Dataset Information

How sticky are our proteins? Quantifying hydrophobicity of the human proteome.

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 Bioinformatics Advances online.

SUBMITTER: van Gils JHM

PROVIDER: S-EPMC9710682 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

How sticky are our proteins? Quantifying hydrophobicity of the human proteome.

van Gils Juami Hermine Mariama JHM Gogishvili Dea D van Eck Jan J Bouwmeester Robbin R van Dijk Erik E Abeln Sanne S

Bioinformatics advances 20220125 1

<h4>Summary</h4>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 hyd ...[more]

PMID: 36699344

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Project description:The concept of hydrophobicity is critical to our understanding of the principles of membrane protein (MP) folding, structure, and function. In the last decades, several groups have derived hydrophobicity scales using both experimental and statistical methods that are optimized to mimic certain natural phenomena as closely as possible. The present work adds to this toolset the first knowledge-based scale that unifies the characteristics of both alpha-helical and beta-barrel multispan MPs. This unified hydrophobicity scale (UHS) distinguishes between amino acid preference for solution, transition, and trans-membrane states. The scale represents average hydrophobicity values of amino acids in folded proteins, irrespective of their secondary structure type. We furthermore present the first knowledge-based hydrophobicity scale for mammalian alpha-helical MPs (mammalian hydrophobicity scale--MHS). Both scales are particularly useful for computational protein structure elucidation, for example as input for machine learning techniques, such as secondary structure or trans-membrane span prediction, or as reference energies for protein structure prediction or protein design. The knowledge-based UHS shows a striking similarity to a recent experimental hydrophobicity scale introduced by Hessa and coworkers (Hessa T et al., Nature 2007;450:U1026-U1032). Convergence of two very different approaches onto similar hydrophobicity values consolidates the major differences between experimental and knowledge-based scales observed in earlier studies. Moreover, the UHS scale represents an accurate absolute free energy measure for folded, multispan MPs--a feature that is absent from many existing scales. The utility of the UHS was demonstrated by analyzing a series of diverse MPs. It is further shown that the UHS outperforms nine established hydrophobicity scales in predicting trans-membrane spans along the protein sequence. The accuracy of the present hydrophobicity scale profits from the doubling of the number of integral MPs in the PDB over the past four years. The UHS paves the way for an increased accuracy in the prediction of trans-membrane spans.

Dataset Information

How sticky are our proteins? Quantifying hydrophobicity of the human proteome.

Summary

Availability and implementation

Supplementary information

Publications

How sticky are our proteins? Quantifying hydrophobicity of the human proteome.

Similar Datasets

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