GPCRtm: An amino acid substitution matrix for the transmembrane region of class A G Protein-Coupled Receptors

BMC Bioinformatics

Santiago Rios¹  Marta F. Fernandez¹  Gianluigi Caltabiano¹  Mercedes Campillo¹  Leonardo Pardo¹  Angel Gonzalez¹ 

[1] Laboratori de Medicina Computacional, Unitat de Bioestadística, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, 08193, Spain

关键词: Membrane protein;    Evolution;    Transmembrane;    GPCR;    G protein-coupled receptors;    Amino acid substitution matrix;   

Others  :  1231819
DOI  :  10.1186/s12859-015-0639-4

 received in 2015-03-20, accepted in 2015-06-06,  发布年份 2015

【 摘 要 】

Background

Protein sequence alignments and database search methods use standard scoring matrices calculated from amino acid substitution frequencies in general sets of proteins. These general-purpose matrices are not optimal to align accurately sequences with marked compositional biases, such as hydrophobic transmembrane regions found in membrane proteins. In this work, an amino acid substitution matrix (GPCRtm) is calculated for the membrane spanning segments of the G protein-coupled receptor (GPCR) rhodopsin family; one of the largest transmembrane protein family in humans with great importance in health and disease.

Results

The GPCRtm matrix reveals the amino acid compositional bias distinctive of the GPCR rhodopsin family and differs from other standard substitution matrices. These membrane receptors, as expected, are characterized by a high content of hydrophobic residues with regard to globular proteins. On the other hand, the presence of polar and charged residues is higher than in average membrane proteins, displaying high frequencies of replacement within themselves.

Conclusions

Analysis of amino acid frequencies and values obtained from the GPCRtm matrix reveals patterns of residue replacements different from other standard substitution matrices. GPCRs prioritize the reactivity properties of the amino acids over their bulkiness in the transmembrane regions. A distinctive role is that charged and polar residues seem to evolve at different rates than other amino acids. This observation is related to the role of the transmembrane bundle in the binding of ligands, that in many cases involve electrostatic and hydrogen bond interactions. This new matrix can be useful in database search and for the construction of more accurate sequence alignments of GPCRs.

【 授权许可】

   
2015 Rios et al.

【 图 表 】

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【 参考文献 】

• [1]Pierce KL, Premont RT, Lefkowitz RJ. Seven-transmembrane receptors. Nat Rev Mol Cell Biol. 2002; 3(9):639-50.
• [2]Ji TH, Grossmann M, Ji I. G Protein-coupled Receptors. I. Diversity of Receptor-Ligand Interactions. J Biol Chem. 1998; 273:17299-302.
• [3]Liapakis G, Cordomi A, Pardo L. The G-protein coupled receptor family: actors with many faces. Curr Pharm Des. 2012; 18(2):175-85.
• [4]Kolakowski LF. GCRDb: a G-protein-coupled receptor database. Receptors Channels. 1994; 2(1):1-7.
• [5]Fredriksson R, Lagerstrom MC, Lundin LG, Schioth HB. The G-protein-coupled receptors in the human genome form five main families. Phylogenetic analysis, paralogon groups, and fingerprints. Mol Pharmacol. 2003; 63(6):1256-72.
• [6]Wise AGK, Rees S. Target validation of G-protein coupled receptors. Drug Discov Today. 2007; 7:235-46.
• [7]Rask-Andersen M, Masuram S, Schioth HB. The druggable genome: Evaluation of drug targets in clinical trials suggests major shifts in molecular class and indication. Annu Rev Pharmacol Toxicol. 2014; 54:9-26.
• [8]Imai T, Fujita N. Statistical sequence analyses of G-protein-coupled receptors: structural and functional characteristics viewed with periodicities of entropy, hydrophobicity, and volume. Proteins. 2004; 56(4):650-60.
• [9]Michino M, Chen J, Stevens RC, Brooks CL. FoldGPCR: structure prediction protocol for the transmembrane domain of G protein-coupled receptors from class A. Proteins. 2010; 78(10):2189-201.
• [10]Sandal M, Duy TP, Cona M, Zung H, Carloni P, Musiani F, Giorgetti A. GOMoDo: A GPCRs online modeling and docking webserver. PLoS One. 2013; 8(9): Article ID e74092
• [11]Karchin R, Karplus K, Haussler D. Classifying G-protein coupled receptors with support vector machines. Bioinformatics. 2002; 18(1):147-59.
• [12]Qian B, Soyer OS, Neubig RR, Goldstein RA. Depicting a protein's two faces: GPCR classification by phylogenetic tree-based HMMs. FEBS Lett. 2003; 554(1–2):95-9.
• [13]Kakarala KK, Jamil K. Sequence-structure based phylogeny of GPCR Class A Rhodopsin receptors. Mol Phylogenet Evol. 2014; 74:66-96.
• [14]Isberg V, Vroling B, van der Kant R, Li K, Vriend G, Gloriam D. GPCRDB: an information system for G protein-coupled receptors. Nucleic Acids Res. 2014; 42(Database issue):D422-5.
• [15]Ono Y, Fujibuchi W, Suwa M. Automatic gene collection system for genome-scale overview of G-protein coupled receptors in eukaryotes. Gene. 2005; 364:63-73.
• [16]Olivella M, Gonzalez A, Pardo L, Deupi X. Relation between sequence and structure in membrane proteins. Bioinformatics. 2013; 29(13):1589-92.
• [17]Altschul SF. Amino acid substitution matrices from an information theoretic perspective. J Mol Biol. 1991; 219(3):555-65.
• [18]Yu YK, Altschul SF. The construction of amino acid substitution matrices for the comparison of proteins with non-standard compositions. Bioinformatics. 2005; 21(7):902-11.
• [19]Dayhoff MO, Schwartz RM, Orcutt BC. A model of evolutionary change in proteins. Atlas of protein sequence and structure. 1978; 5(3):345-51.
• [20]Henikoff S, Henikoff JG. Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci U S A. 1992; 89(22):10915-9.
• [21]Gonnet GH, Cohen MA, Benner SA. Exhaustive matching of the entire protein sequence database. Science. 1992; 256(5062):1443-5.
• [22]Ng PC, Henikoff JG, Henikoff S. PHAT: a transmembrane-specific substitution matrix. Predicted hydrophobic and transmembrane. Bioinformatics. 2000; 16(9):760-6.
• [23]Sutormin RA, Rakhmaninova AB, Gelfand MS. BATMAS30: amino acid substitution matrix for alignment of bacterial transporters. Proteins. 2003; 51(1):85-95.
• [24]Lemaitre C, Barre A, Citti C, Tardy F, Thiaucourt F, Sirand-Pugnet P, Thebault P. A novel substitution matrix fitted to the compositional bias in Mollicutes improves the prediction of homologous relationships. BMC Bioinformatics. 2011; 12:457. BioMed Central Full Text
• [25]Strotmann R, Schrock K, Boselt I, Staubert C, Russ A, Schoneberg T. Evolution of GPCR: change and continuity. Mol Cell Endocrinol. 2011; 331(2):170-8.
• [26]Activities at the Universal Protein Resource (UniProt). Nucleic Acids Res. 2014;42(Database issue):D191-98.
• [27]Zozulya S, Echeverri F, Nguyen T. The human olfactory receptor repertoire. Genome Biol. 2001;2(6):RESEARCH0018.
• [28]Topiol S, Sabio M. X-ray structure breakthroughs in the GPCR transmembrane region. Biochem Pharmacol. 2009; 78(1):11-20.
• [29]Venkatakrishnan AJ, Deupi X, Lebon G, Tate CG, Schertler GF, Babu MM. Molecular signatures of G-protein-coupled receptors. Nature. 2013; 494(7436):185-94.
• [30]Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R et al.. Clustal W and Clustal X version 2.0. Bioinformatics. 2007; 23(21):2947-8.
• [31]Ballesteros JA, Weinstein H. Integrated methods for the construction of three dimensional models and computational probing of structure-function relations in G-protein coupled receptors. Meth Neurosci. 1995; 25:366-428.
• [32]Gonzalez A, Cordomi A, Caltabiano G, Pardo L. Impact of helix irregularities on sequence alignment and homology modeling of G protein-coupled receptors. ChemBioChem. 2012; 13(10):1393-9.
• [33]Sheetlin S, Park Y, Spouge JL. The Gumbel pre-factor k for gapped local alignment can be estimated from simulations of global alignment. Nucleic Acids Res. 2005; 33(15):4987-94.
• [34]Katoh K, Misawa K, Kuma K, Miyata T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 2002; 30(14):3059-66.
• [35]Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013; 30(4):772-80.
• [36]Deupi X, Olivella M, Sanz A, Dolker N, Campillo M, Pardo L. Influence of the g- conformation of Ser and Thr on the structure of transmembrane helices. J Struct Biol. 2010; 169(1):116-23.
• [37]Mirzadegan T, Benko G, Filipek S, Palczewski K. Sequence analyses of G-protein-coupled receptors: similarities to rhodopsin. Biochemistry. 2003; 42(10):2759-67.
• [38]Gonzalez A, Cordomi A, Matsoukas M, Zachmann J, Pardo L. Modeling of G protein-coupled receptors using crystal structures: from monomers to signaling complexes. Adv Exp Med Biol. 2014; 796:15-33.
• [39]Bernstein FC, Koetzle TF, Williams GJ, Meyer EF, Brice MD, Rodgers JR, Kennard O, Shimanouchi T, Tasumi M. The Protein Data Bank: a computer-based archival file for macromolecular structures. J Mol Biol. 1977; 112(3):535-42.
• [40]Bylund DB, Eikenberg DC, Hieble JP, Langer SZ, Lefkowitz RJ, Minneman KP, Molinoff PB, Ruffolo RR, Trendelenburg U. International Union of Pharmacology nomenclature of adrenoceptors. Pharmacol Rev. 1994; 46(2):121-36.
• [41]Soriano-Ursua MA, Trujillo-Ferrara JG, Correa-Basurto J, Vilar S. Recent structural advances of beta1 and beta2 adrenoceptors yield keys for ligand recognition and drug design. J Med Chem. 2013; 56(21):8207-23.
• [42]Jaakola VP, Griffith MT, Hanson MA, Cherezov V, Chien EY, Lane JR, Ijzerman AP, Stevens RC. The 2.6 angstrom crystal structure of a human A2A adenosine receptor bound to an antagonist. Science. 2008;322(5905):1211–17.
• [43]Hanson MA, Roth CB, Jo E, Griffith MT, Scott FL, Reinhart G, Desale H, Clemons B, Cahalan SM, Schuerer SC et al.. Crystal structure of a lipid G protein-coupled receptor. Science. 2012; 335(6070):851-5.
• [44]Jones DT, Taylor WR, Thornton JM. A mutation data matrix for transmembrane proteins. FEBS Lett. 1994; 339(3):269-75.
• [45]UniProtKB/Swiss-Prot protein knowledgebase release statistics Oct-29, 2014.