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Cellular and Molecular Life Sciences

, Volume 68, Issue 16, pp 2711–2737 | Cite as

Fractal symmetry of protein interior: what have we learned?

  • Anirban Banerji
  • Indira Ghosh
Review
First Online:
Received:
Revised:
Accepted:

Abstract

The application of fractal dimension-based constructs to probe the protein interior dates back to the development of the concept of fractal dimension itself. Numerous approaches have been tried and tested over a course of (almost) 30 years with the aim of elucidating the various facets of symmetry of self-similarity prevalent in the protein interior. In the last 5 years especially, there has been a startling upsurge of research that innovatively stretches the limits of fractal-based studies to present an array of unexpected results on the biophysical properties of protein interior. In this article, we introduce readers to the fundamentals of fractals, reviewing the commonality (and the lack of it) between these approaches before exploring the patterns in the results that they produced. Clustering the approaches in major schools of protein self-similarity studies, we describe the evolution of fractal dimension-based methodologies. The genealogy of approaches (and results) presented here portrays a clear picture of the contemporary state of fractal-based studies in the context of the protein interior. To underline the utility of fractal dimension-based measures further, we have performed a correlation dimension analysis on all of the available non-redundant protein structures, both at the level of an individual protein and at the level of structural domains. In this investigation, we were able to separately quantify the self-similar symmetries in spatial correlation patterns amongst peptide–dipole units, charged amino acids, residues with the π-electron cloud and hydrophobic amino acids. The results revealed that electrostatic environments in the interiors of proteins belonging to ‘α/α toroid’ (all-α class) and ‘PLP-dependent transferase-like’ domains (α/β class) are highly conducive. In contrast, the interiors of ‘zinc finger design’ (‘designed proteins’) and ‘knottins’ (‘small proteins’) were identified as folds with the least conducive electrostatic environments. The fold ‘conotoxins’ (peptides) could be unambiguously identified as one type with the least stability. The same analyses revealed that peptide–dipoles in the α/β class of proteins, in general, are more correlated to each other than are the peptide–dipoles in proteins belonging to the all-α class. Highly favorable electrostatic milieu in the interiors of TIM-barrel, α/β-hydrolase structures could explain their remarkably conserved (evolutionary) stability from a new light. Finally, we point out certain inherent limitations of fractal constructs before attempting to identify the areas and problems where the implementation of fractal dimension-based constructs can be of paramount help to unearth latent information on protein structural properties.

Keywords

Fractal Dimension Aromatic Amino Acid Correlation Dimension Hydrophobic Amino Acid Fractal Kinetic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgments

One of the authors, Anirban, would like to thank the COE-DBT scheme, Govt. of India, for supporting him during the tenure of this work. He would also like to thank Charudatta Navare for various technical help and Professor Paul Bourke for permitting him to use the self-similarity figures.

Supplementary material

18_2011_722_MOESM1_ESM.xls (24 kb)
Supplementary material 1 (XLS 24 kb)

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Copyright information

© Springer Basel AG 2011

Authors and Affiliations

  1. 1.Bioinformatics CentreUniversity of PunePuneIndia
  2. 2.School of Information TechnologyJawaharlal Nehru UniversityNew DelhiIndia
  3. 3.School of Computational & Integrative SciencesJawaharlal Nehru UniversityNew DelhiIndia

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