradigm
10.1146/annurev-genom-111221-103208 · 2022
Proteome-scale prediction of molecular mechanisms underlying dominant genetic diseases
10.1371/journal.pone.0307312 · 2024
Transcription factor haploinsufficiency: when half a loaf is not enough
10.1172/jci0215043 · 2002
Intrinsically disordered proteins in cellular signalling and regulation
10.1038/nrm3920 · 2015
BRAF V600E mutation-specific antibody: A review
10.1053/j.semdp.2015.02.010 · 2015
Mutations of the BRAF gene in human cancer
10.1038/nature00766 · 2002
Somatic histone H3 alterations in pediatric diffuse intrinsic pontine gliomas and non-brainstem glioblastomas
10.1038/ng.1102 · 2012
A cellular model provides insights into the pathogenicity of the oncogenic FOXL2 somatic variant p.Cys134Trp
10.1038/s41416-024-02613-x · 2024
Index for rating diagnostic tests
10.1002/1097-0142(1950)3:1<32::aid-cncr2820030106>3.0.co;2-3 · doi-reference
Three reasons protein disorder analysis makes more sense in the light of collagen
10.1002/pro.2913 · doi-reference
The Pfam protein families database: embracing AI/ML
10.1093/nar/gkae997 · doi-reference
Improved pathogenicity prediction for rare human missense variants
10.1016/j.ajhg.2021.08.012 · doi-reference
Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology
10.1038/gim.2015.30 · doi-reference
Deep learning tools predict variants in disordered regions with lower sensitivity
10.1186/s12864-025-11534-9 · doi-reference
Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria
10.1016/j.ajhg.2022.10.013 · doi-reference
GEMME: A Simple and Fast Global Epistatic Model Predicting Mutational Effects
10.1093/molbev/msz179 · doi-reference
Genome-wide prediction of disease variant effects with a deep protein language model
10.1038/s41588-023-01465-0 · doi-reference
Cross-protein transfer learning substantially improves disease variant prediction
10.1186/s13059-023-03024-6 · doi-reference
LIST-S2: taxonomy based sorting of deleterious missense mutations across species
10.1093/nar/gkaa288 · doi-reference
Accurate proteome-wide missense variant effect prediction with AlphaMissense
10.1126/science.adg7492 · doi-reference
The evaluation of tools used to predict the impact of missense variants is hindered by two types of circularity
10.1002/humu.22768 · doi-reference
Variant effect predictor correlation with functional assays is reflective of clinical classification performance
10.1186/s13059-025-03575-w · doi-reference