Abstract

BackgroundPlant MADS domain proteins are involved in a variety of developmental processes for which their ability to form various interactions is a key requisite. However, not much is known about the structure of these proteins or their complexes, whereas such knowledge would be valuable for a better understanding of their function. Here, we analyze those proteins and the complexes they form using a correlated mutation approach in combination with available structural, bioinformatics and experimental data.ResultsCorrelated mutations are affected by several types of noise, which is difficult to disentangle from the real signal. In our analysis of the MADS domain proteins, we apply for the first time a correlated mutation analysis to a family of interacting proteins. This provides a unique way to investigate the amount of signal that is present in correlated mutations because it allows direct comparison of mutations in various family members and assessing their conservation. We show that correlated mutations in general are conserved within the various family members, and if not, the variability at the respective positions is less in the proteins in which the correlated mutation does not occur. Also, intermolecular correlated mutation signals for interacting pairs of proteins display clear overlap with other bioinformatics data, which is not the case for non-interacting protein pairs, an observation which validates the intermolecular correlated mutations. Having validated the correlated mutation results, we apply them to infer the structural organization of the MADS domain proteins.ConclusionOur analysis enables understanding of the structural organization of the MADS domain proteins, including support for predicted helices based on correlated mutation patterns, and evidence for a specific interaction site in those proteins.

Highlights

  • Plant MADS domain proteins are involved in a variety of developmental processes for which their ability to form various interactions is a key requisite

  • Our results will be applied in prediction of protein interactions and scrutinized to obtain structural insight into the MADS proteins

  • The results presented here are for using a cutoff for the correlation coefficient of 0.4, but qualitatively they are similar for higher cutoffs

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Summary

Introduction

Plant MADS domain proteins are involved in a variety of developmental processes for which their ability to form various interactions is a key requisite. In protein-coding sequences, coevolution of residues can occur as compensation of changes in e.g. volume or charge, or because of the simultaneous involvement of residues in e.g. ligand binding This implies that residues which show such correlated mutations are expected to be located close to each other in the 3 D structure of a. A distinction can be made between pairwise correlation methods (which might be based on substitution matrix scores or related physicochemical van Dijk and van Ham BMC Genomics 2010, 11:607 http://www.biomedcentral.com/1471-2164/11/607 characteristics) [7,8] and information-theory based methods [9,10,11] The former seem to outperform the latter when using enrichment of residue pairs at short distances as a criterion [12,13]. Several correlated mutation measurements yield reasonable accuracy for intramolecular contact map prediction, the accuracy level drops in intermolecular contact prediction [14]

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