Evolutionary aspects in evaluating mutations in the melanocortin 4 receptor
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vor 17 Jahren
More than 70 missense mutations have been identified in the human
melanocortin 4 receptor (MC4R), and many of them have been
associated with obesity. In a number of cases, the causal link
between mutations in MC4R and obesity is controversially discussed.
Here, we mined evolution as an additional source of structural
information that may help to evaluate the functional relevance of
naturally occurring variations in MC4R. The sequence information of
more than 60 MC4R orthologs enabled us to identify residues that
are important for maintaining receptor function. More than 90% of
all inactivating mutations found in obese patients were located at
amino acid positions that are highly conserved during 450 million
years of MC4R evolution in vertebrates. However, for a reasonable
number of MC4R variants, we found no correlation between structural
conservation of the mutated position and the reported functional
consequence. By re-evaluating selected mutations in the MC4R, we
demonstrate the usefulness of combining functional and evolutionary
approaches.
melanocortin 4 receptor (MC4R), and many of them have been
associated with obesity. In a number of cases, the causal link
between mutations in MC4R and obesity is controversially discussed.
Here, we mined evolution as an additional source of structural
information that may help to evaluate the functional relevance of
naturally occurring variations in MC4R. The sequence information of
more than 60 MC4R orthologs enabled us to identify residues that
are important for maintaining receptor function. More than 90% of
all inactivating mutations found in obese patients were located at
amino acid positions that are highly conserved during 450 million
years of MC4R evolution in vertebrates. However, for a reasonable
number of MC4R variants, we found no correlation between structural
conservation of the mutated position and the reported functional
consequence. By re-evaluating selected mutations in the MC4R, we
demonstrate the usefulness of combining functional and evolutionary
approaches.
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