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J. Biol. Chem., Vol. 281, Issue 22, 15164-15171, June 2, 2006
Multivariate Design and Evaluation of a Set of RGRPQ-derived Innate Immunity Peptides*
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| ABSTRACT |
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| INTRODUCTION |
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Acidic, basic, and glycosylated proline-rich proteins (PRPs)2 encoded by six genes on chromosome 12p13.2 (5), are abundant and polymorphic proteins in saliva (1, 6). Acidic PRPs mediate adhesion of commensal Streptococcus and Actinomyces species (7, 8), neutralize dietary tannins (polyphenols), and interact with calcium (1). These interactions occur through the C-terminal, proline-rich middle and phosporylated N-terminal domains, respectively (1). PRPs are subject to endogenous and bacterial proteolysis, generating a wide range of peptide derivatives in saliva (6, 9, 10). Both allelic PRP variants and small size peptides derived thereof coincide with susceptibility or resistance to caries (11, 12). The allelic acidic PRP variant Db coincides with caries susceptibility and adhesion of Streptococcus mutans (12), implicated in caries. The other acidic PRP variants (e.g. PRP-1 and PRP-2) coincide with resistance to caries and adhesion of commensal streptococci and actinomycetes (12). Moreover, commensal Streptococcus gordonii SK12 proteolytically cleave PRP-1 into a multipotent RGRPQ peptide that regulates plaque pH in situ, stimulates proliferation of the same organism, and inhibits adhesion of Actinomyces naeslundii T14V, which competes for acidic PRP binding sites (10, 13). The effect on plaque pH by RGRPQ resides in inhibition of bacterial acid production from sucrose and catabolism of arginine to ammonia. The RGRPQ peptide could, similar to the ERGMT and ARNQT peptide signals that affect intra- or extracellular receptors and gene expression in Bacillus subtilis (14), mimic natural peptide signaling substances in the streptococcal biofilm. In S. gordonii challis, genes encoding peptide pheromone receptors are present (15).
We have shown that the Arg and Gln termini of the RGRPQ peptide are crucially, though differentially, linked to the various innate responses by systematically replacing one amino acid after another with alanine and comparing the activities of designed and wild type peptides (13). Such alanine, proline, or serine scans represent simple and easy strategies to uncover structure-activity relationships. A more powerful approach is to use statistical molecular design (SMD), an experimental design approach (16, 17), in combination with quantitative structure activity-relationship (QSAR) analyses based on quantitative amino acid descriptors (18, 19). QSARs are modeled using multivariate data analysis techniques, such as partial least squares projection to latent structures (PLS) (20, 21). In SMD and QSAR, several amino acid positions are varied simultaneously. The SMD and QSAR approach reveals both amino acid properties and interactions between amino acids pertinent to activity and, consequently, forms a platform for the generation of peptide mimetics. This approach has, for example, been used to develop mimetics that inhibits pili assembly and urinary tract infections based on the interaction of pili chaperones with peptides from the cell surface pilus subunit of uropathogenic Escherichia coli (22, 23).
The aim of this study was to apply (i) SMD and PLS to establish QSARs for a set of RGRPQ-related peptides varied at amino acids 24 simultaneously and (ii) size and N- and C-terminal modifications of RGRPQ to generate structure activity information. The results were used to design new peptides with differential adhesion inhibition/desorption and proliferation activities. Moreover, this SMD approach extracted which properties in the various positions in the peptides that controlled the various biological responses. The results therefore constitute a solid platform for extended studies toward novel peptidomimetics.
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| EXPERIMENTAL PROCEDURES |
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SMDSMD (16, 17) is an approach for selection of subsets of compounds from large virtual compound libraries. It can, for instance, be used to select well balanced compound sets and thereby reducing the number of compounds required for establishing QSARs. An initial step in SMD and QSAR is to quantitatively describe the compounds, i.e. peptide sequences, with molecular descriptors. Here the z-scales for hydrophilizity (z1), size (z2), and electronic effects (z3) were used to quantitatively describe the separate amino acids in the sequence (26). In addition, lipophilicity (SlogP) and total polar surface area (TPSA) (26) were calculated in MOE (27), for the entire peptide, resulting in a so-called descriptor matrix with 11 variables for each peptide sequence (Fig. 1).
In this work, a D-optimal design (28) was used to select a set of 14 diverse peptides for QSAR modeling. While amino acids 24 of the RGRPQ peptide were varied simultaneously using all 20 natural amino acids in the candidate set used for SMD, the functionally crucial Arg and Gln were kept constant. This resulted in a candidate set of 203, or 8,000, RXXXQ peptides. The candidate set was reduced to 7,600 peptides by exclusion of the most distant or extreme five percent of the peptides, as estimated by their distances to the RGHPQ center point of the SMD. A test set of 14 peptides, including the center point RGHPQ peptide, was then selected from the descriptor matrix using D-optimal design (28, 29) as implemented in MODDE 6.0 (30). Hence, a diverse selection of peptides covering a representative range of each z-scale was made. The RGHPQ center point peptide was the peptide closest to a calculated middle point between the highly active RGRPQ and RGAPQ peptides (13). Earlier tested peptides were added as inclusions in the D-optimal design, and RGRPQ was added and used as a reference.
QSAR ModelingThe method of PLS was used to calculate the QSAR model for the 14 test peptides and three biological responses (SIMCA-p + 10.0) (31). The PLS method identifies the information in X (amino acid properties) that relates to the variation in Y (biological responses), i.e. the amino acid properties that result in a change in response. R2 and Q2 are used to diagnose the model. R2 is a measure of how much of the variation in Y that is explained by the model, and Q2 is a measure of the cross-validated predictive ability of the model. R2 and Q2 values can also be generated for each separate response in the model. The QSAR model was used to predict the biological activity for the remaining 7,585 pentapeptides in the candidate set not selected by the D-optimal design. Six of these peptides were tested to verify the reliability of the QSAR-model, i.e. external validation of the model.
Bacterial StrainsS. gordonii SK12 and A. naeslundii T14V (8, 32) were grown overnight on Columbia-II-agar base plates (BD Biosciences), supplemented with 30 ml of a human erythrocyte suspension per liter, at 37 °C and 5% CO2. The strains intended for adhesion inhibition tests were metabolically labeled with [35S]methionine (8).
Growth-inducing Capacity (Proliferation)The ability of RGRPQ-related peptides to induce growth of S. gordonii strain SK12 (referred to as proliferation) was measured by culturing SK12 in a minimum growth medium supplemented with peptide. The minimum growth medium, generated by dilution eight times of a chemically defined medium (free amino acid pool; Ref. 33), were filter-sterilized (Millipore) and aliquoted (100 µl/well) into a 96-well microtiter plate. Prior to inoculation of strain SK12 to the minimum growth medium, SK12 was cultured twice and consecutively in chemically defined medium at 37 °C and 5% CO2. The second culture was grown for 14 h and used as an inoculum (1%, 1/100 µl) to the minimum growth medium supplemented with 150 µM peptide (peptide/free amino acid pool ratio was 1:20). The effect by RGRPQ on growth was dose-dependent between 25 and 250 µM peptide, and 150 µM RGRPQ increased the regeneration time from 4.35 to 1.85 h. The inoculated wells were incubated for 18 h at 37 °C and 5% CO2. Bacterial cell numbers were established by recording the absorbance at 550 nm using a SpectraMAX 340 spectrometer (Molecular Devices, Sunnyvale, CA) before and during culturing. Absorbance values within the range of the assay were linearly proportional to the bacterial cell concentration, as established by correlating the absorbance values and bacterial cell numbers obtained from counting of cells on agar plates.
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Ammonia ProductionAn overnight culture of S. gordonii SK12 was washed once in 10 ml sterile water, adjusted to 4.8 x 109 cells/ml with water, and kept on ice for a minimum of 30 min before use (34). Bacterial cells (90 µl) were mixed with test peptide, and sterile water was added to give a final volume of 100 µl at a final peptide concentration of 0.5 mM. The mixture and control cell suspension were incubated at 37 °C aerobically, and pH was measured using a pH-electrode.
| RESULTS |
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The R2 and Q2 for the separate responses showed similar values, leading to the conclusion that they were all explained well by the model: proliferation (R2 = 92%, Q2 = 71%), adhesion inhibition (R2 = 86%, Q2 = 69%) and desorption (R2 = 87%, Q2 = 60%).
Amino Acid and RGRPQ Characteristics Influencing Proliferation ActivityThe proliferation response depended on similar properties as for adhesion inhibition/desorption for amino acid 4 but different properties for amino acids 2 and 3 (Fig. 2). The following properties of amino acids 24 or the overall peptide correlated with a high proliferation activity (Fig. 2A): (i) large (z2) and hydrophobic (z1) amino acids 2 and 3 as illustrated by the potent RWWCQ and RIWWQ peptides with hydrophobic tryptophan (Trp) or isoleucine (Ile) groups at these positions, (ii) a hydrophobic and low polarity of amino acid 4 (z3-4) (e.g. cysteine), and (iii) a high overall peptide lipophilicity, SlogP, as illustrated by the low potency of the RKKKQ peptide with a charged residue in all three positions.
Some amino acid or peptide properties interacted (i.e. interaction terms) with a large size of amino acid 3 (z2-3) to generate a high proliferation activity (Fig. 2A): (i) a high peptide lipophilicity (SlogP*z2-3), (ii) high hydrophobicity for amino acid 3 (z1-3*z2-3), and (iii) low polarity of amino acid 4 (z2-3*z3-4). The strength of these interactions and the highly influential and linear dependence on hydrophobic properties of amino acid 3 (z1-3) emphasizes the primary importance of a large and hydrophobic amino acid 3 that largely guides the properties of amino acids 2 and 4 (e.g. if increasing the size of amino acid 3 above a threshold level, the size of amino acid 4 should be diminished to retain high activity).
Some peptides mediated 11.6-fold increased proliferation (e.g. RWWCQ and RIWWQ) compared with RGRPQ, while others (e.g. RKKKQ or RDDDQ) displayed reduced but still some proliferation activity (Fig. 1).
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Some amino acid or peptide properties interacted (i.e. interaction terms) with a small size of amino acid 2 (z2-2) to generate a high adhesion inhibition or desorption activity (Fig. 2, B and C): a hydrophilic amino acid 3 (z2-2*z1-3) and amino acid 2 (z1-2*z2-2) and high total polar surface area (TPSA*z2-2). Accordingly, the positive z1-2*z2-2 terms for both adhesion inhibition/desorption and proliferation, which show inversed correlations for the corresponding linear properties, emphasize that size and hydrophobic/hydrophilic character of amino acid 2 affects the two responses differently. Similarly, while a hydrophilic character of amino acid 3 (TPSA*z1-3) correlates with a high adhesion/desorption activity, high proliferation activity depends on a large and hydrophobic character of the same amino acid (SlogP*z2-3 and z1-3*z2-3). Thus, peptides with differential proliferation and adhesion inhibition activities can be designed.
Peptides Designed from the QSAR Model Behaved as ExpectedTo verify the QSAR model and delineated structure-activity relationships, we tested the activity of six peptides predicted to have either a high proliferation or adhesion inhibition activity (Fig. 3, A and B). The RPWCQ and RWWHQ peptides mediated as predicted high proliferation but not adhesion inhibition/desorption and contained a large hydrophobic proline (Pro) or tryptophan (Trp) in position 2, tryptophan in position 3, and low polarity cysteine or histidine (His) in position 4, respectively. The RGWAQ and RGRCQ peptide, on the other hand, showed as predicted a high adhesion inhibition and desorption activity and, accordingly, contained a small glycine (Gly) in position 2, a large nitrogen containing tryptophan (Trp), or arginine (Arg) in position 3 and a low polarity alanine (Ala) or cysteine (Cys) at position 4 (see Figs. 4 and 5). Thus, peptides with differential proliferation and adhesion inhibition/desorption activities were found.
In addition, the RGRCQ and RGWAQ verification peptides and RGHPQ test peptide were improved in all three responses as compared with RGRPQ (Fig. 3B and supplemental Table 1). The three peptides are characterized by (i) a small amino acid 2 (Gly), (ii) a large, hydrophobic and nitrogen-containing amino acid 3 (Trp), and (iii) a hydrophobic (Ala) or low polarity (Cys) amino acid 4 (Fig. 5).
Effects of N- and C-terminal and Size Modifications of RGRPQ on Its Innate PropertiesWe next used N- and C-terminal and size modifications of the RGRPQ peptide to further explore peptide characteristics essential to the RGRPQ innate properties (Table 1).
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Ammonia production occurred rather independently of size. The RG and AGR peptides and the di- or tri-repetitive RGRPQ peptides (RGRPQ2 and RGRPQ3) showed activities rather similar to full-length RGRPQ. Moreover, ammonia production occurred rather independently of an N- or C-terminal location of the Arg residue. Finally, while the activity was completely blocked by acetylation of the N-terminal Arg residue, amidation of the C terminus of RGRPQ did not affect activity.
| DISCUSSION |
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The present results suggest a blend of complex and simple peptide motifs for proliferation, adhesion inhibition, and ammonia production. The complex, though differential, peptide motifs for proliferation and adhesion inhibition/desorption involved more or less the full-length RGRPQ peptide. A high proliferation activity is mediated by RGRPQ, GRPQ, and RPQ (RGRPQ and GRPQ > RPQ) and peptides with unmodified glutamine (Gln), large and hydrophobic properties of amino acids 2 and 3, and hydrophobic and low polarity properties of amino acid 4 (Fig. 5). The importance of a high overall peptide lipophilicity, largely involving amino acid 3, may relate to uptake of the peptide at the cellular membrane or to the character of intra or extra cellular receptors. Moreover, a high adhesion inhibition/desorption activity is mediated by GRPQ with an unmodified Gln terminus, a small amino acid at position 2 (Gly) and a hydrophobic/low polarity (Pro or Cys) amino acid at position 4. Position 3, on the other hand, allowed a variety of substituents but should favorable be slightly hydrophilic (Fig. 5). The PQ and RPQ peptides lacked inhibitory activity and conformational features of glycine at position 2, potentially guiding a cis or trans configuration of proline (Pro), may accordingly contribute to the high GRPQ activity. The virtually identical requirements for adhesion inhibition and desorption are consistent with two related phenomena but surprising, since they are surface versus solution reactions, respectively. Bacterial desorption or release of multiple fimbriae-receptor interactions may, however, follow solution kinetics in general or reflect the aggregation assay used, as opposed to irreversible protein ligand interactions at surfaces, e.g. antibody-antigen surface reactions (24). Finally, ammonia production required only a simple arginine (Arg) motif independent of peptide size or N- and C-terminal localization. It is possible that arginine protrudes from the rest of the RGRPQ peptide, which largely accounts for proliferation and adhesion inhibition/desorption (i.e. GRPQ), and that the arginine deaminease (involved in the catabolism of arginine to ammonia by bacteria) recognizes the protruding arginine (Fig. 5).
Adhesion and proliferation of microorganisms and local conditions, such as pH, are key factors in biofilm formation (25). In oral biofilm formation, frequent intakes of sugar induce acid production from bacteria and a pH decrease changing the biofilm ecology and its potential to cause caries. It is certainly interesting that the RGRPQ peptide is capable of affecting adhesion, proliferation, and pH and that the present findings show the possibility of designing peptides that affects these properties selectively. While RIWWQ increased proliferation but lacked adhesion inhibition/desorption activity, the QSAR model predicts peptides with even larger differences and with the opposite behaviors. While a hydrophobic amino acid 3 and peptide character promotes proliferation selectively, a hydrophilic amino acid 3 and peptide character promotes adhesion inhibition selectively (Fig. 5). There has been a long standing question of whether compounds affecting proliferation versus adhesion are more effective in controlling biofilm formation and infectious diseases in vivo. This study enlightens the possibility to design RGRPQ derivatives with differential adhesion and proliferation activities for evaluation in biofilm models.
In conclusion, this study has drug development implications and provides an example of statistical molecular design as a platform to extract important structure activity relationships from peptides with a multitude of biological properties.
| FOOTNOTES |
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The on-line version of this article (available at http://www.jbc.org) contains supplemental Table 1. ![]()
1 To whom correspondence should be addressed. Tel.: 46-90-7856030; Fax: 46-90-770580; E-mail: Nicklas.Stromberg{at}odont.umu.se.
2 The abbreviations used are: PRP, proline-rich protein; SMD, statistical molecular design; QSAR, quantitative structure activity-relationship; PLS, partial least squares projection to latent structure(s); SlogP, lipophilicity; TPSA, total polar surface area. ![]()
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