Design of affinity peptides from natural protein ligands: A study of the cardiac troponin complex.

Design of affinity peptides from natural protein ligands: A study of the cardiac troponin complex Divya Chandra1,2, Nitesh Sankalia1, Imee Arcibal3, Scott Banta4, Donald Cropek3,*, and Pankaj Karande1,2*

1

Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York

2

Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, New

York 3

U.S. Army Engineer Research and Development Center, Construction Engineering Research Laboratory (CERL), Champaign, Illinois

4

Department of Chemical Engineering, Columbia University, New York, New York

*: To whom correspondence should be addressed. Dr. Donald M. Cropek 2902 Newmark Dr. Champaign, IL 61822 Phone: 217-373-6737 Email: [email protected]

Dr. Pankaj Karande 110 8th St. Troy, NY, 12180 Phone: 518-276-4459 Email: [email protected]

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as an ‘Accepted Article’, doi: 10.1002/bip.22436 © 2013 Wiley Periodicals, Inc.

Biopolymers: Peptide Science

ABSTRACT We describe a general strategy for the design and discovery of affinity peptides for a protein from its natural ligands. Our approach is guided by protein-protein interactions in natural systems and focuses on the hetero-trimeric complex of cardiac troponin I (cTnI), C (cTnC) and T (cTnT). A key premise of this work is that cTnC and cTnT, owing to their innate ability to bind cTnI, are potential templates for the design and discovery of cTnI-binding peptides. Relying only on the knowledge of primary sequences of cTnC and cTnT, we designed a library of short overlapping peptides that span the entirety of cTnC and cTnT and tested them for binding to cTnI. We were successful in identifying several peptides that display high affinity (1-100 nM) for cTnI. The specific implication of this work is that mimicking natural proteinprotein interactions is an excellent starting point for the discovery and rational design of peptide ligands. The knowledge of secondary or tertiary structures of the proteins involved is not a necessary pre-condition for this approach. Nevertheless, we show that structural information can be used to validate the results of a fragment-based peptide design, and can be potentially beneficial for refining the lead candidates. Our approach is broadly applicable to any protein with at least one natural binding ligand with known primary sequence. For protein targets with multiple natural ligands, this approach can potentially yield several distinct affinity peptides capable of simultaneously binding the target protein via orthogonal modes or at complementary interfaces.

KEYWORDS: ligand design, ligand discovery, peptide fragment screening, peptide microarrays, highthroughput screening

2 John Wiley & Sons, Inc.

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Introduction Protein-mediated interactions are ubiquitous in nature and play an important role in a number of biological events including signal transduction, immune responses, and cellular regulation. Molecular recognition is a key determinant of protein-based interactions, and the biological responses that follow. Knowledge of the specific recognition events is essential not only for elucidating protein function but also for designing affinity ligands. Protein affinity ligands are important in a wide variety of applications 1, 2, 3

. They can be used to provide quantitative information on proteins in analytical assays 4, 5 as well as

qualitative information on their biological function 6. Affinity ligands can be employed as chaperones to assist protein folding

7, 8, 9

or for delivering cargoes by following the native protein transport pathways

10,11

. In drug design, affinity ligands are used to inhibit or promote protein interactions with other

biomolecules to enhance or block specific biological functions 12,13. Affinity ligands are also indispensable in affinity-based protein separation and purification processes 14,15. Although many molecular classes of protein affinity ligands exist, peptides are perhaps the most versatile from the standpoint of both design and application. The modular approach of peptide design from the constituent amino acids; the ability to incorporate natural and non-natural building blocks to tune the structure; as well as the relative ease of synthesis afforded by advanced chemical-coupling techniques make peptides an attractive choice as affinity ligands. Furthermore, the introduction and subsequent advances in biological host-based methods such as yeast 16, 17, bacteria 18, phage 19, 20, mRNA 21, 22

and ribosome 21, that enable the testing of extremely large libraries of peptides (106-1010) against

protein targets has made it relatively easy to extract novel peptide affinity ligands. A general limitation of these brute force approaches, however, is the difficulty in a priori directing or biasing the binding to a specific protein surface. Yet another approach is structure-based de novo design of peptides that target specific binding sites on the protein

23–25

. This is particularly advantageous when the three dimensional

(3D) structure of the target protein is established. However, resolving 3D protein structure to reveal the interfaces and surface residues is challenging, which in turn makes structure-based design quite challenging as well. Rational design approaches can provide a valuable intermediate between brute force and de novo schemes for peptide design. Such schemes rely neither on the knowledge of 3D structure and binding sites on the protein as is typical of structure-based approaches, nor on random but large chemical libraries as is typical of brute force approaches. In contrast, they exploit native protein interactions. More often than not, proteins display promiscuity in both binding and function, and can interact simultaneously or independently with multiple ligands. The qualitative (Van der Waal’s, electrostatic, hydrophobic interactions, etc.) and quantitative (affinity or strength) nature of these 3 John Wiley & Sons, Inc.


interactions varies depending on the specific binding interfaces involved as well as the biological environment. For such proteins, the sites of strong interactions with their natural binding partners can be utilized advantageously for designing affinity peptides. Here we describe a systematic approach for the discovery and design of affinity peptides for a protein by screening short fragments derived from its natural ligands using the cardiac troponin complex as a prototypical example. The hetero-trimeric complex (~80 kDa) of cardiac troponins I (cTnI), C (cTnC) and T (cTnT) is ideal, but not the only example, for illustrating the merits of this approach for two specific reasons. First, although not necessary, the crystal structure of the complex has been resolved and can provide valuable insights for understanding and building on the findings of this study. Second, cTnI is a clinically relevant biomarker of acute myocardial infarction (AMI), and cTnI-binding peptides have potential utility in the development of diagnostic assays and platforms for therapeutics development 26,27. We have chosen the rat cardiac troponin (rcTn) complex for our studies as this is a fairly common and relevant animal model for in vivo studies 28,29,30. Interestingly, there is 99% (100%), 87% (92%) and 92% (95%) sequence identity (similarity) between rat and human cTnC (Uniprot IDs: Q4PP99 and P63316), cTnT (Uniprot IDs: P50753 and P45379) and cTnI (Uniprot IDs: P23693 and P19429), respectively. Consequently, rcTnI-binding peptides identified from these studies can potentially be used as affinity ligands for human cTnI (hcTnI). More importantly though, the very high sequence identities (and similarities) between the corresponding human and rat troponins suggests that the previously published partial crystal structure of human troponin complex (PDB ID: 1J1E) can provide several insights into the findings of this study.

Materials and Methods Materials The following reagents and materials were used for peptide synthesis and microarray screening: Rat Cardiac Troponin I (rcTnI) (Life Diagnostics Inc.), Alexa Fluor® 633 protein labeling kit (Invitrogen), 10X Blocking Buffer (Sigma), Microarray Slides (Intavis Inc.), CelluspotsTM for peptide synthesis (Intavis Inc.), human serum albumin (HSA) (Sigma), dimethylformamide (DMF) (AGTC Bioproducts), dimethyl sulfoxide (DMSO) (AGTC Bioproducts), trifluoromethanesulfonic acid (TFMSA) (Sigma), Ttriisopropyl silane (TIPS) (Sigma), trifluoroacetic acid (TFA) (Sigma), dichloromethane (DCM) (Sigma), piperidine (AGTC Bioproducts), N-methyl pyrrolidone (NMP) (AGTC Bioproducts), hydroxy benzotriazole (HOBt) (AGTC Bioproducts), diisopropyl carbodiimide (DIC) (Sigma), methyl-tertiary-butyl ether (MTBE) (AGTC Bioproducts) and amino acids (21st Century Biochemicals) with the following side-chain protecting groups: 2,2,4,6,7-pentamethyldihydrobenzofuran-5-sulfonyl (Pbf) for Arginine (R); trityl (Trt) for 4 John Wiley & Sons, Inc.

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Asparagine (N), Cysteine (C), Glutamine (Q), and Histidine (H); tertiary butyl-oxy (OtBu) for Aspartic acid (D), and Glutamic acid (E); tertiary-butyloxycarbonyl (Boc) for Lysine (K) and Tryptophan (W), and tertiary butyl (tBu) for Serine (S), Threonine (T), and Tyrosine (Y).

Synthesis of peptides Peptides were synthesized in a spatially addressable manner, on derivatized cellulose acetate discs (CelluspotsTM) from their C to N termini using an automated peptide synthesizer (Multipep RS, Intavis Inc.). Post-synthesis, CelluspotsTM were subjected to a work-up procedure which involved the following steps: (i) Addition of 150 µL/well of a side-chain cleavage mixture consisting of 80% (v/v) TFA, 3% (v/v) TIPS, 5% (v/v) H2O and 12% (v/v) DCM, (ii) Incubation of peptide-cellulose conjugates for 1-2 hours in fume hood at room temperature (RT), (iii) Removal of the side-chain cleavage cocktail, (iv) Addition of 250 µL/well of a cleavage mixture consisting of 88.5% (v/v) TFA, 4% (v/v) TFMSA, 2.5% (v/v) TIPS and 5% (v/v) H2O followed by overnight incubation at RT in a fume hood, (v) Addition of 750 µL icecold MTBE to the peptide-cellulose conjugates and incubation at -20 °C for 1-2 hours in order to precipitate the peptide-cellulose conjugates in ether, (vi) Centrifugation of the peptide-cellulose conjugates at 0°C followed by washes in 500 µL of fresh ether, and (vii) Removal of ether and addition of 500 µL DMSO in order to dissolve the peptide-cellulose conjugates 31, 32.

Peptide microarray screening All microarray screening studies were performed with full length rat cTnI (211 amino acids). rcTnI (24.16 kDa) was labeled with Alexa-633 fluorophore as per recommended protocols and dialyzed in PBS (0.01 M PBS, 100 mM NaCl, pH 7.4) buffer at 4°C to remove the excess unreacted dye. Concentration of the labeled protein and molar ratio of dye to protein was measured using a NanoDrop UV Spectrophotometer (Harlow Scientific). The labeled protein (Alexa633-rcTnI) was stored at 4°C until further use. 60 nL of each peptide was printed in triplicate on microarray slides using a microarrayer (Intavis Inc.). Post-printing, the microarrays were dried and blocked with 1X casein-based blocking buffer (prepared in 0.2 M Tris-HCl, pH 7.4, 0.01% Tween-20) for 3 hours at RT and washed thrice for 10 minutes each time in 0.2 M Tris-HCl, pH 7.4, 0.01% Tween-20. The microarrays were subsequently incubated with 1 mL Alexa633-rcTnI over a range of concentrations (240 nM, 76 nM, 24 nM, 7.6 nM, 2.4 nM, 0.76 nM) at RT in the dark with gentle shaking on a rotator for 2 hours. Thereafter, the incubation solutions were discarded and the microarrays were washed three times for 10 minutes each time in 10 mL PBS buffer. After washing, the microarrays were completely dried in the dark to remove traces of 5 John Wiley & Sons, Inc.


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buffer and imaged using a flatbed scanner (Typhoon Trio plus, GE Healthcare, NY). All microarrays were scanned simultaneously using a 633 nm laser for excitation and a 670 nm filter for emission with a band pass of 30 nm.

Microarray image analysis Microarray images were analyzed using version 3.2.1a of Spotfinder MEV from TM4 suite33. Average pixel intensities of the peptide spots were obtained using the Otsu segmentation algorithm in Spotfinder MEV after aligning a grid over the microarray image. Mean peptide spot intensities were obtained at all concentrations of rcTnI-Alexa633 and the data were analyzed in Microsoft Excel and Origin 6.0 from OriginLab. Equilibrium dissociation constants (KDs) for the binding of each peptide to rcTnI were obtained by fitting data to the Langmuir adsorption isotherm max

D

(1)

where [rcTnI-Alexa633] is concentration of rcTnI-Alexa633 used to challenge the peptide microarrays, I is the average intensity over three peptide spots, Imax is the maximum intensity at saturation of all binding sites within a peptide spot, and KD is the equilibrium dissociation constant. Imax and KD are the fitted parameters obtained after fitting the I vs [rcTnI-Alexa633] data to Equation 1.

Results and Discussions Design of peptides and interpretation of affinity measurements To systematically evaluate the feasibility of discovering affinity peptides from protein primary sequence information alone, we designed short peptides from both full length rcTnC (161 amino acids) and rcTnT (299 amino acids). Each peptide was 15 amino acids in length (except the last peptide which was 14 amino acids in length), beginning at residue 1 with a ratchet length of 3 residues and thus, an overlap of 12 amino acids with the neighboring peptides (Figure 1). This approach resulted in a library of 147 peptides comprising 50 peptides from rcTnC and 97 peptides from rcTnT. A rational design approach, such as the one discussed here, can significantly reduce the library size while accelerating the chances of discovering potential high-affinity peptides against a target. For instance, the hypothetical search space for all possible 15-mers for identifying potential ‘winners’ is on the order of 1020; 18 orders of magnitude higher than the library designed and tested in this work. The specific length (15) and overlap (12) are not stringent criteria for such an approach but were selected to create a fine mapping over the entire protein sequence while still keeping the library size manageable.


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In conducting these studies, we are aware that the affinity measurements on immobilized surfaces often tend to be overestimated due to avidity effects

34

. The density of the ligand on the

surface plays an important role in establishing the affinity of the binding target

35

. Although, the

interactions of the peptides to rcTnI are likely to be primarily monovalent, it is not entirely obvious a priori that a given peptide will have only one fixed binding site on a protein. When taken out of the context of a full-length protein, a given peptide may have a preferred high-affinity binding site on the protein and another neighboring low-affinity binding site. Thus, two peptide molecules close to each other in a peptide spot on the microarray could aid in multipoint interactions and facilitate better capture of the protein on the surface 36. Nevertheless, immobilized peptide microarrays have been used successfully in prior studies for identifying high affinity peptide binders, and their affinities correlate very well with other independent modes of measurements, particularly SPR 37,38,39. The KDs presented in this work are therefore to be considered as ‘apparent affinity constants’ under immobilized binding conditions, albeit good quantitative measures of the relative affinities of the peptides in comparison to each other40. The work described here is primarily focused on establishing the proof-of-concept that affinity peptides can be designed from natural binding ligands. Their rigorous validation for specific applications is the subject of concurrent work, and not within the scope of this study.

Discovery of affinity peptides from rcTnC and rcTnT Of all the peptides tested in this study, 43 peptides (30% of original library) were found to bind rcTnI with an affinity of 1 µM or better. The term affinity and an accompanying numerical value refers to the equilibrium dissociation constant (KD) obtained from fitting the data to the Langmuir isotherm as described in the section on microarray image analysis. 1 µM was chosen as a threshold for selecting affinity peptides based on the range of protein concentrations used in this study and the statistical confidence in estimating fit parameters (KD and Bmax) in this range. Of the affinity peptides that met this criterion, 11 were fragments derived from the rcTnC library and 32 were from the rcTnT library (Figure 2). As a group, rcTnC derived affinity peptides had an average affinity of 90 nM while those derived from the rcTnT library had an average affinity of 39 nM. The best peptide from rcTnC (70GTVDFDEFLVMMVRC84) bound rcTnI with an affinity of ~4 nM whereas the best peptides from rcTnT (265FKQQKYEINVLRNRI279 and 217EKKKKILAERRKVLA231) bound rcTnI with affinities of ~2 nM.

rcTnI-binding peptides from rcTnC



The sequence and affinities of all peptides from rcTnC that display measurable affinity towards rcTnI (at least 1 µM) are noted in Table 1. Given the high degree of sequence identity and homology between human and rat cardiac troponins, we use the previously published partial crystal structure of the human cardiac troponin complex (Figure 3, PDB ID: 1J1E) as a reference to further elucidate these findings. Note, the available crystal structure of the hcTn complex does not contain full-length proteins and only the regions available in the structure are shown. Specifically, regions spanning amino acids 1212 and 282-298 on hcTnT (1-213 and 283-299 on rcTnT), regions spanning amino acids 1-34, 137-146 and 163-210 on hcTnI (1-35, 138-147 and 164-211 respectively on rcTnI) and the region spanning amino acids 89-91 on hcTnC (89-91 on rcTnC) are missing from the crystal structure. As seen in Figure 3, cardiac troponin proteins contains several well-defined helices that are involved in coiled-coil and α-helix mediated interactions in the human troponin complex 41,42. cTnC, in particular, contains 9 α-helices (H1: 5

YKAAVEQ11, H2: 14EEQKNEFKAAFDIF27, H3: 38TKELGKVMRM47, H4: 54PEELQEMID62, H5: 74FDEFLVMMVR83,

H6: 94EEELSDLFRMF104, H7: 114LDELKMMLQA123, H8: 130EDDIEELMKDG140 and H9: 150YDEFLEFM157) ranging from 7 to 14 amino acids in length. Figure 4 shows the peptide fragments of cTnC identified from microarray screening, and listed in Table 1, mapped on to the crystal structure of the troponin IC complex (troponin T is not shown here for clarity). As seen in this figure, all the 11 affinity peptides contain all or portions (50-100%) of the helices H2 (1 peptide), H3 (4 peptides), H5 (4 peptides) and H6 (2 peptides). To verify if these helical regions are responsible for the primary and dominant binding interactions in full-length cTnC, we synthesized each of the 9 helices and measured their binding affinities to rcTnI. The only helices that display measurable finding affinity to rcTnI are those that contain all or portions of multiple affinity peptides (H3: 6 nM, H5: 3 nM and H6: 57 nM). This suggests that these are likely the dominant regions involved in the binding interactions between rcTnI and rcTnC (Table 2). Indeed, previous studies have established the critical contributions of hydrophobic residues from H2 (Ala-22, Ala-23 and Ile-26), H3 (Val-44 and Met-45), and H5 (Met-81) to two binding pockets formed by pairs of helix-coil-helix on rcTnC that interact with rcTnI 43. Region H6 (94-104) of rcTnC has similarly been identified to interact with rcTnI 44. It stands to reason that the best peptides identified from microarray screening contain all or part of the helical regions H2, H3, H5 and H6, most notably, 70

GTVDFDEFLVMMVRC84 (100% of H5, 4 nM),

10

EQLTEEQKNEFKAAF24 (78% of H2, 10 nM) and

34

GCISTKELGKVMRML48 (100% of H3, 9 nM),

94

EEELSDLFRMFDKNA108 (100% of H6, 51 nM). The

finding that affinity peptides can be designed from α-helical regions of rcTnc that are known to bind to rcTnI, alone, is rather trivial. Indeed, such strategies have been employed previously to design affinity peptides

45

. The key deduction from these studies, however, is that a priori knowledge of binding 8 John Wiley & Sons, Inc.

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domains or their secondary structures is not necessary for designing affinity peptides from natural ligands. Sequence information alone appears to be sufficient. Good examples from this study are peptides 70GTVDFDEFLVMMVRC84 (4 nM) and 94EEELSDLFRMFDKNA108 (51 nM) which contain the entire helical regions H5 (10 amino acids) and H6 (11 amino acids), and have very similar affinities as the helices H5 (3 nM) and H6 (57 nM) themselves. A key caveat to be noted is that in rcTnC all the helical regions are smaller than the length of the test peptides (15 amino acids) and therefore more likely to be captured in binding assays. If the helical regions are longer, then in order to be captured in binding assays, the helical region could be broken up into shorter peptide fragments. The length and overlap of the peptide candidates, however, are somewhat arbitrary and subject to rational design and optimization. It is interesting to note that not all peptides that include the entire helical regions are strong binders. For example, peptide 73DFDEFLVMMVRCMKD87 that contains the entire helix H5 binds with a much lower affinity (511 nM). In contrast, peptides

76

EFLVMMVRCMKDDSK90 (38 nM) and

79

VMMVRCMKDDSKGKS93 (21 nM) that contain only 80% and 50%, respectively, of H5 bind with very

good affinity (albeit lower than H5 or 70GTVDFDEFLVMMVRC84 that contains 100% H5). Likewise, peptide 13

TEEQKNEFKAAFDIF27 that contains the entire helix H2 does not show any measurable affinity, much

like H2 itself, even though H2 has been implicated in the interactions between rcTnC and rcTnI 43. It is likely that this is a weak interaction in the full-length proteins. In contrast, and as noted above, peptide 10

EQLTEEQKNEFKAAF24 containing partial (78%) helix H2 displays a very strong binding affinity (10 nM)

towards rcTnI. Similar conclusions can also be drawn from peptides listed in Table 1 and derived from H3 and H6. Our findings, relying on sequence-based design of peptide fragments have important implications for the design of affinity ligands. Screening of overlapping peptide fragments designed from natural binding partners can not only identify the important regions of protein-protein interactions but also highlight the role of residues flanking those regions in determining the peptide affinity. It is often necessary to design peptides that are longer than the minimally sufficient binding regions for a variety of reasons including addition of linkers 46, cyclization 47, and incorporation of additional functionalities 48. A fine mapping of the protein sequence can provide valuable information for such design strategies. The information generated in this work from screening peptide libraries designed from native partners, combined with structural information, provides a rich knowledge-base on interaction strengths and binding surfaces as discussed. Similar in spirit to alanine scanning, a critical advantage of this approach is that unlike loss/gain in binding information obtained from alanine mutations, it also allows the



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identification and discovery of high affinity peptides. This point is further illustrated with peptides identified from rcTnT that bind to rcTnI (vide infra).

rcTnI-binding peptides from rcTnT Table 3 lists the sequence and affinities of all peptides (32 out of 97) from rcTnT that display measurable binding affinity towards rcTnI. Figure 5 illustrates those affinity peptides that are also part of the available partial crystal structure of the troponin IT complex (troponin C is not shown here for clarity). The crystal structure of hcTnT contains two well-defined α-helices H10: 214-231 and H11: 236279 (215-232 and 237-280 respectively on rcTnT) known to interact with cTnI in the cTn complex 41. It is therefore not surprising that we identified 15 peptides close to or containing these regions that display very high affinity towards rcTnI, specifically,

196

FGGYIQKAQTERKSG210 (5 nM),

199

YIQKAQTERKSGKRQ213

(10 nM), 214TEREKKKKILAERRK228 (6 nM), 217EKKKKILAERRKVLA231 (2 nM), 262QEKFKQQKYEINVLR276 (6 nM) and

265

FKQQKYEINVLRNRI279 (2 nM). It is, however, surprising that we identified 17 moderate to high

affinity peptides from region 1-201 on rcTnT (1-199 respectively on hcTnT; Table 3). This region is typically involved in coiled-coil interactions with tropomyosin as part of the cTn complex and not available to bind cTnI 2, 12. Based on these data, it is likely that this region can indeed interact with cTnI when not in complex with tropomyosin. Indeed, peptides derived from this region share several sequence similarities with those derived from regions 215-280 in that they are rich in charged residues Asp, Glu, Lys, Arg and His, and have a high propensity to form α-helices as predicted by PEP-FOLD49,50,51,52 and AGADIR (data not shown). Additional sequence similarities between peptides from regions 215-280 and 1-201 can explain their similar behavior in binding to rcTnI. Consider, for example, peptides 217

EKKKKILAERRKVLA231 (from helix H10) and 57EKERQNRLAEERARR171 (from region 1-201), which show 3

identical and 6 similar amino acids when aligned using Clustalo in Uniprot. It is therefore possible that several peptides from the region 1-201 of rcTnT have binding properties similar to peptides from regions of cTnT known to interact with cTnI. We have performed structure prediction studies on the peptides reported in this work using computational structure prediction tools such as PEP-FOLD, AGADIR and QUARK. From these, we have observed that several peptides with high-affinity to TnI have a moderateto-high propensity to form α-helices much like their parent protein (data not shown). It is likely that the peptides form secondary structures when immobilized at their c-termini on the microarrays or adopt secondary conformations on binding to the protein. Investigating this in further details, while outside the scope of the present study, is our goal for future studies.


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Screening of overlapping peptide fragments from rcTnT led to the discovery of several high affinity peptide ligands. More importantly, it also revealed interesting correlations between peptide sequence and affinity. As an example, peptide

199

YIQKAQTERKSGKRQ213 (10 nM) bound rcTnI with high

affinity but a neighboring peptide designed by removing the three N terminus residues YIQ and adding three residues TER at the C terminus significantly reduced the affinity (202KAQTERKSGKRQTER216, 68 nM). It is clear from this example that a few residues can significantly alter peptide affinity. To investigate if we could identify additional peptide fragments missed in the first round of screening, we designed a second set of peptides from the region 200-298 of rcTnT that were 15 amino acids in length but with an overlap of 14 amino acids. This allowed for a very fine mapping of the primary sequence of rcTnT by changing only 2 residues at a time. Peptides identified from this study with measurable binding affinities to rcTnI are listed in Table 4. We identified an additional 24 peptides that were missed during the first round of screening but bind rcTnI with very high affinity, most notably, 215EREKKKKILAERRKV229 (3 nM), 216

REKKKKILAERRKVL230 (2 nM),

264

218

KFKQQKYEINVLRNR278 (2 nM), and

KKKKILAERRKVLAI232 (4 nM),

263

EKFKQQKYEINVLRN277 (6 nM),

266

KQQKYEINVLRNRIN280 (2 nM). These results suggest that a first

round of coarse screening can focus on identifying the most likely regions of binding followed by a second round of fine mapping to identify the optimal peptide sequences that act as high affinity ligands.

Conclusion In this study, we describe a general approach for peptide design and screening using the primary sequences of natural binding partners for discovery of affinity ligands for a protein. Peptides identified in this study are quite attractive as potential affinity ligands for a broad range of applications. These include, for example, detection of cTnI from serum samples in microarray ELISAs or dissociation and isolation of cTnI from a complex with cTnT and cTnC by peptides that can inhibit native protein interactions. Additionally, peptides binding to different regions can also be used to enhance affinity by combining them together with linkers of appropriate length or co-immobilizing them on a surface. In fact, it has been shown by Willaims et al. that such an approach can lead to up to 1000-fold improvement in affinity 53. Based on a very focused and small library, dependent primarily on the length of the partner proteins, we screened peptides to obtain qualitative as well as quantitative information on their binding to rcTnI. Using this approach, we identified several peptides from both rcTnT and rcTnC that bind to rcTnI with high affinity. Since rcTnC and rcTnT are known binding partners of rcTnI, it intuitively makes sense that the likelihood of finding peptide ligands is greater as compared to brute-force screening 11 John Wiley & Sons, Inc.


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approaches such as phage or other biological display methods. In a similar fashion, fragments of rcTnI and rcTnT/rcTnC could be made to identify affinity peptides that bind rcTnT and rcTnC. In fact, Ferrieres et al. have reported on a similar approach where they have identified regions of cTnI important for binding to cTnC, which complements our current work54. The strength of our approach lies primarily in the fact that knowledge of binding interfaces, secondary structural domains and 3D crystal structures of individual proteins or their complexes is not a prerequisite for peptide design. In fact, the specific peptide affinity ligands that were discovered from these known binding ligands could not have all been determined a priori, even if structure and knowledge of binding sites were available. This is because the incorporation of a known binding site in a peptide also requires screening for the optimum overall length and nature as well as number of flanking residues. A library of peptides with overlapping sequences contains valuable information on key recognition motifs and residues that are involved in binding of the peptide ligands to the target protein. Structural information, when available, can be used advantageously to interpret the results from the screening and in subsequent efforts directed towards affinity maturation. In our case, the partial crystal structure of the cTn complex provided a number of clues to interpret the results for peptides binding to rcTnI. With the available crystal structure of the cTn at hand, it becomes clear that a significant number of high-affinity peptides in our work contain complete or partial regions of rcTnT and rcTnC that are α-helical in nature. Therefore, with respect to peptide lead refinement and development of other novel moieties from the lead peptides, this opens up several interesting avenues. Addition of chemical functionalities, site directed mutations, and introduction of scaffolds and templates for secondary structure stabilization are some directions that can be explored to achieve additional gains in affinity, selectivity (towards protein target) and specificity (towards specific site) of the selected peptide ligands

55, 56, 57, 45

. Our approach can significantly accelerate the peptide ligand discovery and design

process as compared to brute force techniques where lead refinement is preceded by several rounds of amplification and the necessary sequence determination. Even with a lead sequence obtained from large libraries of unknown peptides, there is limited control over its amino acid content, structure and binding site during the screening process. Usually, in such approaches, affinity maturation via sequence refinement is conducted to elucidate key binding residues, followed by further structural refinement and stabilization. Even though our approach does not directly address the elements of structure and targeted binding at a particular site at the screening stage, it provides the correct preliminary framework for building upon those elements for applications requiring them. Of course, one obvious limitation of


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our approach is its inapplicability when binding partners for a target protein do not exist or are not known. Finally, from the fundamental standpoint of how proteins interact and form complexes, we probe why an approach such as the one described in this work would be successful as a general platform for affinity peptide design. Although protein tertiary structures display a large diversity, they are primarily composed of constitutive secondary structure motifs, i.e., β-hairpins and α-helices, connected by unstructured loops/regions. It has also been demonstrated through several examples in nature that protein function, initiated by a primary binding event, is often mediated by short stretches of amino acids, typically 3-15 in number 45. The short RGD motif involved in binding of αv integrins to fibronectin is a classic example 58. Often, these short stretches of amino acids tend to adopt secondary structures either in the native protein itself or upon binding of the native protein to another ligand. Therefore, in systems containing short recognition motifs between the interacting binding partners, this reductionist approach to discovering affinity ligands by constructing epitope-mimicking peptide fragments would find general applicability and success.

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LIST OF TABLES TABLE 1: Sequences and affinities of peptides from rcTnC that show high affinity for rcTnI No.

Sequence

Affinity (nM)

1.

10

24

9

2.

31

45

32

3.

34

48

4.

37

51

16

5.

40

54

12

6.

70

84

3

7.

73

87

510

8.

76

90

37

9.

79

10.

94

11.

97

EQLTEEQKNEFKAAF

AEDGCISTKELGKVM

GCISTKELGKVMRML

STKELGKVMRMLGQN

ELGKVMRMLGQNPTP GTVDFDEFLVMMVRC

9

DFDEFLVMMVRCMKD EFLVMMVRCMKDDSK

VMMVRCMKDDSKGKS EEELSDLFRMFDKNA

93

108 111

LSDLFRMFDKNADGY

21 51 284

TABLE 2: Sequences and affinities of short helices that originate from rcTnC and show high affinity for rcTnI No.

Sequence

Affinity (nM)

1.

39

2.

74

83

3

3.

94

104

57

TKELGKVMRM FDEFLVMMVR

EEELSDLFRMF

47

6

TABLE 3: Sequences and affinities of peptides from rcTnT that show high affinity for rcTnI No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Sequence

Affinity (nM)

67

81

70

84

73

87

76

90

79

93

EDGPVEDSKPKPSRL

PVEDSKPKPSRLFMP

27 3

DSKPKPSRLFMPNLV PKPSRLFMPNLVPPK SRLFMPNLVPPKIPD

7 10

103

HRKRMEKDLNELQTL

112

117

126

NELQTLIEAHFENRK

124

138

NRKKEEEELISLKDR

130

EELISLKDRIEKRRA

133

144

ISLKDRIEKRRAERA

136 139

2

147

KDRIEKRRAERAEQQ

150

153

IEKRRAERAEQQRIR

157

171

166

180

EKERQNRLAEERARR EERARREEEENRRKA

215 61 18 8 9 138 9 9 75

John Wiley & Sons, Inc.


15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

175

ENRRKAEDEARKKKA

189

184

ARKKKALSNMMHFGG

198

187

KKALSNMMHFGGYIQ

196

FGGYIQKAQTERKSG

199

YIQKAQTERKSGKRQ

202

KAQTERKSGKRQTER

205

TERKSGKRQTEREKK

208

KSGKRQTEREKKKKI

214

TEREKKKKILAERRK

201

210 213 216

219

222

228

217

KKILAERRKVLAIDH

238

DQLREKAKELWQSIH

234

253

NLEAEKFDLQEKFKQ

AEKFDLQEKFKQQKY

259

FDLQEKFKQQKYEIN

252

270

262

273

QEKFKQQKYEINVLR

276

265

FKQQKYEINVLRNRI

284

KVSKTRGKAKVTGRW

60 5 10 68 23 38 2 76

267

256

100

6

231

EKKKKILAERRKVLA

220

45

279 298

37 63 29 57 6 1 20

TABLE 4: Sequences and affinities of peptides that originate from known α-helical regions of rcTnT and show high affinity for rcTnI in a fine-epitope mapping No. 1 2

Sequence 218

206

220

207

221

RKSGKRQTEREKKKK

209

SGKRQTEREKKKKIL

210

GKRQTEREKKKKILA

212

RQTEREKKKKILAER

226

213

QTEREKKKKILAERR

227

215

229

QTERKSGKRQTEREK ERKSGKRQTEREKKK

3 4 5 6 7 8

EREKKKKILAERRKV

67 224

83 75 11 2

218

KKKKILAERRKVLAI

219

KKKILAERRKVLAID

231

AIDHLNEDQLREKAK

11

18

223

REKKKKILAERRKVL

10

230

1

232

3 233

29 245

239

13 14 15 16 17

64 20

216

9

12

Affinity (nM)

204

QLREKAKELWQSIHN

240

254

252

266

255

269

257

271

LREKAKELWQSIHNL HNLEAEKFDLQEKFK

25 31 56

EAEKFDLQEKFKQQK EKFDLQEKFKQQKYE

63

253

32 82


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258

18

KFDLQEKFKQQKYEI

272

263

19

22 23 24

277

264

KFKQQKYEINVLRNR

266

KQQKYEINVLRNRIN

20 21

18

EKFKQQKYEINVLRN

275

6 278

2

280

LRNRINDNQKVSKTR

289

278

RINDNQKVSKTRGKA

292

281

DNQKVSKTRGKAKVT

295

2 57 52 55



Schematic of the peptide library design. The figure above denotes the primary amino acid sequence of rcTnC from 1-161. Peptides, 15 amino acids in length, a ratchet length of 3 residues, and an overlap of 12 amino acids, were designed from the entire sequence. The sequence in green, for example, 34-54, results in the 3 library entries 34-48, 37-51, and 40-54, as shown. A similar peptide library design was carried out over the entire primary amino acid sequence of rcTnT 50x10mm (300 x 300 DPI)


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Scatter plot of peptides that show high binding affinity for rcTnI. High-affinity peptides from rcTnC are shown as filled green circles. Similarly, high-affinity peptides from rcTnT are shown as filled red circles. Average affinities of peptides are shown as black horizontal lines in their corresponding groups. The average affinities of peptides from each group are: rcTnC: 90 nM, rcTnT: 39 nM 133x93mm (300 x 300 DPI)



Ribbon structure of the troponin complex (PDB ID: 1J1E). Troponin T (residues Thr213-Asn281) is colored blue, Troponin I (residues Ala35-Arg136 and Val147- Arg162) is in grey and Troponin C (residues Met1Glu161) is in yellow. Numbering of residues is based on sequences of human cardiac troponins I, C, T 152x202mm (300 x 300 DPI)


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Ribbon structure of the human cardiac troponin complex showing cTnI in grey and cTnC in yellow. Regions of cTnC containing peptides that show high affinity (< 10 nM) for rcTnI are marked in red. All the helices in cTnC are numbered from H1-H9 76x180mm (300 x 300 DPI)



Ribbon structure of the human cardiac troponin complex with regions of cTnT that contain peptides showing high-affinity (< 10 nM) for rcTnI marked in red. cTnI is depicted in grey and the rest of cTnT in blue. Helices H11 and H12 in cTnT are labeled. Numbering of residues in cTnT is according to the rcTnT sequence 152x228mm (300 x 300 DPI)


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LIST OF FIGURE CAPTIONS Figure 1: Schematic of the peptide library design. The figure above denotes the primary amino acid sequence of rcTnC from 1-161. Peptides, 15 amino acids in length, a ratchet length of 3 residues, and an overlap of 12 amino acids, were designed from the entire sequence. The sequence in green, for example, 34-54, results in the 3 library entries 34-48, 37-51, and 40-54, as shown. A similar peptide library design was carried out over the entire primary amino acid sequence of rcTnT

Figure 2: Scatter plot of peptides that show high binding affinity for rcTnI. High-affinity peptides from rcTnC are shown as filled green circles. Similarly, high-affinity peptides from rcTnT are shown as filled red circles. Average affinities of peptides are shown as black horizontal lines in their corresponding groups. The average affinities of peptides from each group are: rcTnC: 90 nM, rcTnT: 39 nM Figure 3: Ribbon structure of the troponin complex (PDB ID: 1J1E). Troponin T (residues Thr213-Asn281) is colored blue, Troponin I (residues Ala35-Arg136 and Val147- Arg162) is in grey and Troponin C (residues Met1-Glu161) is in yellow. Numbering of residues is based on sequences of human cardiac troponins I, C, T Figure 4: Ribbon structure of the human cardiac troponin complex showing cTnI in grey and cTnC in yellow. Regions of cTnC containing peptides that show high affinity (< 10 nM) for rcTnI are marked in red. All the helices in cTnC are numbered from H1-H9

Figure 5: Ribbon structure of the human cardiac troponin complex with regions of cTnT that contain peptides showing high-affinity (< 10 nM) for rcTnI marked in red. cTnI is depicted in grey and the rest of cTnT in blue. Helices H11 and H12 in cTnT are labeled. Numbering of residues in cTnT is according to the rcTnT sequence


Selective enrichment and characterization of high affinity ligands from collections of random peptides on filamentous phage.

Design of hydropathically complementary peptides for Big Endothelin affinity purification.

Affinity chromatography purification of a cyclic nucleotide phosphodiesterase using immobilized modulator protein, a troponin C-like protein from brain.

Order-Disorder Transitions in the Cardiac Troponin Complex.

A comparative study of the cardiac troponin inhibitory factor (TNI) from mammalians.

Modifications of natural peptides for nanoparticle and drug design.

A model for human cardiac troponin C and for modulation of its Ca2+ affinity by drugs.

Targeting protein-protein interactions with trimeric ligands: high affinity inhibitors of the MAGUK protein family.

The phosphorylation of troponin I from cardiac muscle.

The effects of reported Ca2+ sensitisers on the rates of Ca2+ release from cardiac troponin C and the troponin-tropomyosin complex.

Glycomimetics versus multivalent glycoconjugates for the design of high affinity lectin ligands.

Study of troponin with cleavable protein crosslinkers.

Ultracentrifugation study on interactions among calmodulin, cardiac troponin and tropomyosin-actin complex.

Amino-functionalization of carbon nanotubes by using a factorial design: human cardiac troponin T immunosensing application.

A 1H NMR study of a ternary peptide complex that mimics the interaction between troponin C and troponin I.

Study design of embracing high-sensitivity troponin effectively: the value of more information: a randomized comparison.

Michael acceptor approach to the design of new salvinorin A-based high affinity ligands for the kappa-opioid receptor.

Affinity chromatography of trypsin and related enzymes. I. Preparation and characteristics of an affinity adsorbent containing tryptic peptides from protamine as ligands.

Ultrasensitive electrochemiluminescent detection of cardiac troponin I based on a self-enhanced Ru(II) complex.

Isolation of troponin-like complex from bovine brain cortex.

Time-resolved tryptophan emission study of cardiac troponin I.

Molecular dynamics simulations of the cardiac troponin complex performed with FRET distances as restraints.

The mystifying nomenclature of cardiac troponin immunoassays.

The binding affinity and dissociation rates of peptides for class I major histocompatibility complex molecules.