Abstract
MOTIVATION: The mutation of amino acids often impacts protein function and structure. Mutations without negative effect sustain evolutionary pressure. We study a particular aspect of structural robustness with respect to mutations: regular protein secondary structure and natively unstructured (intrinsically disordered) regions. Is the formation of regular secondary structure an intrinsic feature of amino acid sequences, or is it a feature that is lost upon mutation and is maintained by evolution against the odds? Similarly, is disorder an intrinsic sequence feature or is it difficult to maintain? To tackle these questions, we in silico mutated native protein sequences into random sequence-like ensembles and monitored the change in predicted secondary structure and disorder. RESULTS: We established that by our coarse-grained measures for change, predictions and observations were similar, suggesting that our results were not biased by prediction mistakes. Changes in secondary structure and disorder predictions were linearly proportional to the change in sequence. Surprisingly, neither the content nor the length distribution for the predicted secondary structure changed substantially. Regions with long disorder behaved differently in that significantly fewer such regions were predicted after a few mutation steps. Our findings suggest that the formation of regular secondary structure is an intrinsic feature of random amino acid sequences, while the formation of long-disordered regions is not an intrinsic feature of proteins with disordered regions. Put differently, helices and strands appear to be maintained easily by evolution, whereas maintaining disordered regions appears difficult. Neutral mutations with respect to disorder are therefore very unlikely.
Original language | English (US) |
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Pages (from-to) | 625-631 |
Number of pages | 7 |
Journal | Bioinformatics |
Volume | 26 |
Issue number | 5 |
DOIs | |
State | Published - Jan 16 2010 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: The authors would like to thank the following for valuable discussions: Zsuzsanna Dosztanyi (Eötvös Loránd University Budapest and Columbia University in the City of New York), Dietlind Gerloff (UCSC Santa Cruz), Marco Punta (Columbia University in the City of New York and TUM Munich), Reinhard Schneider (EMBL Heidelberg), Anna Tramontano (La Sapienza Rome and KAUST); the anonymous reviewers for very constructive and helpful suggestions that helped shaping this work; and also to all those who deposit their experimental data in public databases and to those who maintain these databases, in particular to those who contribute to PDB and DisProt.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.