The hydrophobic cores of proteins predicted by wavelet analysis.

Hirakawa, Hideki; Muta, Shigeru; Kuhara, Satoru

doi:10.1093/bioinformatics/15.2.141

Cited by 53 publications

(42 citation statements)

References 19 publications

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“…Here it is the c 2 that contains the receptor's hydrophobic binding modes. Wavelet transformation of the hb i and/or c i yield patterns that confirm the wavelength and, in addition, the sequence locations of these hydrophobic segments as well the eigenmodes as described below (Mandell et al, 1997a, b, c;Hirakawa et al, 1999;Lio and Vannucci, 2000;Wouters et al, 2000;Murray et al, 2002;Giuliani et al, 2002).…”

supporting

confidence: 57%

“…This naturally led to our applications of some of these and related techniques (Broomhead et al, 1987;Broomhead and King, 1986;Ott et al, 1994) to hydrophobically transformed amino-acid sequences and/or subsequences (Manavalen and Ponnuswamy, 1978;Nozaki and Tanford, 1971;Reynolds et al, 1974;Zimmerman et al, 1968), including those that are conformationally disordered in globular proteins (Mandell et al, 1997a(Mandell et al, , b, 1998b, polyproteins (Mandell et al, 1998c), membrane channels and transporters, (Mandell et al, 1998a;Selz et al, 1998) and Type I (Mandell et al, 2001) and Gprotein-coupled (Mandell et al, 1997c(Mandell et al, , 2000b) membrane receptors. Recently, other groups have begun applying some of these techniques of one-dimensional signal analysis to protein structural characterization and prediction (Hirakawa et al, 1999;Murray et al, 2002;Lio and Vannucci, 2000;Giuliani et al, 2002;Wouters et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

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Cellular and Behavioral Effects of D2 Dopamine Receptor Hydrophobic Eigenmode-Targeted Peptide Ligands

Mandell

Selz

Owens

et al. 2003

Neuropsychopharmacol

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Patterns in G-protein-coupled receptors' hydrophobically transformed amino-acid sequences can be computationally characterized as hierarchies of autocorrelation waves, 'hydrophobic eigenmodes,' using autocovariance matrix decomposition and all poles power spectral and wavelet transformations. L-or D-amino acid (retro-inverso) 12-18 residue peptides targeting these modes can be designed using eigenvector templates derived from these computations. In all, 12 human long-form D 2 dopamine receptor eigenmode-targeted 15 mer peptides were designed, synthesized, and shown to modulate and/or indirectly activate the extracellular acidification response, EAR, in stably receptor-transfected CHO and LtK cells, with an 83% hit rate. Representative L-and D-amino-acid retro-inverso peptides injected bilaterally in the nucleus accumbens demonstrated changes in rat exploratory behavior and prepulse inhibition similar to those observed following parenteral amphetamine. In contrast with geometric models used for ligand design, such as pharmacophores, the hydrophobic eigenmode approach to lead modulatory peptide design targets hydrophobic eigenmode-bearing subsequences, including those not visible from X-ray and NMR studies such as extracellular segments and loops.

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supporting

confidence: 57%

Section: Introductionmentioning

confidence: 99%

Cellular and Behavioral Effects of D2 Dopamine Receptor Hydrophobic Eigenmode-Targeted Peptide Ligands

Mandell

Selz

Owens

et al. 2003

Neuropsychopharmacol

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“…The latter are formed by composition of the eigenvectors with the sequentially averaged hydrophobic series 1,53,54 ; (3) all poles, maximum entropy, power spectral transformation of the leading eigenfunctions to partially describe and index the wavelengths of the leading hydrophobic eigenmodes 1,[55][56][57] ; (4) wavelet transformation of the leading eigenfunctions to obtain an independent approximation of the wavelengths of the leading mode densities that were indicated by their power (frequency) spectral transformations, and to suggest the sequence location(s) of their leading eigenmode densities 7,11,12,[58][59][60][61][62][63] ; (5) weighted random assignment of amino acids by hydrophobic group to the partitioned compound eigenvector template, derived from, (2) generating the hydrophobic mode matched, candidate peptide ligands. 7 We have consistently used 64,65 the earliest complete set of hydrophobic amino acid energetic transformations, the Tanford hydrophobicity scale in kcal/mol.…”

Section: The Results Of Gal Analyses and Peptide-ligand Design Elucidmentioning

confidence: 99%

“…7,62 Subsequent work confirmed the usefulness of wavelet transformation in locating transmembrane segments, as well as the hydrophobic core and repeating motifs in globular proteins. 9,11,63 Using standard methods, 59,60 the continuous Morlet wavelet transformations of the first and second eigenfunctions of GAL were computed and displayed as phase amplitude plots in Figures 2A and 2B and 3. The sequence positions (uncorrected for the offset created by the 14-lagged autocovariance matrix generating the eigenvectors and thus the eigenfunctions) are indicated along the x-axis.…”

Section: Data Relevant To Gal's Hydrophobic Eigenmode Accessibility Amentioning

confidence: 99%

“…1 Similar spectroscopic findings on hydrophobically transformed protein amino acid sequences have been reported. 8,9,63 When the hydrophobic variation of this leading eigenfunction is mathematically removed, the modes of the residual secondary and tertiary eigenvectors appeared to match those of the receptor protein's extramembranous peptide segments, 7,14 those that are accessible in the extracellular space. These hydrophobic eigenvectors were used to design peptide ligands.…”

Section: Designing Allosteric Peptide Ligands 55mentioning

confidence: 99%

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Designing allosteric peptide ligands targeting a globular protein

et al. 2006

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Patented signal analytic algorithms applied to hydrophobically transformed, numerical amino acid sequences have previously been used to design short, protein‐targeted, L or D retro‐inverso peptides. These peptides have demonstrated allosteric and/or indirect agonist effects on a variety of G‐protein and tyrosine kinase coupled membrane receptors with 30% to over 80% hit rates. Here we extend these approaches to a globular protein target. We designed eight peptide ligands targeting an ELISA antibody responsive protein, β‐galactosidase, βGAL. Three of the eight 14mer peptides allosterically activated βGAL with ELISA methodology. Using Bayesian statistics, this 38% hit rate would have occurred 2 × 10−9 by chance. These peptides demonstrated binding site competitive or noncompetitive interactions, suggesting allosteric site multiplicity with respect to their βGAL binding‐mediated ELISA signal. Kinetic studies demonstrated the temperature dependence of the βGAL peptide binding functions. Using the van't Hoff relation, we found evidence for enthalpy–entropy compensation. This relation is often found for hydrophobic interactions in aqueous media, and is consistent with the postulated hydrophobic series encoding underlying our protein‐targeted, peptide design methods. It appears that our algorithmic, hydrophobic autocovariance eigenvector template approach to the design of allosteric peptides targeting membrane receptors may also be applicable to the design of peptide ligands targeting nonmembrane involved globular proteins. © 2006 Wiley Periodicals, Inc. Biopolymers 85: 38–59, 2007.This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com

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