Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0: a quantitative molecular docking study

Background HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 – 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pKa of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positively charged and very hydrophilic, while at pH 7.0 imidazole is unprotonated, making Histidine less hydrophilic. We develop here a method to predict peptide binding to the four most frequent HLA-DP proteins: DP1, DP41, DP42 and DP5, using a molecular docking protocol. Dockings to virtual combinatorial peptide libraries were performed at pH 5.0 and pH 7.0. Results The X-ray structure of the peptide – HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. The resulting models were used to produce virtual combinatorial peptide libraries constructed using the single amino acid substitution (SAAS) principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were normalized and used to generate Docking Score-based Quantitative Matrices (DS-QMs). The predictive ability of these QMs was tested using an external test set of 484 known DP binders. They were also compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0 and showed significantly improved predictions for three of the four DP proteins, when compared to the existing servers. They are able to recognize 50% of the known binders in the top 5% of predicted peptides. Conclusions The higher predictive ability of DS-QMs derived at pH 5.0 may be rationalised by the additional hydrogen bond formed between the backbone carbonyl oxygen belonging to the peptide position before p1 (p-1) and the protonated ε-nitrogen of His79β. Additionally, protonated His residues are well accepted at most of the peptide binding core positions which is in a good agreement with the overall negatively charged peptide binding site of most MHC proteins.


Background
Major histocompatibility complex class II (MHC class II) proteins are normally found in B lymphocytes, dendritic cells, and macrophages; they are primarily involved in processing foreign, extracellular antigens, which are endocytozed and then enclosed in endosomes containing acid proteases. The pH in endosomes ranges from 4.5 to 6.0 [1]. In endosomes, antigens are degraded into oligopeptides.
MHC class II proteins are synthesized in the endoplasmic reticulum (ER) and bind to a protein known as the MHC class II-associated invariant chain (Ii). Ii facilitates the export from the ER of MHC class II proteins and prevents binding to peptides resident in the ER. The complex MHC-Ii enters a specific endocytic compartment, called MIIC (MHC class II compartment), which fuses with endosomes. Ii is cleaved initially to the so-called CLIP fragment, with CLIP later being displaced by high-affinity peptides. The peptide -MHC class II protein complex is translocated to the cell surface, where it is recognized by CD4+ T cells.
Peptides binding to MHC class II vary in length from 12 to 25 amino acids, yet the binding site accepts only nine peptide residues, the rest extending from both ends as the cleft is open-ended. The side chains of bound peptides project into several binding pockets while a system of hydrogen bonds forms between the peptide backbone and the side chain atoms of the MHC [2].
Human MHCs, known as HLA (Human Leukocyte Antigens), are extremely polymorphic and polygenic. The IMGT/HLA database lists over 1,600 HLA class II proteins [3]. HLAs class II contain three loci: DR, DQ and DP. DR and DQ proteins are well studied, while DP was initially considered of lesser importance in immune responses. However, it is now clear that HLA-DP proteins have important roles in mediating the immune response to many diseases, such as graft-versus-host (GVH) disease [4], sarcoidosis [5], juvenile chronic arthritis [6], Graves' disease [7], hard metal lung disease [8] and especially, chronic beryllium disease [9]. Recently, the X-ray structure of the HLA-DP2 (DPA*0103, DPB1*0201) in complex with a self-peptide derived from the HLA-DR α-chain has been determined [10]. Although the overall structure of DP2 is similar to that of other MHC class II proteins, it contains a unique solvent-exposed acidic pocket containing three glutamic acids (Glu 26β , Glu 68β and Glu 69β ). This pocket may be able to bind Beryllium and present it to T cells, providing a mechanistic explanation that underlies chronic Beryllium disease [10,11]. X-ray data also reveals that the DP2 binding site comprises four binding pockets: deep, hydrophobic pockets p1 and p6; large, shallow, negatively charged p4; and deep, narrow and polar pocket p9.
Peptides bind to MHC class II proteins in an acidic environment (pH~5.0). Bell-shaped profiles with optima at pH 5.0 are observed in many peptide -MHC class II binding experiments [12][13][14]. Acidic pH markedly elevated association rate constants 40 fold; dissociation rates are, by contrast, almost unchanged in the pH range 5.0 -7.0 [13]. The equilibrium binding level is thus enhanced at pH 5.0. The influence of pH on the binding equilibrium can be explained by subtle conformational changes due to altered protonation and deprotonation states and near neighbor interactions. The only amino acid sensitive to pH in the range 5.0 -7.0 is histidine. The side-chain pK a of the His imidazole is 6.0. At pH 5.0 imidazole is protonated and His is thus positively charged and very hydrophilic. At pH 7.0, imidazole is unprotonated making His less hydrophilic. Thus, a pair of amino acids consisting of His and a hydrophobic residue could function as a pH-sensitive "His button" [14]. It "closes" at pH 7.0 (hydrophobic interaction) and "opens" at pH 5.0 (hydrophobiccharge repulsion). Such pH-sensitive switch was observed for His 33α in the formation of HLA-DR1 -HLA-DM complexes [14].
There are five His residues in the HLA-DP binding cleft: four belong to the α-chain (positions 5, 16, 44 and 79) and one to the β-chain (position 79). All five histidine residues are conserved among DP proteins. His 79β side chain contacts the binding peptide in the vicinity of peptide position 2. Recently, a favorable π-π stacking between the aromatic rings of His 79β and His 2peptide was identified [15]. The other His residues are remote from the binding site and do not make contact with the bound peptide.
Molecular docking is a key structure-based method with significant utility in drug design, bioinformatics, and immunoinformatics. In contrast to sequence-based approaches, virtual docking experiments do not require extensive pre-existing experimental data. The only information necessary is a reliable model of the peptide -MHC protein complex, as provided by X-ray crystallography. Docking methodology allows the development of predictive models where the training and test data are fully independent, thus, eliminating any possibility of over-fitting. We use rigid docking to identify optimised bound peptide conformations; since even for a nonamer, a fully unconstrained peptide docking would be of a prohibitively extended duration. However, since the number of distinct peptide conformations observed within currently-known X-ray structures remains very small, we make the parsimonious and wholly-reasonable assumption that peptides will bind in a similar conformation. Molecular docking has been extensively and rigorously tested on both peptide-MHC class I and peptide-MHC class II complexes. As an approach to evaluating peptide binding to MHCs, it has proved to be rapid, accurate, and reliable [15][16][17].
Recently, we applied a molecular docking protocol to a library of modeled peptide-DP2 complexes to assess the contribution of each of the 20 naturally occurred amino acids at each of the nine binding core positions and four flanking residues (two at both ends) [15]. The normalized binding scores formed a quantitative matrix (QM), known also as a position-specific scoring matrix (PSSM). PSSMs are a commonly used representation of motifs or patterns within biological sequences. The predictive ability of the derived QM was assessed using an external test set of known binders to DP2. A comparison to predictions made by existing servers for DP2 binding prediction indicated an improvement in performance offered by our docking score-based QM (DS-QM) [15].
In the present study, we modelled by homology four of the most frequent HLA-DP proteins [18]: DP1 (DPA1*0201/DPB1*0101), DP41 (DPA1*0103/ DPB1*0401), DP42 (DPA1*0103/DPB1*0402) and DP5 (DPA1*0201/ DPB1*0501). We applied a similar docking protocol to derive DS-QMs for peptide binding prediction [15]. To investigate the influence of pH on the predictive ability, different QMs were derived at two pH values: 5.0 and 7.0. The QMs were validated using external test sets and compared to other servers for DP binding prediction. Additionally, in order to analyze the peptide-MHC protein interaction interface, a single docking of HLA-DP2 (DPA*0103, DPB1*0201) in complex with a self-peptide derived from the HLA-DR α-chain (pdb code: 3lqz) was analyzed using Rosetta Dock [19]. Our analysis affords a  deep and detailed analysis of the different amino acid preferences at each position of peptides binding DP proteins.

Input data
The X-ray structure of the HLA-DP2 (DPA*0103, DPB1*0201) protein, in complex with a self-peptide derived from the HLA-DR α-chain, was used as the starting structure for homology modelling [10]. The covalently bound peptide was separated and defined as chain C. It consists of nine binding core positions (FHYLPFLPS) and six flanking residues (RK at the N terminus and TGGS at the C terminus). The conformation of the protein was used to model by homology the four HLA-DP proteins. The conformation of the bound peptide was used as a template for the modelling of four virtual combinatorial peptide libraries.

Homology modelling
Models of four HLA-DP proteins were built using the X-ray structure of HLA-DP2 protein (pdb code: 3lqz) as the template for homology modelling. HLA-DP proteins used were: DP1 (DPA1*0201/DPB1*0101), DP41 (DPA1*0103/ DPB1*0401), DP42 (DPA1*0103/DPB1*0402), and DP5 (DPA1*0201/DPB1*0501). The polymorphic amino acids among the first 80 amino acids from chain α (DPA1) and the first 90 amino acids from chain β (DPB1) were mutated accordingly. The resulting structure, in complex with the native peptide from the starting X-ray structure, was subjected to energy minimization by simulated annealing using the AMBER force field [20]. Each peptide-DP protein complex was used as a starting structure for generating the corresponding virtual peptide library.

Combinatorial peptide library
The nine positions forming the peptide binding core were examined. Four peptide libraries, each consisted of 172 peptides (19 amino acids × 9 positions + 1 original ligand), were built using PyMOL [21]. The SAAS (single amino acid substitution) approach was used to model the conformations of each altered side chains: after substitution, the peptide was minimized while keeping the MHC protein rigid. The protonation state of ionisable protein side chains was assigned to a standard ionisable state: neutral for His; positively charged for Arg and Lys; and negatively charged for Asp and Glu [22]. In the case of docking at pH 5, His was considered to be positively charged.

AutoDock protocol
A parallelized version of AutoDock 4.2 [23], employing an implementation of the Lamarckian genetic algorithm (GA), was used to model the peptide binding to HLA-DPs. All simulations were run on the IBM Blue Gene -P of the Bulgarian Supercomputing Centre. The input ligands for AutoDock 4.2 were prepared by using tools developed in-house using C# and .NET. The output data were mined by python scripts using the MGL Tools 1.5.4 package [24]. All retained poses considered in the study had an RMSD below 2.0 Å. To limit the computational burden of calculating peptide-MHC interactions at positions not involved in the static docking, all coordinates were kept fixed apart from the peptide residues of interest. These were left flexible. All GA settings were kept to their default values, apart from the number of energy evaluations and the number of generations which were set to 2 500 000 and 27 000, respectively.   Docking score-based quantitative matrices (DS-QMs) The FEBs derived from the docking experiments had negative and positive values. Negative FEBs correspond to binding peptides, while positive FEBs correspond to non-binding peptides. Only negative FEBs were considered; non-binding amino acids were assigned the penalty score of −10. The FEBs were normalized position per position using the following formula: Where FEB i is the binding energy of the i-th peptide, FEB is the average for a given position, FEB max and FEB min are the maximum and minimum FEBs for a given position. Normalized FEBs were multiplied by (−1) before being entered into the quantitative matrices (QMs) for ease of presentation. Thus, the positive FEBs correspond to preferred amino acids, and negative FEBs to non-preferred residues. Eight QMs were derived: two for each HLA-DP protein at pH 5.0 and pH 7.0, respectively.

Test set
Four test sets of peptides known to bind HLA-DP1, HLA-DP41, HLA-DP42, and HLA-DP5, respectively, were collected from the Immune Epitope Database [25] (June 2011 release). The test set of DP1 binders contained 102 peptides originating from 60 proteins. The DP41 test set contained 152 binding peptides from 71 proteins. The DP42 test set contained 122 binding peptides from 66 proteins. The DP5 test set contained 108 binding peptides from 66 proteins. The peptides had different lengths. No multiple binders were used. Each protein was represented as a set of overlapping nonamers. The nonameric subsequence of any known binder with the highest score was considered a binder; all other protein nonamers were considered as non-binders. The binding score of each nonamer was calculated as a sum of the weights of all nine positions or of different combinations thereof.
The tests were performed under conditions similar to those which an experimental immunologist might use: proteins were cleaved into overlapping nonamers, the binding score of each nonamer was predicted. Nonamers were then ranked according to their binding score and the top 5% of the predicted nonamers was selected. The selected peptides were then compared to the known binders. If the nonamer sequence was part of the known binder sequence, the predicted peptide was considered as a true predicted binder. The ratio of all true predicted binders to all binders in the corresponding test set defined the sensitivity of prediction at the top 5% cutoff. The test sets used in the present study are given as Additional file 1.  Additionally, the models were compared in terms of the area under the receiver operating characteristics curve (AUC). Two variables -sensitivity and 1-specificity -were calculated at different thresholds. AUC is a quantitative measure of predictive ability and varies from 0.5 for random prediction to 1.0 for a perfect prediction.

Rosetta Dock protocol
The Rosetta Dock server (http://rosettadock.graylab.jhu. edu) was used to generate the pair interaction energies across the peptide-DP2 protein binding interface. The X-ray structure of the peptide-HLA-DP2 (DPA*0103, DPB1*0201) complex (pdb code: 3lqz) was used as input. The RosettaDock output file contains a table of pair energies across the binding interface. Several energy terms are generated: E tot is the sum of all energies between the pair residues; E atr and E rep are the Lennard -Jones attractive and repulsive energies, respectively; E sol is the solvation energy according to the Lazaridis-Karplus solvation model [26], which penalizes buried polar groups; E hbnd is the hydrogen bonding energy per residue; E pair is a statistically-based pair term derived from the PDB database, which favours salt bridges.

Results
Pair energies across peptide -HLA-DP2 protein binding interface The peptide-DP protein binding interface was analysed using the RosettaDock server [19].
It consists of 39 residues: 21 residues belong to αchain (9, 11, 22, 24, 32, (Figure 1). Only five of the residues are polymorphic among the five most frequent DP proteins (Table 1). These are Tyr/Phe 9β , Ala/Asp/ Glu 55β , Lys/Glu 69β , Val/Met 76β and Asp/Gly 84β . Asp 55β is involved in a salt-bridge with peptide Ser9, while the other polymorphic residues do not form either an H-bond or a salt bridge with the bound peptide.

External validation
A test set comprising 484 peptides known to bind HLA-DP1, HLA-DP41, HLA-DP42 or HLA-DP5, originating from 263 proteins, was used for external validation of the derived DS-QMs. Initially, the sensitivity of the top 5% of the best scored peptides for each position was assessed using DS-QMs calculated at pH 7.0 and pH 5.0. Next, all possible combinations of different positions were evaluated. The most predictive models among all possible combinations between the nine peptide positions are shown in Table 2. It is evident that almost all positions are involved in these highly predictive models, indicating that no peptide positions have a negligible effect on binding. The results also indicate that the models derived at pH 5.0 seem to predict better than those derived at pH 7.0. Moreover, different peptide positions are important for binding at different pH values.

Comparison to existing servers for HLA-DP binding prediction
The best performing models derived here were compared to two state-of-the-art servers for MHC class II binding prediction: NetMHCII [27] and IEDB [28]. Both use sequence-based models powered by artificial neural networks (ANN). NetMHCII identifies nonamers, while IEDB works only with 15mers. The tests were performed as follows: protein sequences were converted into sets of overlapping peptides (9mers for NetMHCII and 15mers for IEDB), and the binding score of each peptide was predicted; peptides were ranked according to their binding score, and the top 5% of the ranked peptides were selected and compared to known binders. If the predicted peptide was included in the known binder sequence, it was considered a true predicted binder. The ratio of all true predicted binders to all binders in the corresponding test set defined the sensitivity of prediction at the top 5% cut-off. The sensitivities were recorded and compared to our best predicted models at pH 5.0 ( Figure 2a). Additionally, servers were compared in terms of AUC (Figure 2b). It is evident that our DS-QM models out-performed state-of-the-art servers for DP1, DP42 and DP5 proteins.

Effect of pH on peptide and protein His residues
As peptides typically bind to class II MHC proteins in an acidic environment, with a pH between 4.5 and 5.5, dockings were performed at pH 5.0 and pH 7.0, and compared in terms of their predictive ability. Better prediction was found for the DS-QMs derived at pH 5.0.  The only amino acid sensitive to pH in the range 5.0 to 7.0 is Histidine. The pK a of the His imidazole is 6.0, thus making His protonated and very hydrophilic at pH 5.0 and unprotonated and less hydrophilic at pH 7.0. The influence of pH on the affinity of peptide binding to HLA-DP proteins has two potential aspects: influence on peptide protonation/deprotonation and influence on protein binding site protonation/deprotonation. Figure 3 summarizes the normalized FEB values for protonated and nonprotonated His residues at each of the nine peptide binding core positions. It is clear that protonated His residues are preferred in most peptide positions (p3 to p9). As the peptide binding site on DP proteins is predominantly negatively charged [29], preference for positively charged His were expected. Five His residues are present in the HLA-DP binding site: four belong to the α-chain (positions 5, 16, 44 and 79) and one belongs to the β-chain (position 79). All are conserved among the studied DPs. Only His 79β contacts the binding peptide in the vicinity of peptide position 2; the other His residues are distant from the binding site. The protonation of His 79β allows an additional H-bond to be formed between the backbone carbonyl oxygen belonging to peptide position −1 (the position before p1) and the imidazole E-nitrogen of His 79β (Figure 4). The estimated N-H. . .O = C bond energy for polypeptides in water environment lies within the range: 1.5 -2 kcal/mol [30]. This means that the formation of this additional Hbond can increase the binding affinity constant of the peptide-protein complex by over an order of magnitude in the absence of other effects. This may explain the enhanced experimentally-observed equilibrium binding level seen at pH 5.0 [13].

Discussion
In the present study, molecular docking procedures developed recently for peptide binding prediction to HLA-DP2 protein [15] were significantly extended to include the four most frequent DP proteins [18]: DP1 (DPA1*0201/DPB1*0101), DP41 (DPA1*0103/ DPB1*0401), DP42 (DPA1*0103/DPB1*0402) and DP5 (DPA1*0201/ DPB1*0501). The X-ray structure of the peptide -HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. In turn, these were used to generate combinatorial peptide libraries built using the SAAS principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were recorded, normalized, and used to generate DS-QMs. The predictive ability of these QMs was tested using an external test set and compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0, showing significantly improved predictions for three of the four DP proteins, when compared to current state-of-the-art servers. DS-QMs can recognize 50% of the known binders in the top 5% of predicted peptides. Moreover, a single docking  of HLA-DP2 (DPA*0103, DPB1*0201) in complex with a self-peptide derived from the HLA-DR α-chain (pdb code: 3lqz) was analysed using RosettaDock. This characterised more fully the interacting amino acids across the peptide -MHC binding interface, helping identify amino acid preferences at each position of the peptide binding core. Peptide binding pocket 1 (p1) consists of 11 residues ( Table 3). Ten of them are conserved and only Asp/Gly 84β is dimorphic ( Figure 5). DP1 and DP5 contain Asp 84β , while DP41 and DP42 contain Gly 84β as does DP2. Aromatic amino acids such as Phe, Tyr, Trp and His, as well as aliphatic Ile and Leu are able to bind into this pocket. Additionally, the Asp 84βcontaining proteins DP1 and DP5 accept positively charged Lys, Arg and His (when is charged at pH 5.0). A hydrogen bond is formed between Ser 53α and NH of peptide position 1 (p1) ( Table 1).
The peptide position 2 (p2) makes contacts with 6 residues of the binding site (Table 4), 5 of them are conserved, one (Met/Val 76β ) is dimorphic ( Figure 6). Only DP1 contains Val 76β , the remaining DPs have Met 76β . The p2 side chain protrudes up the binding site close to the β chain and a variety of amino acids are well situated here. His at p2 makes H-bonds with Tyr 9α and Asn 80β , and salt bridges with His 79β and Asn 80β (Table 4). A π-π stacking of aromatic rings explains the preference of aromatic residues here [15]. Protonated His is not favored here.
The side chain of peptide position 3 (p3) protrudes up of the binding site close to α chain. It contacts 7 α-chain residues and 2 β-chain residues, one of which is the dimorphic Met/Val 76β (Table 5). Glu 55α makes a hydrogen bond with Tyr OH-group (Figure 7). The amino acid preferences here are quite uniform for the four DPs: Tyr,  Trp, Phe, Pro and the positively charged Arg. Met 76βcontaining DPs (DP41, DP42 and DP5) accept a protonated His here. Binding pocket 4 (p4) is large, shallow and negatively charged due to the presence there of Glu 26β , Glu 68β and Glu 69β [10]. It strongly attracts positively charged amino acids such as Arg, Lys and protonated His. Leu, Tyr, Trp and Phe are also well accepted here. Asn 62α and Gln 13β make H-bonds with Leu4 (Table 6 and Figure 8). Glu 68β and Glu 69β are not shown to make contacts to p4, as Leu does not fill the pocket [10]. Surprisingly, Glu, Gln and Asn also fit well into this pocket making H-bonds with Asn 62α and Gln 13β .
Position 5 (p5) protrudes from the binding cleft but it is still in close proximity to the negatively charged residues Glu 26β , Glu 68β and Glu 69β . This explains the observed preferences for the positively charged Arg, Lys and protonated His and the disinclination for Asp and Glu. Pro at p5 hydrogen bonds to Gln 13β and contacts Asn 62α , Ile 65α and Glu 26β (Table 7 and Figure 9). Phe and Trp are also well accepted at p5. No polymorphism exists here (Table 2).
Binding pocket 6 (p6) is deep and formed by 8 residues from the α-chain and 5 residues from the β-chain (Table 8 and Figure 10). Asn 62α makes an H-bond with the NH of Phe6. No polymorphism exists here (Table 2) and that makes the amino acid preferences at this pocket uniform for the five DPs. Phe, Tyr, Trp and His (protonated and nonprotonated) are well accepted here. Lys and Arg also fit well.
The side chain of position 7 (p7) lies tangentially to the binding site and is oriented towards the β-chain (Table 9). It is considered to be a secondary anchor position for some MHC class II proteins [31,32]. NH and CO of Leu7 make H-bonds with Tyr 28β and Asn 69α , respectively. The p7 side chain makes contacts with Ile 65α , Glu 26β , Phe 45β , Trp 59β , Ile 65β and Glu/Lys 69β Figure 11 Peptide position 7. The α chain residues are shown in light blue, the β chain residuesin darksalmon The dimorphic Glu/Lys 69β is shown in green. Asn 69α and Tyr 28β (given in magenta) make H-bonds with p7 residue Leu (given as LEU-9 in orange).

Figure 10
Peptide binding pocket 6. The α chain residues are shown in light blue, the β chain residuesin darksalmon.
No polymorphism exists here. Asn 62α (given in magenta) makes an H-bonds with p6 residue Phe (given as PHE-8 in orange).
( Figure 11). Aliphatic residues are well accepted here. Additionally, Asp is preferred by Lys 69β -containing DP proteins. Position 69β is dimorphic: DP1, DP41, DP42 and DP5 have Lys 69β , while DP2 has Glu 69β . Protonated His is accepted better here than the unprotonated form. Position 8 (p8) is solvent-exposed, yet shows preference for a variety of peptide residues: Trp, Tyr, Pro, Arg, Asn, Gly, Ala, His. Pro8 makes favourable contacts with Ile 65α and Trp 59β and disfavoured contacts with Asn 69α and Asp 55β (Table 10 and Figure 12). Position 55β is polymorphic: DP1 and DP41 contain Ala; DP2 and DP42 have Asp; and DP5 has Glu. However, this position is situated far from the side chain of p7 and does not influence the preferences there. Protonated His is preferred here.
Binding pocket 9 (p9) is formed from Asn 68α , Asn 69α , Leu 70α , Thr 72α , Leu 73α , Phe/Tyr 9β , Ala/Asp/Glu 55β and Trp 59β (Table 11 and Figure 13). It accepts large aromatic, polar, and even charged residues [10]. The side chain of p9 is oriented towards the α-chain. Ser9 is too short to fill the pocket. It makes H-bonds with Asn 69α and Thr 72α . Phe, Tyr, Trp, His fit well into this pocket. The Asp/Glu 55β -containing DPs accept Arg and protonated His.
The influence of pH on the affinity of peptides binding to HLA-DP has two main aspects: influence on peptide protonation/deprotonation and influence on protein binding site protonation/deprotonation. At pH 5.0, His is positively charged and it is preferred at peptide positions 3 to 9. Among the five His residues in the HLA-DP binding site, only the protonation state of His 79β affects peptide binding. At pH 5.0 an additional hydrogen bond is formed between the backbone carbonyl oxygen of the peptide position before p1 (p-1) and the imidazole E-nitrogen of His 79β (Figure 4). This H-bond increases the peptide binding affinity by more than 3 orders of magnitude, perhaps explaining the higher experimentally-observed equilibrium binding level seen at pH 5.0 [30]. The peptide-protein association rate constants greatly increases at pH 5.0 (~40fold), while the dissociation rates are almost unchanged in the pH range 5.0 -7.0 [13]. Thus, one may speculate that the peptide-protein complex formed in the acidic environment of endosomes will also be stable in the neutral environment of the cell surface.

Conclusion
For peptide binding to the four most frequent HLA-DP proteins (DP1, DP41, DP42 and DP5), statistically the DS-QMs derived through molecular docking simulations Figure 12 Peptide position 8. The α chain residues are shown inlight blue, the β chain residuesin darksalmon. The trimorphic Ala/Asp/Glu 55β is shown in green. No H-bonds are made with p8 residue Pro (given as PRO-10 in orange).  Polymorphic residues are given in bold.

Figure 13
Peptide binding pocket 9. The α chain residues are shown in light blue, the β chain residuesin darksalmon. The trimorphic Ala/Asp/Glu 55β is shown in green. Asn 69α and Thr 72α (given in magenta) make H-bonds with p9 residue Ser (given as SER-11 in orange).