Structure-based mutation analysis (PKU)
To all who are engaged in Psyche's task, of sorting out the seeds of good from the seeds of evil, i dedicate this discourse. FRASER
Contents
Short task description
This week, we will introduce mutations in the known tertiary structure of our protein and calculate and compare the potential energy of mutant and wildtype protein with different methods. See the complete task description for details. Our journal might be found here.
Finding the right structure
As proposed we searched the UNIProt entry for our protein and then selected the entry with the highest resolution and the lowest r-Value. In our case this is 1J8U which is the protein in a complex with its cosubstrate BH4. IN the following we will only use this structure, but we also list the results we found. <figtable id="tab:uniprotresult">
Entry | Method | Resolution (Å) | r-Value | Chain | Positions | PDBsum |
---|---|---|---|---|---|---|
1DMW | X-ray | 2.00 | 0.200 | A | 118-424 | [»] |
1J8T | X-ray | 1.70 | 0.197 | A | 103-427 | [»] |
1J8U | X-ray | 1.50 | 0.157 | A | 103-427 | [»] |
1KW0 | X-ray | 2.50 | 0.220 | A | 103-427 | [»] |
1LRM | X-ray | 2.10 | 0.211 | A | 103-427 | [»] |
1MMK | X-ray | 2.00 | 0.199 | A | 103-427 | [»] |
1MMT | X-ray | 2.00 | 0.213 | A | 103-427 | [»] |
1PAH | X-ray | 2.00 | 0.176 | A | 117-424 | [»] |
1TDW | X-ray | 2.10 | 0.206 | A | 117-424 | [»] |
1TG2 | X-ray | 2.20 | 0.213 | A | 117-424 | [»] |
2PAH | X-ray | 3.10 | 0.251 | A/B | 118-452 | [»] |
3PAH | X-ray | 2.00 | 0.175 | A | 117-424 | [»] |
4ANP | X-ray | 2.11 | 0.204 | A | 104-427 | [»] |
4PAH | X-ray | 2.00 | 0.169 | A | 117-424 | [»] |
5PAH | X-ray | 2.10 | 0.163 | A | 117-424 | [»] |
6PAH | X-ray | 2.15 | 0.171 | A | 117-424 | [»] |
</figtable> In <xr id="tab:uniprotresult"/> there are all results according to which we selected 1J8U to be our reference for this weeks task. The corresponding line is marked in yellow. Unfortunately, as we discovered in the preparation of SCWRL, the coverage in not from 103 to 427 for 18JU but only from 118 to 427.
1J8U
In order to know the structure of the protein and its important residues, we have a look at its structure with PyMol and visualize the BH4 and the Fe-ion with the most important residues.
<figure id="fig:structuremoving">
</figure>
Mutations
As you probably know from last weeks dataset the first two mutations are located before residue 103 and therefore not contained in the structure. We changed them to mutations, which we think are interesting from a structural view. We propose the following dataset, chosen mostly from well known SNPs from OMIM. They include mutations causing no reported effect, the mild related hyperphenylalaninemia (reduced activity, but functional enzyme) and phenylketonuria. We will present a similar table for each method, in which we show the results we would suggest from this method alone in the end we present our overall results here, which will be a intuitive consensus for all the intermediate results.
SNP | effect | prediction | validation | |
---|---|---|---|---|
ARG158GLN | disease causing | effect | ||
GLN172HIS | non-disease | no effect | ||
ARG243GLN | disease causing | effect | ||
LEU255SER | disease causing | effect | ||
MET276VAL | non-disease | effect | ||
ARG297CYS | disease causing | no effect | ||
ALA322GLY | hyperphenylalaninemia | no effect | ||
GLU330ASP | disease causing | effect | ||
GLY337VAL | disease causing | effect | ||
ARG408TRP | disease causing | effect |
ARG158GLN
<figure id="fig:ARG158GLNmutation">
</figure>This mutation, which is diseasecausing is in a moderate distance to the important binding sites (<xr id="fig:ARG158GLNmutation" />). A clear explanation, why this has an effect on the protein can not be found from the structure alone. But even with the results from last weeks Task, we just had to rely on the clashes which occurred when we estimated the structure.
GLN172HIS
<figure id="fig:ARG158GLNmutation">
</figure>In <xr id="fig:ARG158GLNmutation" /> one can see the big distance between the binding sites and the mutation location. Since we know that this is harmless, one would tend to say, that its clear, due to the distance, but as we know, that we also have mutations in a big distance which cause the disease, we are bound to say we do not know the mechanism.
ARG243GLN
<figure id="fig:ARG243GLNmutation">
</figure>This is the second mutation of this kind, which means a change from arginine to glycine. As the other mutation, this one is disease causing. But in difference to the other case, this one is rather close to the binding areas (see <xr id="fig:ARG243GLNmutation" /> )
LEU255SER
<figure id="fig:LEU255SERmutation">
</figure>When one compares this mutation ( in <xr id="fig:LEU255SERmutation" />) to the reference structure in <xr id="fig:structuremoving" /> one can see, that one of the yellow residues (BH4 binding site) is mutated. And as one would expect this mutation is harmful.
MET276VAL
<figure id="fig:MET276VALmutation">
</figure>As the mutation shown in <xr id="fig:MET276VALmutation" /> is rather far from any important binding site, one would expect it to be of little effect for the protein, which is the case for this mutation.
ARG297CYS
<figure id="fig:ARG297CYSmutation">
</figure>As the last mutation, this one is located quite far from any annotated sites ( <xr id="fig:ARG297CYSmutation" />), however it is located in the kink of two helices, and therefore the expectation which this mutation might have on the protein tends towards disease causing, which is actually the right choice.
ALA322GLY
<figure id="fig:ALA322GLYmutation">
</figure> The mutation, which affects one of the amino acids responsible for the BH4-binding, is shown in <xr id="fig:ALA322GLYmutation" /> and as one would guess is disease causing.
GLU330ASP
<figure id="fig:GLU330ASPmutation">
</figure>As the last mutation in <xr id="fig:ALA322GLYmutation" /> this mutation affects a binding site (this time iron) and is disease causing.
GLY337VAL
<figure id="fig:GLY337VALmutation">
</figure>This mutation (shown in <xr id="fig:GLY337VALmutation" />) is far from any known binding site and located in a loop on the far outside of the protein, but it is disease causing.
ARG408TRP
<figure id="fig:ARG408TRPmutation">
</figure>In <xr id="fig:ARG408TRPmutation" /> one can again see a mutation which is pretty far from the annotated sites, but still is disease causing.
SCWRL
preparations
We use the repairPDB script to extract the sequence from our model file. Afterwards we do some bashing to get the sequence in small letters but for the mutation, which has to be in capitals. <source lang="bash"> $ repairPDB 1J8U.pdb -seq > 1J8U.seq $ tr '[:upper:]' '[:lower:]' < 1J8U.seq > lower18JU.seq $ sed 's/^\(.\{<pos-118>\}\)<original in small letter>\(.*\)/\1<target in capital letter>\2/' lower18JU.seq > lower18JUmut<pos>.seq </source>
usage
Afterwards, we used a little bashscript which just applies all SCWRL-calls after another. In the following you see one example: <source lang="bash"> $ /opt/SS12-Practical/scwrl4/Scwrl4 -i ../1J8U.pdb -s lower18JUmut158.seq -o mut158.pdb > mut158.log </source>
results
The following pictures show the structure optimized by SCWRL. The mutant is colored in red for this residue as the wildtype is colored in green, as the structure apart from this residue is unchanged, the color is chosen automatically by PyMol. Polar bonds are colored respectively to mutant and wildtype, but note, that there might be overlaps, where only one color is shown.
<figtable id="tab:scwrlenergies">
Mutation | energy | energy mut/energy wt | prediction |
---|---|---|---|
wildtype | 164.21 | 1 | no effect |
ARG158GLN | 172.845 | 1.05 | effect |
GLN172HIS | 169.699 | 1.03 | no effect |
ARG243GLN | 152.987 | 0.93 | effect |
LEU255SER | 166.123 | 1.01 | effect |
MET276VAL | 164.472 | 1.00 | effect |
ARG297CYS | 166.646 | 1.01 | no effect |
ALA322GLY | 164.285 | 1.00 | no effect |
GLU330ASP | 171.68 | 1.04 | effect |
GLY337VAL | 164.304 | 1.00 | no effect |
ARG408TRP | 393.804 | 2.39 | effect |
</figtable>
foldX
The other approach we used is foldX
preparation
We use the run.txt from the example at the test and adapt the list and individual list as its shown in the journal.
usage
<source lang="bash">
scwrl -runfile run.txt
</source>
results
As we already have results from the SCWRL run, we just compare those with the new results from foldX. The comparison with the sourounding structures is left for the reader as an exercise. The residue placed by SCWRL is colored in blue whereas the foldX residue is orange. THe surrounding structure is colored randomly by PyMol. <figure id="foldxstructcompare">
</figure>
Mutation ARG158GLN: In this picture the changes between foldX and SCWRL are not big. The stuctural differences of the two residues result in the fact, that SCWRl includes H-atoms which are not included in foldX. Apart from that, the residues are twisted which results in a difference of the H-bonds. As one can see, SCWRL forms a bond (colored in blue) which is not present in the residue conformation in foldX.
<figtable id="tab:foldxenergies">
Mutation | energy | energy mut/energy wt | energy mut/energy relative wt | prediction |
---|---|---|---|---|
wildtype | 14.00 | 1 | 1 | no effect |
ARG158GLN | 6.36 | 0.45 | 1.31 | effect |
GLN172HIS | 16.69 | 1.16 | 0.99 | no effect |
ARG243GLN | 6.15 | 0.43 | 0.72 | effect |
LEU255SER | 23.57 | 1.68 | 1.21 | effect |
MET276VAL | 21.99 | 1.57 | 1.06 | effect |
ARG297CYS | 20.31 | 1.45 | 1.01 | no effect |
ALA322GLY | 21.76 | 1.55 | 1.05 | no effect |
GLU330ASP | 19.65 | 1.40 | 1.02 | effect |
GLY337VAL | 24.01 | 1.71 | 1.10 | effect |
ARG408TRP | 34.36 | 2.45 | 1.58 | effect |
</figtable>
minimise
preparation
To use minimise we have to clear the structure of hydrogen atoms and solvent which we do again using the repairPDB script. <source lang="bash"> $ repairPDB 1J8U.pdb -noh -nosol > 1J8U_pure.pdb </source>
usage
Afterwards a little script is used to apply the minimization five times and each time using the output as input.
- usage:
<source lang="bash"> $ runAllMinimiser.sh <filestem> </source>
results
Just to see the differences between the results of one run and several using the output again as input, we produce this little animated .gif, which is basicly all the results from the 18JU.pdb on till the fifth minimise result. <figure id="fig:helixminimise">
</figure> In <xr id="fig:helixminimise" /> one can see that minimise shifts the start of the helix further down in the picture, and once it reaches a certain point, the start of the helix is converted to a coiled region instead. A similar effect can be found if one compares sheets in the output of the different minimise runs. Here a twisting of the sheets takes place, which can bee seen in <xr id="fig:sheetminimise" /> <figure id="fig:sheetminimise">
</figure> <figure id="fig:timecourseminimise">
</figure> As one can see in <xr id="fig:timecourseminimise" /> consecutive multiple minimise runs do not decrease the energy but increase it drastically. But the first two minimise steps reduce the energy, and therefore we want to compare the energyoutput from minimise to the two others found in <xr id="tab:foldxenergies" /> and <xr id="tab:scwrlenergies" />. <figtable id="tab:minimiseenergies">
mutation | energy foldX | energy foldX/energy wt | energy scwwrl | energy scwrl/energy wt | prediction |
---|---|---|---|---|---|
wildtype | -7516.267118 | no effect | |||
ARG158GLN | -7564.267932 | 1.00 | -7400.825142 | 0.98 | |
GLN172HIS | -7513.718344 | 0.99 | -7375.087666 | 0.98 | |
ARG243GLN | -7522.768865 | 1.00 | -7476.255952 | 0.99 | |
LEU255SER | -7522.768865 | 1.00 | -7476.255952 | 0.99 | |
MET276VAL | -7502.369873 | 0.99 | -7374.091542 | 0.98 | |
ARG297CYS | -7616.286033 | 1.01 | -7484.442763 | 0.99 | |
ALA322GLY | -7509.307761 | 0.99 | -7389.927555 | 0.98 | |
GLU330ASP | -7494.936652 | 0.99 | -7367.788205 | 0.98 | |
GLY337VAL | -7504.533976 | 0.99 | -7380.216180 | 0.98 | |
ARG408TRP | -5289.743707 | 0.70 | -5438.301688 | 0.72 | effect |
</figtable> TODO: this and maybe compare with the other weird energy outputs from SCWRL and foldX und dann halt irgendwie daraus die prediction für die einzelnen Mutationen ableiten
surface considerations
As we only can get very little information from the minimise-results, we try to include the overall surface of the protein as well as the important sites into the prediction of the effectivity. In the following, mutants are colored red and wildtype residues green. The wildtype surface is shown in green and grey (for non mutant areas). In contrast the mutant surface will be shown as a mesh and in red color.
Mutation ARG243GLN: In this picture we see the big differences which come with the change of the amino acids. As the normal surface is kind of a small tunnel on the upper left, with the change to glutamine this tunnel would widen (see red mesh) and a new hole on the right would appear, which is not present in the green surface (wildtype)
<figtable id="tab:scwrlenergies">
Mutation | surface changes | bindingsite | prediction |
---|---|---|---|
ARG158GLN | mild to big | no | effect |
GLN172HIS | mild | no | no effect |
ARG243GLN | big | no | effect |
LEU255SER | mild | yes | effect |
MET276VAL | big | no | no effect |
ARG297CYS | big | no | effect |
ALA322GLY | mild | yes | effect |
GLU330ASP | mild | yes | effect |
GLY337VAL | big | no | effect |
ARG408TRP | huge | no | effect |
</figtable>
Gromacs
We choose the scwrl structures as input, since there is little difference to observe so far, but scwrl will be used in next week's task and results will be more comparable that way. The provided fetchPDB-script just wgets the gzipped PDBfile for a given PDB identifier, but was not used, since we already had our input structures. To extract the protein alone from the PDB-file, we used repairPDB with the -jprot option. repairPDB provides a number of usefull options, e.g. it extracts or removes DNA, crystal water, selects individual chains or renumbers the sequence.
The minimization preparation and runs were performed with this script. There is also a short script to run g_energy from the .edr-files here. We initially choose the forcefields TIP3P for water, AMBER03 (option 1 in the interactive menu), CHARMM27 (option 8) and GROMOS96 53a6 (option 13) for the protein, since they are amongst the most popular, but run into troubles with GROMOS and replaced it with OPLS-AA (option 14). All of them work with our chosen water model TIP3P. We used the provided standard configuration file for gromacs, described elsewhere.
Results
Runtime
For most mutants and most forcefields the minimization converges between step 250 and 300 and calculation stops then, so there is little sense in starting with a value of more then say 1000 for nsteps. If the energy does not converge by then, we'd suspect some error in the input. We give a few runtimes for the wildtype and the AMBER03 forcefield in <xr id="fig:runtime"/>, performed on the lrz grid. The maximum runtime we observed was around 50 seconds (not shown), the average runtime for a minimization is around 30 seconds. Since the calculation of every step requires the same amount of work, the expected runtime behaviour until convergence is perfectly linear in nsteps plus a constant for initialization. The provided datapoints confirm this nicely. <figure id="fig:runtime">
</figure>
Energies
We show the curve of the angle, bond and potential energy during the wildtype minimization for all three forcefields in <xr id="fig:1J8U_energies"/>. In all cases, the energy goes down steeply at first. While the bond energy does not change much after that and potential energy slowly converges, the angle energy rises during optimization until it also converges at a level slightly higher than its initial lowest point. This is as expected, since the total energy is optimized by adjusting the conformation of the protein. The mutants behave qualitatively similar, plots will be available here, once they are uploaded.
The tables <xr id="tab:gromacs_energies_1J8U"/> to <xr id="tab:gromacs_energies_mut408"/> show the energies of angle, bond and the potential energy of the wildtype and the ten mutants. In brackets, the difference to the wildtype is given. The bond energy comprises a small part of the total energy and changes not much in the mutants (the largest change in ARG158GLN is 2.6%). Neither direction nor amplitude of the energy changes seem to correlate with malignance of the mutations directly.
For the AMBER force field the average change in potential energy for the mutants is +304 kJ/mol, the average change in benign or hyperphenylalanemia causing mutations is only +139 kJ/mol. On the other hand, the smallest change in energy is observed in a disease causing, the GLY337VAL mutation. All but one disease causing mutation increase the potential energy, but two of the three benign ones do the same.
So far, we observe that smaller changes in energy indicate a less severe impact on the structure, but the prediction value appears limited, since the false positives number (benign mutations thought to be malign) is high. Setting a cut-off of the potential energy change to 100 kJ/mol would correctly classify five disease causing mutations above and two benign mutations below this threshold, giving an accuracy of 70%.
For the CHARMM force field the average change in potential energy for the mutants is +712 kJ/mol, the average change in benign or hyperphenylalanemia causing mutations is only +101 kJ/mol. The largest change in a benign mutation is only +160.53 kJ/mol and there are four extreme changes above 900 kJ/mol in the malign mutations. Setting a cut-off of the potential energy change to 100 kJ/mol would correctly classify six disease causing mutations above and two benign mutations below this threshold, giving an accuracy of 80%.
For the OPLS-AA force field the average change in potential energy for the mutants is +151 kJ/mol, the average change in benign or hyperphenylalanemia causing mutations is only +57 kJ/mol. The largest change in a benign mutation is +147.33 kJ/mol and there are three larger changes above 100 kJ/mol in the malign mutations, but also one change of +147 kJ/mol in an benign mutation. Setting a cut-off of the potential energy change to 50 kJ/mol would correctly classify five disease causing mutations above and two benign mutations below this threshold, giving an accuracy of 70%.
In all force fields, the largest change is caused by the malign ARG408TRP mutation, a visibly extreme disruption of the structure. Rather surprising is the large change in the benign GLN172HIS, that is located in a coiled region at the outside of PheOh and was one of the easier cases in last week's prediction task.
<figtable id="fig:1J8U_energies"> Course of the energies during minimization of 1J8U with gromacs.
</figtable>
<figtable id="tab:gromacs_energies_1J8U"> Energies after Gromacs minimization of the wildtype.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2403.47 (Δ 0.00) | 2092.75 (Δ 0.00) | |
Bonds (kJ/mol) | 522.31 (Δ 0.00) | 1162.70(Δ 0.00) | 545.17 (Δ 0.00) |
Potential (kJ/mol) | -37536.96 (Δ 0.00) | -40392.46(Δ 0.00) | -65323.58 (Δ 0.00) |
</figtable>
<figtable id="tab:gromacs_energies_mut158">
Energies after Gromacs minimization of the disease causing ARG158GLN mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2387.31 (Δ -16.17) | 2087.86 (Δ -4.90) | |
Bonds (kJ/mol) | 509.25 (Δ -13.06) | 1138.40(Δ -24.30) | 543.58 (Δ -1.59) |
Potential (kJ/mol) | -37171.73 (Δ 365.23) | -39342.72(Δ 1049.75) | -65223.57 (Δ 100.01) |
</figtable>
<figtable id="tab:gromacs_energies_mut172">
Energies after Gromacs minimization of the benign GLN172HIS mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2479.53 (Δ 76.06) | 2106.61 (Δ 13.86) | |
Bonds (kJ/mol) | 522.68 (Δ 0.37) | 1154.75(Δ -7.95) | 546.84 (Δ 1.67) |
Potential (kJ/mol) | -37163.15 (Δ 373.82) | -40231.94(Δ 160.53) | -65176.25 (Δ 147.33) |
</figtable>
<figtable id="tab:gromacs_energies_mut243">
Energies after Gromacs minimization of the disease causing ARG243GLN mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2398.46 (Δ -5.01) | 2086.91 (Δ -5.84) | |
Bonds (kJ/mol) | 517.89 (Δ -4.43) | 1144.20(Δ -18.50) | 542.42 (Δ -2.76) |
Potential (kJ/mol) | -37333.11 (Δ 203.86) | -39440.42(Δ 952.05) | -65231.15 (Δ 92.43) |
</figtable>
<figtable id="tab:gromacs_energies_mut255">
Energies after Gromacs minimization of the disease causing LEU255SER mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2415.15 (Δ 11.68) | 2092.62 (Δ -0.13) | |
Bonds (kJ/mol) | 530.22 (Δ 7.91) | 1150.95(Δ -11.75) | 546.59 (Δ 1.41) |
Potential (kJ/mol) | -37613.71 (Δ -76.75) | -40227.79(Δ 164.67) | -65323.13 (Δ 0.45) |
</figtable>
<figtable id="tab:gromacs_energies_mut276">
Energies after Gromacs minimization of the benign MET276VAL mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2402.78 (Δ -0.70) | 2094.12 (Δ 1.37) | |
Bonds (kJ/mol) | 522.62 (Δ 0.31) | 1153.45(Δ -9.25) | 548.90 (Δ 3.72) |
Potential (kJ/mol) | -37460.79 (Δ 76.18) | -40308.56(Δ 83.90) | -65297.64 (Δ 25.95) |
</figtable>
<figtable id="tab:gromacs_energies_mut297">
Energies after Gromacs minimization of the disease causing ARG297CYS mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2404.12 (Δ 0.65) | 2088.02 (Δ -4.73) | |
Bonds (kJ/mol) | 521.46 (Δ -0.86) | 1140.64(Δ -22.06) | 547.49 (Δ 2.32) |
Potential (kJ/mol) | -36943.84 (Δ 593.13) | -39121.65(Δ 1270.81) | -65074.67 (Δ 248.91) |
</figtable>
<figtable id="tab:gromacs_energies_mut322">
Energies after Gromacs minimization of the hyperphenylalaninemia causing ALA322GLY mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2409.61 (Δ 6.13) | 2091.98 (Δ -0.77) | |
Bonds (kJ/mol) | 528.05 (Δ 5.74) | 1147.60(Δ -15.10) | 547.21 (Δ 2.03) |
Potential (kJ/mol) | -37567.33 (Δ -30.36) | -40334.32(Δ 58.14) | -65325.79 (Δ -2.21) |
</figtable>
<figtable id="tab:gromacs_energies_mut330">
Energies after Gromacs minimization of the disease causing GLU330ASP mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2408.24 (Δ 4.77) | 2097.44 (Δ 4.69) | |
Bonds (kJ/mol) | 522.71 (Δ 0.39) | 1162.17(Δ -0.53) | 544.42 (Δ -0.75) |
Potential (kJ/mol) | -37373.77 (Δ 163.19) | -40487.35(Δ -94.89) | -65280.02 (Δ 43.57) |
</figtable>
<figtable id="tab:gromacs_energies_mut337">
Energies after Gromacs minimization of the disease causing GLY337VAL mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2415.06 (Δ 11.58) | 2105.72 (Δ 12.97) | |
Bonds (kJ/mol) | 526.54 (Δ 4.23) | 1156.77(Δ -5.93) | 548.96 (Δ 3.79) |
Potential (kJ/mol) | -37518.37 (Δ 18.60) | -40272.05(Δ 120.41) | -65273.33 (Δ 50.25) |
</figtable>
<figtable id="tab:gromacs_energies_mut408">
Energies after Gromacs minimization of the disease causing ARG408TRP mutation.
Type | Amber03 | Charmm27 | Oplsaa |
---|---|---|---|
Angle (kJ/mol) | 2430.32 (Δ 26.85) | 2110.42 (Δ 17.67) | |
Bonds (kJ/mol) | 524.16 (Δ 1.84) | 1150.43(Δ -12.26) | 546.33 (Δ 1.15) |
Potential (kJ/mol) | -36674.55 (Δ 862.41) | -38873.69(Δ 1518.78) | -64802.38 (Δ 521.21) |
</figtable>