Identification and Computational Design of an α-Gliadin Endopeptidase

E. coli platform, that have an available crystal structure in complex with their peptide substrates. Finally, we examined the amino acid specificities of the candidate endopeptidases to identify those that are specific to an amino acid motif similar to our targeted PQ motif. To engineer a peptidase that can degrade gliadin peptides under gastric conditions, we first focused on identifying a suitable naturally occurring endopeptidase that could be used as a starting point for our engineering efforts. Ideally, such an enzyme would exhibit high stability and activity at an acidic pH, with specificity for a dipeptide amino acid motif similar to the PQ motif found in the immunogenic gluten peptides (Figure 1 ). We searched the MEROPS Peptide Database to identify enzyme families that are known to be active in acidic pH. These are the aspartic and glutamic peptidases, and the S10 and S53 families of serine peptidases. We further narrowed our search by selecting endopeptidases, produced in a soluble form using anplatform, that have an available crystal structure in complex with their peptide substrates. Finally, we examined the amino acid specificities of the candidate endopeptidases to identify those that are specific to an amino acid motif similar to our targeted PQ motif.

K a of 4.1), instead of a histidine (pK a of 6.5), in the catalytic triad allows this enzyme to function at low pH. Indeed, KumaWT exhibits optimal activity over the pH range of 2–4,E. coli, On the basis of the above criteria, we identified the enzyme kumamolisin-As (KumaWT) as an excellent candidate. KumaWT is a serine endopeptidase that demonstrates a serine–glutamate–aspartate catalytic triad instead of the serine–histidine–aspartate triad of traditional serine proteases. The involvement of a glutamate (pof 4.1), instead of a histidine (pof 6.5), in the catalytic triad allows this enzyme to function at low pH. Indeed, KumaWT exhibits optimal activity over the pH range of 2–4, (12) which matches the approximate pH range of the human stomach after a meal. (7) KumaWT also demonstrates high stability and activity at the physiologically relevant temperature of 37 °C. (13) The purification of this enzyme yields significant quantities of soluble protein using standard recombinant protein production methods in (13) an important property both for screening mutant libraries and for its eventual production for use as an OET. Finally, KumaWT naturally recognizes a specific dipeptide motif as opposed to a single amino acid. (13) This property is potentially important for an OET meant to be taken during digestion, since dipeptide specificity should result in reduced competitive inhibition from other food-derived peptides in the stomach or off-target effects due to degradation of other necessary proteins in the gut.

An effective OET for celiac disease would ideally be specific for a PQ motif, due to the frequent occurrence of this dipeptide in immunogenic gluten-derived α-gliadin oligopeptides (Figure 1 ). KumaWT exhibits specificity for proline at the P2 position of its peptide substrate, matching the P2 residue of interest for the degradation of immunogenic α-gliadin peptides. (13) In the P1 site, KumaWT prefers the positively charged amino acids arginine or lysine. (13) Despite this preference, KumaWT is also capable of recognizing glutamine at the P1 position, albeit at a significantly decreased level compared with its recognition of arginine or lysine. (13) This low level of activity for glutamine at the P1 position suggests that KumaWT might be amenable to re-engineering to prefer glutamine at this position. At the P1′ site, KumaWT demonstrates broad specificity, which is desirable since the residue in the position after the PQ motif varies among the different immunogenic peptides (Figure 1 ). (14)

Given these characteristics of KumaWT, we sought to computationally redesign the S1 binding pocket of KumaWT such that it would prefer a PQ dipeptide motif over the native PR or PK substrates. Using the Rosetta Molecular Modeling Suite, (15) we modeled the PR dipeptide in the S1 binding pocket of the KumaWT crystal structure (PDB-ID 1T1E ). This revealed that two negatively charged amino acids, D358 and D368, likely facilitate binding of the positively charged amino acids in the P1 position (Figure 2 A). The native specificity for proline at P2 appears to be derived in large part from a hydrophobic interaction of this residue with the aromatic ring of W318 in the S2 pocket of the enzyme. Because specificity at the P2 position for proline is desired for OET, we maintained this native tryptophan during the design of the S1 pocket.

Figure 2 Figure 2. Computational models of the peptide binding sites for KumaWT and KumaMax. (A) KumaWT in complex with a PR dipeptide motif (brown). (B) KumaMax in complex with the designed PQ dipeptide motif (brown, native P; green, designed Q). Computationally designed residues in the active site are labeled and highlighted in sticks (KumaWT, gold; KumaMax, purple). The modeled peptides were based on a bound structure of kumamolisin-AS (PDB ID 1T1E) and final structures were generated using the Rosetta Molecular Modeling Suite. Images were generated using PyMol v1.5 (http://www.pymol.org/).

To redesign the substrate specificity of the S1 pocket to prefer glutamine at the P1 position, we modeled mutations in the KumaWT binding pocket using the Foldit interface to the Rosetta Molecular Modeling Suite. (16) A tetrapeptide that represents a common immunogenic motif found throughout α-gliadin, PQLP, was modeled into the P2 to P2′ active site positions. The crystal structure already contained a polypeptide bound in the active site, so the residues of this polypeptide were mutated using Rosetta to the PQLP tetrapeptide motif. A total of 75 residues within an 8 Å sphere of the tetrapeptide were targeted for mutagenesis during the design process. Combinatorial sets of mutations were analyzed for their predicted effect on the overall energy of the new enzyme–PQLP substrate complex. A mutation set was considered for experimental characterization if the predicted energy of the enzyme–substrate complex was not significantly higher than wild-type. To accommodate the smaller, neutral amino acid glutamine, we focused our design efforts on removing the negative charge of the S1 pocket during the design process, filling in open space that resulted from the replacement of the larger arginine with glutamine and providing hydrogen bonds to the amide functional group of the glutamine. This computational modeling yielded 261 designs containing from one to seven simultaneous mutations.

E. coli BL21(DE3) cells.k cat /K M values, ranged from 2-fold to 120-fold more active than KumaWT (Supplementary Table 2, In order to test the activity of these designed peptidases against the PQLP motif, the desired mutations were incorporated into the KumaWT nucleotide sequence using site-directed mutagenesis, and mutant enzyme variants were produced inBL21(DE3) cells. (16) Enzyme variants were then screened for enzymatic activity in clarified whole cell lysates at pH 4 using the synthesized peptide analogue QXL520-PQPQLP-K(5-FAM)-NH2 (FQ). This substrate is an α-gliadin hexapeptide analogue conjugated to 5-carboxyfluorescein (5-FAM) at the C-terminus and to the nonfluorescent quencher QXL520 at the N-terminus. Thus, peptidase activity can be measured by the increased fluorescence resulting from the release of 5-FAM from the quencher. Of the 261 enzyme variants tested in this assay, 20% had decreased enzymatic function compared with KumaWT, 30% were similar in activity to KumaWT, and 50% had an increase in activity against this substrate (Supplementary Table 1 and Supplementary Figure 1, Supporting Information ). Twenty-eight of the most promising enzyme variants that exhibited a 2–70- fold increase in activity in cell lysates were then purified in order to obtain an accurate comparison of enzymatic activity to that of KumaWT. After purification and correction for protein concentration, the catalytic efficiencies of these enzymes, as determined by theirvalues, ranged from 2-fold to 120-fold more active than KumaWT (Supplementary Table 2, Supporting Information ). The most active variant, which we termed KumaMax, was selected for further characterization.