ArticleBioinformatics advances2022
How sticky are our proteins? Quantifying hydrophobicity of the human proteome.
Article in Bioinformatics advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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Who cites it
19 citing papers in PubMed.
- The barcoded binding assay: Multiplexed profiling of chaperone binding selectivity for hydrophobic substrates.Cell stress & chaperones · 2026Article
- West Nile virus and Zika virus infections induce aggresome formation in human neural progenitor and A549 cells.Journal of virology · 2026Article
- Predicting Aberrant Fc-fusion Protein Pharmacokinetics from In Silico Structural Properties and Physiologically Based Pharmacokinetic (PBPK) Modeling.The AAPS journal · 2026Article
- Parkinson's disease-specific α-Synuclein variants potentially drive Lewy body formation by engaging in promiscuous and non-functional interactions.Communications biology · 2026Article
- Effect of acyl donors on EGCG esterification reaction catalyzed by Lipase "Amano" 30SD based on molecular dynamics analysis.Current research in food science · 2026Article
- Surface-modified protein crowders influence mutant huntingtin exon 1 aggregation via crowding effects, crowder association, and crowder solution stability.Protein science : a publication of the Protein Society · 2025Article
- InteracTor: Feature engineering and explainable AI for profiling protein structure-interaction-function relationships.PLoS computational biology · 2025Article
- The Structural Proteins of Thermophilic Bacteriophage P23-77: Expression and Characterization.International journal of molecular sciences · 2025Article
- Plasmonic Single-Molecule Affinity Detection at 10Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Computational electrostatic engineering of nanobodies for enhanced SARS-CoV-2 receptor binding domain recognition.Frontiers in molecular biosciences · 2025Article
- Electric Field Cycling of Physisorbed Antibodies Reduces Biolayer Polarization Dispersion.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Creating Chemiluminescence Signature Arrays Coupled with Machine Learning for Alzheimer's Disease Serum Diagnosis.Research (Washington, D.C.) · 2025Article
- Bacterial nucleoid is a riddle wrapped in a mystery inside an enigma.Journal of bacteriology · 2024Review
- PatchProt: hydrophobic patch prediction using protein foundation models.Bioinformatics advances · 2024Article
- Proteome encoded determinants of protein sorting into extracellular vesicles.Journal of extracellular biology · 2024Article
- Associating Compositional, Nutritional and Techno-Functional Characteristics of Faba Bean (Foods (Basel, Switzerland) · 2023Article
- Ten quick tips for sequence-based prediction of protein properties using machine learning.PLoS computational biology · 2022Article
- ProteinGLUE multi-task benchmark suite for self-supervised protein modeling.Scientific reports · 2022Article
- Multi-Omics Interdisciplinary Research Integration to Accelerate Dementia Biomarker Development (MIRIADE).Frontiers in neurology · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Summary: Proteins tend to bury hydrophobic residues inside their core during the folding process to provide stability to the protein structure and to prevent aggregation. Nevertheless, proteins do expose some 'sticky' hydrophobic residues to the solvent. These residues can play an important functional role, e.g. in protein-protein and membrane interactions. Here, we first investigate how hydrophobic protein surfaces are by providing three measures for surface hydrophobicity: the total hydrophobic surface area, the relative hydrophobic surface area and-using our MolPatch method-the largest hydrophobic patch. Secondly, we analyze how difficult it is to predict these measures from sequence: by adapting solvent accessibility predictions from NetSurfP2.0, we obtain well-performing prediction methods for the THSA and RHSA, while predicting LHP is more challenging. Finally, we analyze implications of exposed hydrophobic surfaces: we show that hydrophobic proteins typically have low expression, suggesting cells avoid an overabundance of sticky proteins. Availability and implementation: The data underlying this article are available in GitHub at https://github.com/ibivu/hydrophobic_patches. Supplementary information: Supplementary data are available at
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.