Correlated mutation analysis

Natural mutation of amino acids in the core of a protein can stabilize the same fold with different complementary amino acid types, but they can also cause a different fold of that particular portion. If the sequence identity is lower than 30% it is much more difficult to identify a homologous structure. Other strategies like secondary structure predictions combined with knowledge-based rules about reciprocal exchange of residues are necessary. If there is a reliable assumption for common fold then it is possible to identify intra- and intermolecular interacting residues by search for correlated complementary mutations of residues by correlated mutation analysis, CMA (see e.g., http //www.fmp-berlin.de/SSFA). 

Although the evolutionary trace method applied to GPCRs (175,185) fails to detect any residues responsible for the subtype-specific heterodimerizafion that has recently been demonstrated for opioid (96), somatostatin (106), and chemokine (98) receptors, correlated mutation analysis had already been demonstrated to be able to identify useful details of molecular specificity (184). Thus, the molecular basis of specificity was hypothesized to reside in outward (i.e., lipid) facing residues of TM5 and TM6 that exhibited evolutionarily correlated mutations and differed between receptor subtypes (184) in the case of dimerization. In the case of oligomers, the key interface between different subtypes was suggested to be the 2,3-interface (152) rather than the 5,6-interface. 

Correlated mutation analysis does not yield a precise and exhaustive enumeration of all the interacting residues in a complex. Rather, tests have shown (177) that the result is a definition of the neighborhood of interacting regions. This makes the careful construction of explicit 3D models of GPCR homodimers, using the information derived... 

Oliveira, L Paiva, A. C., and Vriend, G. (2002) Correlated mutation analysis on very large sequence families. Chembiochem 3,1010-1017. 

Filizola, M., Olmea, O., and Weinstein, H. (2002) Using correlated mutation analysis to predict the heterodimerization interface of GPCRs. Biophys. J. 82, 2307. (Part 2302 Jan 2002.)... 

Singer, M. S., Oliveira, L., Vriend, G and Shepherd, G. M. (1995) Potential ligand-binding residues in rat olfactory receptors identified by correlated mutation analysis. Recept. Channels 3, 89-95. 

Figure 6.3. G Protein-coupled receptor retrieved from GPCRDB.Seven transmembrane segment receptor for serotonin retrieved from GPCRDB is visualized in a snake-like plot. The colored groups of residues show a correlated behavior as determined by correlated mutation analysis (CMA). The colored positions are hyperlinked to their corresponding residue locations in the multiple sequence alignments.

S =m is the number of contacts predicted within m residues of a correctly predicted contact. Correlated mutation analysis is from the CASP3 predictions of Ortiz et. al. [133],... 

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