Stabilization of TRAIL, an all-ß-sheet multimeric protein, using computational redesign

Almer M. van der Sloot1, Margaret M. Mullally1, Gregorio Fernandez-Ballester2, Luis Serrano2 and Wim J. Quax1,3

1Department of Pharmaceutical Biology, University of Groningen, Antonius Deusinglaan 1, 9713 AV, Groningen, The Netherlands and 2Structural Biology and Biocomputing Program, EMBL, Meyerhofstrasse 1, D-69117 Heidelberg, Germany

3 To whom correspondence should be addressed. E-mail: w.j.quax{at}farm.rug.nl


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Protein thermal stability is important for therapeutic proteins, both influencing the pharmacokinetic and pharmacodynamic properties and for stability during production and shelf-life of the final product. In this paper we show the redesign of a therapeutically interesting trimeric all-ß-sheet protein, the cytokine TRAIL (tumor necrosis factor-related apoptosis-inducing ligand), yielding variants with improved thermal stability. A combination of tumor necrosis factor (TNF) ligand family alignment information and the computational design algorithm PERLA was used to propose several mutants with improved thermal stability. The design was focused on non-conserved residues only, thus reducing the use of computational resources. Several of the proposed mutants showed a significant increase in thermal stability as experimentally monitored by far-UV circular dichroism thermal denaturation. Stabilization of the biologically active trimer was achieved by monomer subunit or monomer–monomer interface modifications. A double mutant showed an increase in apparent Tm of 8°C in comparison with wild-type TRAIL and remained biologically active after incubation at 73°C for 1 h. To our knowledge, this is the first study that improves the stability of a large multimeric ß-sheet protein structure by computational redesign. A similar approach can be used to alter the characteristics of other multimeric proteins, including other TNF ligand family members.

Keywords: computational protein design/stability/TNF-ligand family/TRAIL


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Besides influencing the final pharmacokinetic and pharmacodynamic properties of a protein therapeutic, stability is also important throughout the production process and for the shelf-life of the final product (Marshall et al., 2003Go). Several strategies are used to augment the thermal stability of proteins (Fersht and Winter, 1992Go; Van den Burg and Eijsink, 2002Go). Both rational (Pantoliano et al., 1987Go; Matsumura et al., 1989Go; Villegas et al., 1996Go; Van den Burg et al., 1998Go) and directed evolution methods (Giver et al., 1998Go; Finucane et al., 1999Go; Jung et al., 1999Go) have been successfully used to improve stability. A disadvantage of a rational approach is that one can design only a limited number of potentially improved variants. In contrast, directed evolution methods allow large numbers of variants to be generated and screened. However, suitable selection/screening procedures are required, which are often not available or are very labor intensive. More recently, computational redesign algorithms have been employed to enhance stability, amongst other properties, of proteins (Malakauskas and Mayo, 1998Go; DeGrado et al., 1999Go; Ventura et al., 2002Go; Dantas et al., 2003Go). These methods combine computer design steps with in silico screening, permitting the screening of a much larger sequence space than is experimentally possible with high-throughput techniques. Efficient algorithms are needed to search the vast sequence space and accurate scoring functions are required in order to rank the best designs (Dahiyat, 1999Go; Looger and Hellinga, 2001Go). Recently, computational redesign has been used to generate a hyper-thermophilic variant of streptococcal Gb1 domain protein (Malakauskas and Mayo, 1998Go), to enhance the stability of the spectrin SH3 domain (Ventura et al., 2002Go) and to improve the (thermal) stability of the therapeutically interesting four-helix bundle cytokines, granulocyte colony-stimulating factor (G-CSF) (Luo et al., 2002Go) and human growth hormone (hGH) (Filikov et al., 2002Go).

In this study, we use the automated computer algorithm PERLA (Lacroix, 1999Go; Fisinger et al., 2001Go) and the empirical forcefield FOLD-X (Guerois et al., 2002Go) to improve the thermal stability of a multimeric all-ß-sheet protein, tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL; TNFSF10) (Wiley et al., 1995Go; Pitti et al., 1996Go). TRAIL is a member of the TNF ligand family. Ligands belonging to this family are involved in a wide range of biological activities, ranging from cell proliferation to apoptosis and they share similar structural characteristics. All monomeric subunits of these ligands consist of antiparallel ß-sheets, organized in a jellyroll topology, and these subunits self-associate in bell-shaped homotrimers, the bioactive form of the ligand (Figure 1A). Sequence homology is highest between the aromatic residues responsible for trimer formation. A trimer binds three subunits of a cognate receptor, each receptor subunit binding in the groove between two adjacent monomer subunits. The ligands are type II transmembrane proteins, but the extracellular domain of some members can be proteolytically cleaved from the cell surface, yielding a bioactive soluble form of the ligand. Recent reviews of the TNF ligand family are available (Locksley et al., 2001Go; Bodmer et al., 2002Go).



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Fig. 1. (A) Side view of the TRAIL trimeric complex, showing the three monomers in red, blue and green. (B) Top view of the same complex but viewed along the longitudinal axis, depicting the different sets used for design. Structure figures were generated using MOLMOL (Koradi et al., 1996Go).

 
TRAIL in its soluble form selectively induces apoptosis in tumor cells in vitro and in vivo, by a death receptor-mediated process (LeBlanc and Ashkenazi, 2003Go). Unlike other apoptosis-inducing TNF family members, it appears to be inactive against normal healthy tissue, therefore attracting great interest as a potential cancer therapeutic (Ashkenazi et al., 1999Go). Several crystal structures of TRAIL (Cha et al., 1999Go; Hymowitz et al., 2000Go) and TRAIL in complex with the death receptor 5 (DR5) (Hymowitz et al., 1999Go; Mongkolsapaya et al., 1999Go; Cha et al., 2000Go) are available. Unlike other TNF family members TRAIL has a zinc binding site in its trimeric core and the presence of the zinc ion is known to be vital for the trimeric structure and bioactivity (Bodmer et al., 2000Go; Hymowitz et al., 2000Go). Several versions of recombinant soluble TRAIL with different N-terminal fusions tags have been reported; however, these versions appear to have different bioactivity profiles in comparison with the non-tagged ‘wild-type’ soluble TRAIL encoding amino acids 114–281 (Ashkenazi, 2002Go). The increased in vitro toxicity towards certain normal healthy cells is especially noticeable in the presence of exogenous tags (Lawrence et al., 2001Go). We therefore chose to increase the stability of TRAIL by modification of the soluble ligand version (114–281), without addition of any exogenous tags. In view of possible use as a therapeutic protein, a close resemblance to the wild-type structure is desirable. To our knowledge, this is the first study that shows an improvement of the stability of a large multimeric protein structure by computational redesign. Methods used in this study are also applicable to other TNF family ligands.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
All reagents were of analytical grade unless specified otherwise. Isopropyl ß-D-1-thiogalactoside (IPTG), ampicillin and dithiothreitol (DTT) were purchased from Duchefa. Chromatographic columns and media were supplied by Amersham Biosciences. Restriction enzymes used were purchased from New England Biolabs. All other chemicals were obtained from Sigma.

Computational design of mutants

A detailed description of the protein design algorithm PERLA is available elsewhere (Lacroix, 1999Go) (http://proteindesign.embl-heidelberg.de) and its use has been previously described (Fisinger et al., 2001Go; Lopez et al., 2001Go; Reina et al., 2002Go; Ventura et al., 2002Go). In the case of oligomeric proteins such as TRAIL, protein design requires the following steps. First, residues of a monomer that could establish specific interactions with the contiguous monomer must be identified and selected. Second, side chains that contact the residues to be mutated must be identified to allow side chain movements that are necessary to accommodate the new residues introduced by the algorithm. The algorithm automatically selects these residues based on a geometric approach that takes C{alpha}–C{alpha} distances and the angle between C{alpha}–Cß vectors into consideration. Third, the algorithm places the amino acid repertoire at each position selected from a set of naturally occurring amino acids in a multiple sequence alignment of the TNF ligand family and eliminates those side chain conformations and amino acids that are not compatible with the rest of the structure. Fourth, all possible pair-wise interactions are explored to eliminate those combinations that are less favorable. Finally, an output of sequences and PDB coordinates corresponding to the best calculated solution (in terms of energy) is produced. The resultant PDB files containing the mutations were energy minimized using GROMOS 43B1 as implemented in Swiss-PdbViewer v3.7b2 (Guex and Peitsch, 1997Go) and evaluated by FOLD-X (Guerois et al., 2002Go) (http://fold-x.embl-heidelberg.de). The final energies of the models were compared with the reference wild-type TRAIL structure and expressed as {Delta}{Delta}G (kcal/mol).

Cloning and PCR

cDNA corresponding to human soluble TRAIL (amino acids 114–281) was cloned in pET15B (Novagen) using NcoI and BamHI restriction sites. The N-terminal sequence encoding a His-tag and protease recognition site was therefore removed. Mutants were constructed by polymerase chain reaction (PCR) using the QuikChange (Stratagene) method or a modified megaprimer method (Picard et al., 1994Go). The polymerase used was Pfu Turbo supplied by Stratagene. Purified mutagenic oligonucleotides were obtained from Invitrogen. Introduction of mutations was confirmed by DNA sequencing.

Expression and purification of wild-type TRAIL and mutants

The wild-type TRAIL and TRAIL mutant constructs were transformed to Escherichia coli BL21 (DE3) (Invitrogen). Wild-type TRAIL and M1 were grown at a 5 l batch scale in a 7.5 l fermenter (Applicon) using 4 x LB medium, 1% (w/v) glucose, 100 µg/ml ampicillin and additional trace elements. The culture was grown to mid-log phase at 37°C, 30% oxygen saturation and subsequently induced with 1 mM IPTG. ZnSO4 was added at a concentration of 100 µM to promote trimer formation. The temperature was lowered to 28°C and the culture was grown until stationary phase. Other mutants were grown in shake flasks at a 1 l scale at 250 r.p.m., using a similar protocol. Protein expression was induced when the culture reached OD600 0.5 and induction was continued for 5 h. In this case, the medium used was 2 x LB without additional trace elements.

The isolated pellet was resuspended in three volumes of extraction buffer [PBS pH 8, 10% (v/v) glycerol, 7 mM ß-mercaptoethanol]. Cells were disrupted using sonication and extracts were clarified by centrifugation at 40 000 g. Subsequently, the supernatant was loaded on a nickel-charged IMAC Sepharose fast-flow column and wild-type TRAIL and TRAIL mutants were purified as described by Hymowitz et al. (2000)Go with the modifications that 10% (v/v) glycerol and a minimal concentration of 100 mM NaCl were used in all buffers to prevent aggregation during purification. After the IMAC fractionation step, 20 µM ZnSO4 and 5 mM DTT (instead of ß-mercaptoethanol) were added to all buffers. Finally, a gel filtration step, using a Hiload Superdex 75 column, was included. Purified proteins were >98% pure as determined using a colloidal Coomassie Brilliant Blue-stained SDS–PAGE gel. Purified protein solutions were flash frozen in liquid nitrogen and stored at –80°C.

Circular dichroism (CD) spectroscopy

CD spectra were recorded on a Jasco J-715 CD spectrophotometer equipped with a PFD350S Peltier temperature-control unit (Jasco). Rectangular quartz cuvettes with a pathlength of 0.2 cm were used. Protein samples were dialyzed against PBS pH 7.3 and adjusted to a final concentration of 100 mg/ml. Wavelength spectra were recorded between 250 and 205 nm using a 0.2 nm step size and 1 nm bandwidth at 25°C. Temperature scans from 25 to 98°C were performed at 222 nm with a scan rate of 40°C/h. Thermal decay measurements were performed at 73°C for 1 h at 222 nm.

Bioactivity of TRAIL mutants in vitro

The bioactivity of wild-type TRAIL and TRAIL mutants was determined using a viability assay according to the manufacturer's instructions (Celltiter Aqueous One, Promega). Colo205 human colon carcinoma cells (ATCC number CCL-222) were cultured in RPMI 1640 Glutamax containing 10% heat-inactivated fetal calf serum and 100 units/ml penicillin–streptomycin. All reagents were supplied by Invitrogen. A concentration series of the wild-type TRAIL or TRAIL mutants was made in cell culture medium. A 50 ml volume of each dilution was added to a 96-well tissue culture micro plate (Greiner) and 100 ml of cell suspension were added, to a final cell number of 1 x 104 cells/well. Mixtures were incubated for 16 h at 37°C under a humidified atmosphere containing 5% CO2. Subsequently, 20 ml of MTS reagent were added. Cell viability was determined after 30 min of incubation by measuring the absorption at 490 nm.

Receptor binding

Binding experiments were performed using a Biacore 3000 surface plasmon resonance-based biosensor (Biacore, Uppsala, Sweden), at 25°C. Recombinant receptors were purchased from R&D systems (Minneapolis, MN). Immobilization of the receptors on the sensor surface of a Biacore CM5 sensor chip was performed following a standard amine coupling procedure according to the manufacturer's instructions. A reference surface was generated simultaneously under the same conditions but without receptor injection and used as a blank to correct for instrument and buffer artifacts. Purified wild-type TRAIL and TRAIL mutants were injected in duplicate at a concentration of 2 µg/ml and at a flow rate of 20 µl/min. Binding of ligands to the receptors was monitored in real time. The receptor/sensor surface was regenerated using 3 M sodium acetate pH 5.2 injections.


    Results
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Computer screening

Novel mutants of TRAIL have been designed in order to increase the stability of the bioactive trimer. Predictions were based on the automated computer algorithm PERLA (Fisinger et al., 2001Go; Lopez et al., 2001Go), as described in the Materials and methods section. Briefly, the program performs strict inverse folding: a fixed backbone structure is decorated with amino acid side chains from a rotamer library. Relaxation of strain in the protein structure is achieved via the generation of subrotamers. Most terms of the scoring function are balanced with respect to a reference state, to simulate the denatured protein. The side chain conformers are all weighted using the mean-field theory and finally candidate sequences with modelled structures (PDB coordinates) are produced. Energy evaluation of the modeled structures was carried out by a modified version (J.Schymkowitz, J.Borg, F.Rousseau and L.Serrano, in preparation) of FOLD-X (Guerois et al., 2002Go) (available at http://fold-x.embl-heidelberg.de). The force field module evaluates the properties of the structure, such as its atomic contact map, the accessibility of its atoms and residues and the backbone dihedral angles, in addition to the H-bond network and electrostatic network of the protein. The contribution of water molecules making two or more H-bonds with the protein is also taken into account. The algorithm then proceeds to calculate all force field components: polar and hydrophobic solvation energies, van der Waals' interactions, van der Waals clashes, H-bond energies, electrostatics and backbone and side chain entropies.

Selection of the template sequence

The template selected was 1DU3 (Cha et al., 2000Go). The crystal structure at 2.2 Å resolution contains the trimeric structure of human TRAIL complexed with the ectodomain of the DR5 receptor. The TRAIL monomer lacks an external, flexible loop (130–146), not involved in receptor binding or in monomer–monomer interaction. To complete the molecule, this loop was modeled using the structure of 1D4V (2.2 Å) (Mongkolsapaya et al., 1999Go), a monomeric TRAIL complexed with DR-5 receptor, having the atomic coordinates of the loop. Finally, the TRAIL molecule was isolated by removing the receptor molecules from the PDB file.

Computational design of mutants

The visual inspection of the isolated monomers, monomer–monomer interface and central core of TRAIL showed several residues as potential candidates for mutagenesis. The highly conserved hydrophobic residues were discarded from this list. After generating the mutants we identified whether there were residues involved in receptor binding. These residues in principle could not be mutated without disrupting interactions with the receptor. However, it could be that a small decrease in binding affinity could be compensated by an increase in stability. Thus one TRAIL variant (M2), which showed a significant predicted increase in stability but also contained residues involved in receptor interaction, was retained for subsequent experimental analysis.

The sequence space search for every position was simplified by checking the naturally occurring amino acids in a multiple sequence alignment of proteins belonging to the TNF ligand family, thus decreasing the computing time and subsequently focusing on non-conserved residues. The use of protein rational design and force field algorithms allowed the identification of a list of mutant sequences with potential relevance for TRAIL stability. Four sets of residues were selected for design (Figure 1B and Table I): (1) non-conserved residues at the surface of the monomer ('monomer' set), (2) non-conserved residues near positions close to the interface between two monomers (‘dimer’ set), (3) non-conserved residues along the central trimeric axis (‘trimer’ set) and (4) a miscellaneous set (‘misc. set’). The automated computer design algorithm was applied as described previously (Angrand et al., 2001Go). Amino acid substitutions were introduced at the non-conserved residue positions in conformations (side chain rotamers) compatible with the rest of the structure. Subsequently, favorable mutations were combined and evaluated in terms of free energy (kcal/mol) and unfavorable combinations (e.g. high van der Waal clashes) were eliminated. An output of sequences and coordinates was produced and ranked in terms of free energy and subsequently reintroduced in the design algorithm for a second, third or fourth round of design, if necessary. Table I summarizes the list of mutants assayed in silico for increased stability of TRAIL. Some of these predictions were discarded directly after theoretical energy calculations, without further experimental analysis.


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Table I. Residues initially considered for design

 
Description of the tested mutations

Predicted mutants were energy minimized and subsequently analyzed with FOLD-X. The energy values obtained were compared with that of the wild-type structure and used for discrimination of candidates. Mutants were selected based on an improvement in free energy relative to wild-type TRAIL (Table II). In the monomeric set, M1 (E194I, I196S) was selected because of the large improvement of energy compared with wild-type TRAIL ({Delta}{Delta}G = –9.7 kcal/mol per monomer). This low energy value is due to the fact that a trimer is being studied, in addition to the presence of significant van der Waals' clashes in the crystal structure (~5 kcal/mol per monomer), which are removed upon mutation. The mutations are located in the external loop connecting the C and D anti-parallel ß-strands (CD loop), following the notation according to Eck et al. (1992)Go. The predicted increase in stability of M1 can be explained since Glu194 is surrounded by hydrophobic groups (Trp231, Phe192, Ala235) and the carboxyl group is uncompensated. The mutation Glu194 to Ile rectifies this situation by replacing the charged residue for a medium-sized hydrophobic residue. Conversely, Ile196 is surrounded by polar residues (Asn202, Lys233) and is very close to the backbone, resulting in probable van der Waals clashes. Mutation to Ser avoids clashes and allows formation of a hydrogen bond to Asn202, located in the opposite part of the CD loop (Figure 2A). Both mutations improve polar solvation energy, in addition to ameliorating side chain and backbone entropy.


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Table II. Computational design results

 


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Fig. 2. (A) Comparison between wild-type TRAIL and M1 of the local environment around residues 194 and 196. (B) Comparison between wild-type TRAIL and M2. Backbones of the two adjacent monomers are in green and blue, respectively, and the backbone of the DR5 receptor is in gray. Hydrogen-bond interactions are depicted in dashed green lines.

 
In the dimeric set (Table II), the design of M2 (D203I, Q205M, Y237F) leads to the creation of a hydrophobic cluster to stabilize the interaction between residues 203 and 205 (D strand) of one monomer and residue 237 (F strand) of the adjacent monomer. Gln205 and Tyr237 together form an intermolecular hydrogen bond and Asp203 points to a gap in the monomer–monomer interface. Mutation to Ile (203), Met (205) and Phe (237) breaks the Q205–Y237 hydrogen bond, but facilitates the tight packing of these residues, improving van der Waals interactions, hydrophobic and polar solvation energies of the entire TRAIL molecule, without a further increase in van der Waals clashes (Figure 2B). Although FOLD-X predicted that the affinity of M2 for the DR5 receptor is lower ({Delta}{Delta}Gbinding = 7.3 kcal/mol per monomer) than for wild-type TRAIL, this mutant was retained as a control to evaluate the accuracy of the procedure.

Residue 225 of M3 (S225A), belonging to the ‘misc. set’, is located in strand E and is solvent exposed in the monomeric form. However, after trimerization, this position becomes buried in a small pocket, leaving the side chain of the hydrogen bond donor Ser uncompensated. After mutation to Ala, the energy of the model is better than wild-type TRAIL for both polar and hydrophobic solvation energies, in addition to side chain entropy.

The Arg227 residues of the trimeric set mutant (M4) are located in strand E, equidistantly opposed in a central position along the longitudinal axis of the TRAIL trimer. The three arginines are surrounded by hydrophobic (Ile242), polar (Ser241, Ser225) and aromatic (Tyr240, Tyr243) residues. These tyrosines direct the hydroxyl groups away from Arg227, thus creating a rather hydrophobic cavity. The high concentration of positive charges is apparently not well compensated, since it forms only hydrogen bonds with the backbone (carbonyl groups of Ser241). Thus, the mutation of these positions to Met could help to accommodate the hydrophobic environment, and also to decrease the repulsion of monomers due to uncompensated positive charges.

Mutagenesis and purification of mutants

The highest ranking mutant from each of the four sets was selected for further experimental analysis (Table II). A mutant (C1) combining the mutations of M1 and M3 was also constructed. All the designed TRAIL mutants were expressed in E.coli and purified successfully with a protein yield of ~0.7–2 mg/l. Far-UV CD wavelength spectra indicated that all mutants were properly folded with characteristics of a ß-sheet-containing protein, similar to that of wild-type TRAIL. Gel filtration and dynamic light scattering measurements showed that all mutant protein solutions contained a single molecule species, consistent with a trimeric oligomerization state. Analytical ultracentrifugation with wild-type TRAIL and M1 corroborated this finding (data not shown).

Thermal unfolding

The thermal unfolding of wild-type TRAIL and TRAIL mutants was monitored by CD, measuring changes in molar ellipticity at 222 nm upon heating. Figure 3 shows the heat-induced changes of wild-type TRAIL and TRAIL mutants. TRAIL shows an onset of unfolding at ~70°C and has a transition midpoint (Tm) of 77°C. The TRAIL mutants show, however, onset of unfolding at increased temperatures and higher transition midpoints (Figure 3). For M1 the onset of unfolding was at ~76°C and the transition midpoint was at 85°C. M2 showed an onset of unfolding at ~74°C. M3 gave intermediate values between those of wild-type TRAIL and M1, with an onset of unfolding of 73°C and a transition midpoint of 80°C. Mutant C1, representing the combined mutations of M1 and M3, showed values comparable to those of M1. The mutant belonging to the trimeric set (M4), however, showed an experimentally determined stability of ~3°C less than wild-type TRAIL and was therefore discontinued. The initial increase in molar ellipticity around 76°C for M2 is due to an overall change of the far-UV spectrum, reflecting a loss of structural properties of the starting material (data not shown). Upon cooling, all protein solutions were turbid, indicating irreversible aggregation, and therefore no thermodynamic parameters could be derived. Far- and near-UV wavelength CD scans at increasing temperatures confirmed the above findings (data not shown).



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Fig. 3. Thermal denaturation profiles of wild-type TRAIL (closed circles), M1 (closed squares), M2 (open circles), M3 (open squares) and C1 (closed triangles).

 
In vitro bioactivity and binding of designed mutants

Bioactivity of the TRAIL mutants was assessed in vitro using the Colo205 human colon cancer cell line with an MTT-based viability assay. A reduction in viability was measured using increasing concentrations of wild-type TRAIL or TRAIL mutants relative to the control. Whereas M1, M3 and C1 showed a bioactivity comparable to that of wild-type TRAIL (ED50 {approx} 5 ng/ml), M2 exhibited bioactivity of nearly one order of magnitude lower (ED50 {approx} 50 ng/ml). Real-time binding of wild-type TRAIL and TRAIL mutants to the death receptors DR4 and DR5 was assessed using surface plasmon resonance with a Biacore 3000 instrument. Sensorgrams of M1, M3 and C1 were identical with that of wild-type TRAIL. In contrast, M2, although showing a similar level of binding to both receptors, displayed an increased off-rate when compared with the wild-type TRAIL sensorgram (Figure 4).



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Fig. 4. Binding of wild-type TRAIL (closed circles), M1 (closed squares) and M2 (open circles) to DR5 (dotted lines) and DR4 (solid lines) receptors.

 
Accelerated thermal stability study

In order to test the stability of TRAIL and TRAIL mutants over time, an accelerated thermal stability measurement was performed. The temperature of 73°C was chosen to measure effects on stability within a 1 h timeframe. At this temperature, wild-type TRAIL starts to unfold, whereas the mutants are still properly folded (Figure 3). Protein solutions with the same concentration as used in the thermal unfolding measurements were incubated at 73°C for 1 h and changes in molar ellipticity at 222 nm were measured (Figure 5). The ellipticity of wild-type TRAIL decreased from the onset, giving a half-life of ~13 min. The signal for the M1, M2 and C1 mutants remained essentially constant, indicating an increased thermal stability. M3 showed a half-life of ~24 min. These measurements, however, are not indicative of the bioactive trimeric structure of the TRAIL molecule, but of the secondary structure of the monomeric unit. To monitor a concomitant increase in biological activity at elevated temperatures of the mutants with unchanged biological activity (M1, M3 and C1), protein solutions with the same concentrations as used in the thermal unfolding measurements were incubated at 73°C and samples were taken at regular intervals for 1 h. Samples were subsequently diluted in tissue culture medium and added to Colo205 cells, resulting in a final concentration of 100 ng/ml. After overnight incubation, the viability of the cells was measured using an MTT assay. Wild-type TRAIL showed decrease in bioactivity after 20 min of incubation, whereas M1 and C1 retained full bioactivity after incubation at 73°C for 1 h (Figure 6). M3 displayed an intermediate bioactivity between wild-type TRAIL and the other mutants. The increases in thermal stability of the mutants as measured with CD could therefore be correlated with a more stable biologically active trimeric molecule.



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Fig. 5. Stability of wild-type TRAIL (closed circles), M1 (closed squares), M2 (open circles), M3 (open squares) and C1 (closed triangles) at 73°C for 60 min.

 


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Fig. 6. Remaining biological activity of wild-type TRAIL, M1, M3 and C1 (from left to right) upon incubation at 73°C for 60 min. Biological activities are calculated relative to the value observed at 0 min.

 

    Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Others have previously applied computational engineering techniques to improve the thermal stability of {alpha}-helical proteins or monomeric ß-sheet molecules (Vriend and Eijsink, 1993Go; Villegas et al., 1996Go; Chiti et al., 1999Go). However, frequently, monomeric proteins of <100 amino acids were used as targets. To our knowledge, this report is the first example of computational redesign of a large trimeric all-ß-sheet protein towards a more thermally stable variant. Significantly, it shows that the principles learned from design and engineering of small proteins can also be applied for large multimeric protein complexes.

The wild-type TRAIL (114–281) molecule has a relatively high thermal stability compared with some members of the TNF ligand family. Human TNF-{alpha}, for example, has an apparent Tm of 65°C as measured with CD (Narhi et al., 1996Go) and the CD40L receptor binding domain has an apparent Tm of 60°C as measured with differential scanning calorimetry (DSC) (Morris et al., 1999Go). In parallel investigations, we could show using CD that RANKL, however, is more thermally stable than TRAIL, with an apparent Tm 5°C higher than wild-type TRAIL, confirming another study (Willard et al., 2000Go). In this study, we investigated the possibility of further increasing the thermal stability of TRAIL, as a model for all-ß-sheet proteins, through the use of computational engineering.

We succeeded in extending the thermal stability of the ß-sheet protein by more than 5°C by using a combined approach, employing both TNF ligand family alignment information and an automated computational design algorithm. Owing to the non-reversible nature of the unfolding reaction, the apparent Tm is not a perfect indication of an increase in stability. From a functional point of view, therefore, it also makes sense to study the time taken for the protein to denature at high temperature and to relate this to an effect on biological activity. The accelerated thermal stability study showed that the increase in thermal stability of the mutants as measured with CD spectroscopy (Figure 5) can be correlated with the preservation of overall structural characteristics as highlighted by the lasting bioactivity of M1 during the experimental timeframe (Figure 6). When measuring the residual bioactivity of wild-type TRAIL and TRAIL mutants upon incubation at 73°C for 1 h, it was shown that, whereas wild-type TRAIL was all but thermally inactivated after ~20 min, the mutants, significantly, had an improved stability with respect to wild-type TRAIL (Figure 5). According to the Arrhenius equation, a measured increase in stability for M1 at 73°C could also correlate with an increase in stability for M1 at more relevant temperatures, such as 37°C or room temperature, provided that the type of degradation mechanism is the same at both temperatures. Although not tested in this study, it has been shown that in the case of certain therapeutically interesting proteins, improvement of thermal stability can also be indicative of an improved in vivo half-life (Filikov et al., 2002Go; Luo et al., 2002Go). This could be of particular interest for the therapeutic use of TRAIL. Preclinical studies showed that wild-type TRAIL was rapidly eliminated from both rodents and non-human primates, with half-lives ranging from 3.6 min (mouse) to 27 min (chimpanzee) (Kelley et al., 2001Go).

It is advantageous to use alignment information in order to focus the design on non-conserved residue positions, because conserved residues are usually retained in a family for a good reason and it is probable that any mutation will decrease protein stability (Serrano et al., 1993Go; Steipe et al., 1994Go). On the other hand, regions with high sequence variability are tolerant to mutation and it can be expected that variants that stabilize the protein can be found in these regions (Serrano et al., 1993Go). To accomplish our goal of redesigning a ß-sheet protein, TRAIL, and to generate stable variants with the minimum number of mutations, the conserved residues forming the trimeric interface were therefore largely excluded from the prediction/optimization strategy. This resulted in an approach which focused mainly on improvement of the stability of the monomer (intra-chain stabilization; monomeric set) or improving monomer-monomer contacts (inter-chain stabilization; dimeric set); see Table I.

M1, M2, M3 and C1 showed, in agreement with our predictions, an increase in thermal stability (Table II, Figures 3, 5 and 6). Different basic principles were used in the M1, M2 and M3 designs. M1 shows an example of intra-chain stabilization. Stabilization of the flexible CD loop at the surface of each TRAIL monomer results in an increased stability of the entire trimer. This loop is not directly involved in receptor binding and is disordered in uncomplexed wild-type TRAIL structures (Cha et al., 1999Go; Hymowitz et al., 2000Go), but becomes ordered on binding to DR5 (Hymowitz et al., 1999Go; Mongkolsapaya et al., 1999Go; Cha et al., 2000Go). M2, however, illustrates the optimization of the interactions between two adjacent monomers, i.e. inter-chain stabilization. Although we were successful with the above designs, in other cases such as the combination mutant C1 (M1 and M3 combined) or the M4 mutant, we failed in our predictions. There could be several reasons behind this, but it also shows the limitations of design methods. Inherent limitations on force fields, resolution of the structures used as templates and the omission of protein dynamics in the exercise are some of the factors behind protein design failures.

The increase in thermal stability did not affect the biological activity of M1, M3 and C1. M2 was more stable than wild-type TRAIL but the formation of an electrostatic interaction between Gln205 and Arg154 of the DR5 receptor was prevented (Figure 2B). This resulted in a subsequent 10-fold decrease in biological activity when compared with wild-type TRAIL, as predicted by FOLD-X ({Delta}{Delta}Gbinding = 7.3 kcal/mol per monomer). Our findings confirmed an earlier study showing decreased bioactivity of alanine mutants at these positions (Hymowitz et al., 2000Go). Analysis of binding to the DR4 and DR5 receptors, using surface plasmon resonance, shows an increased off-rate for M2, indicating a lower affinity for both receptors when compared with wild-type TRAIL and M1 (Figure 4). Since ligand-receptor binding sites are normally ‘high-energy regions’, the M2 mutations were expected to stabilize the TRAIL molecule. Hence this could be regarded as an example of a possible increase in stability which is counterbalanced in evolution by loss of function.

Frequently, other computational redesign studies limited the screening for improvement of thermal stability to the core of the molecule (Malakauskas and Mayo, 1998Go; Filikov et al., 2002Go; Luo et al., 2002Go). Here we show that computational redesign techniques can also involve inter-chain interfaces and surface residues of the molecule, to stabilize the structure successfully.

Performance of PERLA/FOLD-X was successful in the case of the intra-chain (monomer) set, the inter-chain (dimeric) set and the miscellaneous set. The experimental data corresponding to these designs showed that all variants within these sets were more stable than wild-type TRAIL. Significantly, we could show that stabilization of the CD loop in a single monomer resulted in stabilization of the entire trimeric molecule (Figure 2A).

Our studies have shown that computer redesign of a more thermal stable multimeric all ß-sheet-protein is achievable. Computational protein redesign is therefore a valuable addition to other protein engineering methodologies, such as directed evolution or experimental high-throughput approaches, as a tool for the improvement of protein properties. Since the computational method used in our study is general applicable, our findings can be further applied to design other TNF ligand family members with improved thermal stability.


    Acknowledgments
 
We thank Rob van Weeghel and Ron Suk for providing purified wild-type TRAIL. We would also like to express gratitude to Afshin Samali and Eva Szegezdi for helpful discussions, and to Arie Geerlof, Sjouke Piersma and Johanna Vrielink for technical assistance. This research was partly funded by the EU 5th Framework Program (QLK3-CT-2001-00498).


    References
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 Abstract
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 Materials and methods
 Results
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 References
 
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Received June 29, 2004; revised September 24, 2004; accepted October 5, 2004.

Edited by Jane Clarke





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