Team:NYMU-Taipei/modelling-protein-structure-champ-design

MPFHLAPYLAKSVPGVGVLGALVGGAAALAKNVRLLKEKRITNTEAAIDTGKETVGAGLATALSAVAATAVGGGLVVSLGTALVAGVAAKYAWDRGVDLVEKELNRGKAANGASDEDILRDELA.

Fig. 5: The critical G-X3-G motifs on helix1 of the Mms13

Section 2. Selection of a nativelike helical-pair backbone within the chosen structural motif

After the selection of a helical-pair structural motif, we have to select a native-like helical-pair backbone as the templates for our CHAMP design. First, we follow the instructions to determine the template cluster. (R. F. S. Walters, et al., 2006) A library of 445 helical pairs from 31 proteins in the paper was clustered into groups based on their three-dimensional similarity. Different clusters have specific features and also show varying degrees of homogeneity. We finally choose cluster 2 as our candidates because of the antiparallel helices on Mms13 and the traits which belong to right-handed crossing angle on helix1. (For examples, the helix1 have small residues at the helix–helix interface, and they are also spaced at four-residue intervals.) The pie chart (See Figure 6) shows the fraction of the total number of pairs that fall within a given cluster and Table 1 (See Figure 7) shows some characteristics of the top 14 clusters.

After determining the cluster, we still have to choose one final template from within the 71 candidates of cluster 2. We first eliminated the number of candidates to 27 templates through the prediction of van der Waals minimum distance of the helical pairs based on the uniformity of packing assessed by finding structures with the minimal number of inter-atomic contacts that are closer than 1.0 Å from the expected van der Waals minimum distance. (Hang Yin, et al., 2007)

Then to get the most matched template of our CHAMP design, we used the online program-TMhit (Lo A., et al., 2009) inferring helix-helix interactions from residue contact in Mms13. We selected the best template pairs by finding the template having one helix with the most residue contacts with Mms13 and whose sequence of another helix has the most residue alignments with Mms13. After comparison, we chose protein 1iwg: A437-A450 and A932-A945 as the template pairs for our CHAMP design. Part of the data for the comparison is shown in Figure 8).

Fig. 7: Table1 with some characteristics of the clusters (R. F. S. Walters, et al., 2006)

Fig. 6: The pie chart with the fraction of a given cluster (R. F. S. Walters, et al., 2006)

Fig. 8

Section 3. Threading the sequence of the targeted TM helix onto the selected pair

By using the online program-ProtMod-Protein Structure Modeling-Alignment (Godzik A., et al., 2011), we got the pdb file of the repacking structure, where Mms13 is aligned onto the helix of the chosen template-1iwg: A437-A450.

Fig. 10a: The whole 1iwg protein. Figure 10b: The selected template pairs of 1iwg. Figures are graphed using YASARA View (Krieger E., et al., 2011)

Fig. 9: The aligned Mms13 structure from ProtMod (Godzik A., et al., 2011) graphed using YASARA View (Krieger E., et al., 2011).

After having both materials: the aligned Mms13 and the selected template pairs (1iwg: A437-A450; A932-A945), we threaded the Mms13 aligned sequence onto the corresponding helix. The threading process was finished by matching G-X3-G motif of Mms13 to the motif on the template structure. The backbones of the complex were then minimized to remove clashes with the threaded Mms13 sequence (See Figure 11).

Fig. 12: The minimal inter-helical distances predicted by YASARA View (Krieger E., et al., 2011)

Fig. 11

Section 4. Selection of the amino acid on CHAMP design with a side chain repacking algorithm

We gave a second stage repacking of the minimized structure and selected the one that showed a uniformly packed interior. We first found the proximal positions between Mms13 and the CHAMP template since the effect of the peripheral sequences are less dominant in the helical interaction. We used YASARA View (Krieger E., et al., 2011) to calculate the minimal inter-helical distances, VMD (Klaus Schulten., et al., 2011) to show the hydrophobic regions, and both to specify the proximal positions between helical pairs. The results are shown in Figures 12 and 13.

Fig. 13: The hydrophobic regions shown by VMD (Klaus Schulten., et al., 2011) indicate the peripheral regions since the membrane lipid bilayer is also non hydrophilic.

On CHAMP anti-mms13 helix, seven proximal positions were selected for secondary repacking based on their proximity to the mms13-threaded helix. We used the YASARA Energy Minimization Server (Krieger E., et al., 2009) and the ΔG prediction server v1.0 (Hessa, T., et al., 2007) to choose the residue sequences of proximal residues. We calculated the potentials following the potential energy functions (Hang Yin, et al., 2007) shown in Figure 14.

Fig. 14: The Summations of the energy potential equation. (Hang Yin, et al., 2007)

YASARA Energy Minimization Server (Krieger E., et al., 2009) is performed to calculate the EvdW + EHbond + Eelectrostatic + Econtact . Though the program is based on predicting the potentials in the water, we can still rank the prefer residues by using the result scores as support for our decision. The other program, ΔG prediction server v1.0 (Hessa, T., et al., 2007), in the other hand, we use it for computing the Esolvation + Eself potentials. The results of ΔG prediction server v1.0 (Hessa, T., et al., 2007) were ranked as well. By the cross-program comparison, we decided which residue is best for the corresponding proximal position.

For each step of the energy calculation process, the identity of one of the proximal positions on the CHAMP helix was mutated. (Hang Yin, et al., 2007) By using the exhaustive enumeration and the cross-program ranking strategy, we determined whether the mutation is either accepted or rejected and set the best candidate residue for the corresponding proximal position. Only the rotamers with high probabilities of occurrence within helical backbones are considered. The data for energy calculation is showed in Figure 15 and 16.

Fig. 15: One example result of YASARA Energy Minimization Server (Krieger E., et al., 2009)

Fig. 16: One example result of ΔG prediction server v1.0 (Hessa, T., et al., 2007)

Fig. 17: The second amino acid chosen by cross-ranking results.

Fig. 18: The third amino acid chosen by cross-ranking results.

Fig. 19: The sixth amino acid chosen by cross-ranking results.

Fig. 20: The seventh amino acid chosen by cross-ranking results.

Fig. 21: The tenth amino acid chosen by cross-ranking results.

Fig. 22: The eleventh amino acid chosen by cross-ranking results.

In the paper, when the identities of the proximal positions were determined, the membrane-exposed residues could then be fixed. The membrane-exposed positions are determined by random assignment of hydrophobic residues, with 60% probability given to Leu and 10% to Ala, Ile, Phe, and Val. (Hang Yin, et al., 2007) Though it could be done by random selection, we still use ΔG prediction server v1.0 (Hessa, T., et al., 2007) computing the energy to choose the CHAMP design with least energy.

Fig. 23: Results for choosing membrane-exposed positions.

The main targeting sequences of the CHAMP peptide was finally set, the last step was adding the solubilizing groups at the N- and C-termini to insert the CHAMP into the lipid membrane. We added both Lys residues to the termini of our CHAMP design. (Lys or polyethylene glycol-containing amino acids are used in the paper since the amino acids with positive charge can be driven by the negative charge of the lipid bilayer) (Hang Yin, et al., 2007). Our CHAMP design was then completed.

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