Literature DB >> 19052795

Spatial autocorrelation of amino Acid replacement rates in the vasopressin receptor family.

Lorraine Marsh1.   

Abstract

Evolutionary rates of sites can be independent of one another or correlated in some fashion. Significant spatial autocorrelation was observed for site amino acid replacement rates in vasopressin receptor family proteins (VPRs). Spatial autocorrelation of rates is the propensity of residues to lie near other residues of similar rate in the folded protein structure. Optimal correlation occurred at a distance suggesting that residues in contact had correlated rates. As another way to study the same phenomenon, VPR was partitioned into >40 x 10 A(3) contiguous spatial clusters for amino acid replacement rate estimation. Partitioning was done without preconception of functional regions of the protein and with a random partition control. Cluster rates exhibited an overdispersed distribution suggesting that rates were not randomly distributed in the spatial partitions. In tests, cluster partitioning improved maximum likelihood and Bayesian likelihood models for VPR evolution. Spatial clusters with outlier rates, or lineage-specific clusters differing in rate, proved to contain VPR features likely to be under selection. Thus the spatial autocorrelation observed is probably not just a statistical finding, but likely has an evolutionary basis in protein function.

Mesh:

Substances:

Year:  2008        PMID: 19052795     DOI: 10.1007/s00239-008-9183-4

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  31 in total

1.  The Protein Data Bank.

Authors:  H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  The pattern of amino acid replacements in alpha/beta-barrels.

Authors:  Antony M Dean; Claudia Neuhauser; Elise Grenier; G Brian Golding
Journal:  Mol Biol Evol       Date:  2002-11       Impact factor: 16.240

3.  Constitutively active mutants of rhodopsin.

Authors:  P R Robinson; G B Cohen; E A Zhukovsky; D D Oprian
Journal:  Neuron       Date:  1992-10       Impact factor: 17.173

4.  Regions of minimal structural variation among members of protein domain superfamilies: application to remote homology detection and modelling using distant relationships.

Authors:  Saikat Chakrabarti; R Sowdhamini
Journal:  FEBS Lett       Date:  2004-07-02       Impact factor: 4.124

5.  An evolutionary space-time model with varying among-site dependencies.

Authors:  Adi Stern; Tal Pupko
Journal:  Mol Biol Evol       Date:  2005-11-02       Impact factor: 16.240

6.  A gamma mixture model better accounts for among site rate heterogeneity.

Authors:  Itay Mayrose; Nir Friedman; Tal Pupko
Journal:  Bioinformatics       Date:  2005-09-01       Impact factor: 6.937

7.  Quantifying the impact of protein tertiary structure on molecular evolution.

Authors:  Sang Chul Choi; Asger Hobolth; Douglas M Robinson; Hirohisa Kishino; Jeffrey L Thorne
Journal:  Mol Biol Evol       Date:  2007-05-23       Impact factor: 16.240

8.  Assessing the impact of secondary structure and solvent accessibility on protein evolution.

Authors:  N Goldman; J L Thorne; D T Jones
Journal:  Genetics       Date:  1998-05       Impact factor: 4.562

Review 9.  Structure and function of G protein-coupled receptors.

Authors:  C D Strader; T M Fong; M R Tota; D Underwood; R A Dixon
Journal:  Annu Rev Biochem       Date:  1994       Impact factor: 23.643

Review 10.  Molecular evolution of neuropeptide receptors with regard to maintaining high affinity to their authentic ligands.

Authors:  Hyun Ju Cho; Sujata Acharjee; Mi Jin Moon; Da Young Oh; Hubert Vaudry; Hyuk Bang Kwon; Jae Young Seong
Journal:  Gen Comp Endocrinol       Date:  2006-12-30       Impact factor: 2.822

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.