Structure-based mutation analysis GLA

^{by Benjamin Drexler and Fabian Grandke}

Introduction

In this task we analyse the structure of our protein to find out what effects the point mutations have. Therefor we created mutated structures and compared them to the wild-type protein. Several tools based on different methods have been used to achieve that aim. We used the mutations that we have chosen in the previous task.

Methods

In the first step of this task we had to find available protein structures for our Protein and to decide which one would be the best for our detailed analysis. We set several cut-offs to exclude improper structures.

SCWRL

SCWRL was initially developed by Dunbrack et al. in 1997. We use SCWRL4<ref name=dunb>G. G. Krivov, M. V. Shapovalov, and R. L. Dunbrack, Jr. Improved prediction of protein side-chain conformations with SCWRL4. Proteins (2009)</ref> which was published in 2009. The program takes a PDB file and a sequence file as input. By usage of a rotamer library, collision detection, and a residue interaction graph the optimal side-chain conformation is calculated, based on the backbone and the mutated sequence given in the input files. The output is a PDB file containing the conformation and the total minimal energy of the graph in STDOUT.

FoldX

FoldX was developed by Serrano et al. in 2002<ref name=serr>Guerois R, Nielsen JE, Serrano L., Predicting Changes in the Stability of Proteins and Protein Complexes: A Study of More Than 1000 Mutation. Journal of Molecular Biology (2002)</ref>. We used version FoldX 3.0 beta 4. The program provides the calculation of determination of energy effects of point mutations. It provides different run modes, but basically it takes a PDB file as input calculates several single energies(e.g. Van der Waals, Electrostatics, ...) and returns the single energies together with the total energy as output.

Minimise

Before this tool from the virtual box was used we had to remove the hydrogens and waters from the PDB file with the script repairPDB. Afterwards we were able to compare the energies differences between the wildtype and the mutated protein.

Results

Structure Selection

There are several structure files available for our protein:

PDB ID	Resolution [Å]	ph-Value	R-Factor	Coverage [%]	Missing Residues
1R46	3.25	8.0	0.262	99.7	422-429
1R47	3.45	8.0	0.285	99.5	422-429
3GXN	3.01	NULL	0.239	88.08	422-429
3GXP	2.20	NULL	0.204	81.9	422-429
3GXT	2.70	NULL	0.245	97.29	422-429
3HG2	2.30	4.6	0.178	97.32	422-429
3HG3	1.90	6.5	0.167	98.64	427-435
3HG4	2.30	4.6	0.166	99.86	422-429
3HG5	2.30	4.6	0.192	100	422-429
3LX9	2.04	6.5	0.178	98.92	423-435
3LXA	3.04	6.5	0.216	99.52	427-435
3LXB	2.85	6.5	0.227	99.3	427-435
3LXC	2.35	6.5	0.186	98.31	423-435

We set two cutoffs to decide which structures are excluded:

• ph-value: < 6.5
• resolution: > 2.7

After we applied the cutoffs to our set of structures three were left (exclusion factors are colored red in the table). One of them was slightly better than the other ones so we decided to use 3HG3 (worse values are colored gray in the table). Additionally 3GH3 has the best overall resolution and R-factor (colored green). As the missing residues are very similar for all structures they are not further taken into account.

Energy Comparison

Number	AA-Position	Codon change	Amino acid change	SCWRL4	FoldX	FoldX - Diff	Minimise	Minimise - Diff
WT				-	-20.93	-	-20481.23	-
1	42	ATG-ACG	Met -> Thr	343.25	157.29	-178.22	-20324.41	-156.82
2	65	AGT-ACG	Ser -> Thr	327.798	152.87	-173.8	-20339.34	-141.89
3	117	ATT-AGT	Ile -> Ser	333.027	157.97	-178.9	-20353.47	-127.76
4	143	cGCA-ACA	Ala -> Thr	333.944	154.40	-175.33	-20339.32	-141.91
5	186	CAC-CGC	His -> Arg	323.717	154.57	-175.5	-20321.32	-159.91
6	205	gCCT-ACT	Pro -> Thr	340.619	155.96	-176.89	-20345.87	-135.36
7	244	gGAC-CAC	Asp -> His	333.594	152.08	-173.01	-20393.12	-88.11
8	283	CAG-CCG	Gln -> Pro	332.631	159.91	-180.84	-8027.71	-12453.52
8.2	-	-	-	-	-	-	-19134.48	-1346,95
9	321	tCAG-TAG	Gln -> Glu	332.853	160.95	-181.88	-20246.98	-234.25
10	363	TATa-TAA	Arg -> Cys	330.56	150.50	-171.43	-20295.77	-185.46

Gromacs

Figure 11: nstep vs. Elapsed Time in Gromacs.

Wildtype

Force Field	Average	Error Estimat	RMSD	Tot-Drift (kJ/mol)
Bond
AMBERGS	1826.99	420	4409.39	-2499.37
AMBER03	1639.74	410	4358.68	-2424.42
CHARMM27	2908.14	350	4779.8	-2033.44
Angle
AMBERGS	5496.47	74	476.18	408.548
AMBER03	5324.13	72	469.75	369.24
CHARMM27	7975.2	86	798.12	432.901
Potential
AMBERGS	-114713	1200	5648.79	-7915.46
AMBER03	-91307.7	1200	5559.82	-7839.05
CHARMM27	136.699	32	64.3892	227.896

Mutations

Force Field	Average	Error Estimat	RMSD	Tot/Drift
Bond
1	1815.39	570	5166.85	-3384.48
2	1862.77	610	5331.85	-3618.04
3	1773.13	520	4937.34	-3068.93
4	1828.63	580	5229.18	-3479.09
5	1870.95	610	5361.67	-3713.22
6	1816.6	550	5091.81	-3303.34
7	1819.7	570	5173.34	-3397.07
8	2992.15	1700	-nan	-10631.8
9	2083.16	830	-nan	-4913.82
10	1867.42	620	5390.82	-3693.03
Angle
1	5183.95	85	360.959	550.303
2	5195.33	80	364.473	515.645
3	5196.5	89	353.256	586.473
4	5175.59	85	364.496	547.465
5	5113.99	81	365.511	526.244
6	5200.44	85	356.964	553.934
7	5261.77	87	365.202	565.196
8	5178.73	76	-nan	215.036
9	5201.95	76	-nan	442.141
10	5174.48	88	375.775	555.294
Potential
1	-90528.4	1600	7234.09	-10149.1
2	-90481.9	1600	7442.03	-10340
3	-90654	1500	6928.73	-9614.54
4	-90541	1600	7311.04	-10343.7
5	-91011.7	1600	7484.45	-10592.5
6	-90782.2	1600	7226.99	-10188.5
7	-90232.9	1600	7236.24	-10198
8	-87316	3600	-nan	-23670.3
9	-90090.3	1900	-nan	-12335.3
10	-89721.8	1700	7523.88	-10750.1

References

<references />