Analyzing Protein Stability: Mutation Effects on ΔΔG Values
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Australian National University**We aren't endorsed by this school
Course
CHEM 2208
Subject
Chemistry
Date
Dec 11, 2024
Pages
4
Uploaded by ProfessorRabbitPerson1262
Chem2208 Lab Report 7 Part 1.Q1Table in appendixQ2The results indicate that residues 47 and 601, that both lie on either end of the protein, are generally more tolerant to mutations, with the majority of changes being stabilizing, and even the destabilizing mutations at these sites being relatively mild, with no strongly negative values (negative corresponding to destabilisation and positive stabilisation in cupsat). At the more central residues (200, 402, and 533), mutations are predominantly destabilising, and the ΔΔG values associated with these destabilising mutations are much higher than thoseof the destabilising mutations in residues 47 and 601. Cysteine is stabilizing at allpositions except for residue 533, where it is the second most highly destabilizing mutation across all positions with a ΔΔG of -7.14. Residue 533 overall shows the most destabilizing mutations, with 3 of the 4 most negative values occurring at this position. Tryptophan at residue 200 stands out as the most stabilizing mutation across all positions, with a ΔΔG of 3.62, which is 2.03 higher than the next most stabilising mutation with a ΔΔG of 1.59 (also occurring at residue 200).Q3At residue 200 is in a more central position within the protein, at this position a mutation from valine to tryptophan displayed the highest ΔΔG of 3.62, and at that same position, a mutation from valine to lysine displayed a very negative, destabilising ΔΔG of -7.22. Tryptophan at position 200 introduces a large aromatic side chain to the position which could introduce hydrophobic interactions that help stabilise the protein or could be working to fill a void withinthe protein, helping to better pack the protein and increase stability. Lysine is a positively charged and polar, in hydrophobic environment this would be unfavourable, disrupting the environment and any hydrophobic interactions happening around it, leading to destabilisation of the protein. At residue 47 within the protein, a position toward the end of the amino acid chain, a mutation from the wildtype serine to a proline is the most stabilising mutation at the position with a ΔΔG of 1.52, at the same position a mutation to glycine is the most destabilising with a ΔΔG of -0.54. Glycine has only hydrogen atoms as side chains with no extensive structure, its conformation allows for a more flexibility around its position, in contrast, prolines cyclical structure provides it great conformational rigidity. Toward the end of the amio acid chain, the prolines rigidity could help secure the end and avoid fluctuation, while the glycine could allow the end to move to drastically and disrupt the conformation.Q4CupSAT is a tool used to analyse point mutations within a protein to predict stability changes that would occur as a result of mutation. The tool uses the PDB file of the target protein, evaluating structural features such as torsion angle andsecondary structure to predict the difference in free energy of unfolding betweena protein with the wildtype amino acid and one with the mutated amino acid (Camargo et al., 2015).
Part 2Q1Table in appendix. Q2Duet highlights mutations at position 533 to glycine, serine and cysteine as highly destabilising, glycine the most of the 3. These 3 amino acids all have smaller side chains that allow for more flexibility in the peptide backbone, mutations to other smaller amino acids like alanine are also shown to be amongst the more destabilising mutation. Alanine, while being smaller than cysteine and potentially allowing for more flexibility in the backbone, is non-polar while cysteine is polar. The least destabilising of the mutations are mutations to leucine and isoleucine, these both have relatively bulky, hydrophobic side chains that could potentially help stabilise the backbone in comparison to glycine serine and cysteine. Whilemutations to some amino acids result in less destabilisation than others, there are none that result in stabilisation of the protein. The wildtype amino acid at the position is a proline, the structure of proline is a cyclical ring that provides it great rigidity at that point, it is also hydrophobic, the combination of rigidity and being hydrophobic could mean it’s a better candidate than other amino acids at the position 533, resulting in any mutation being destabilising to the overall structure.Q3DUET and CUPSAT both give different results for the stabilising/destabilisng effects of mutations at residue 533. As an approach to determining effects of point mutations, CUPSAT uses mean force potentials specific to environment , taking into account factors such as solvent accessibility and secondary structure, which allows it to analyzehow local structural features influence protein stability. DUET combines the predictions of two sources (mCSM and SDM) using graph based signatures and analysis of existing data.When comparing DUET with CUPSAT, the differences in their methodologies highlight their unique strengths and weaknesses. DUET’s approach, which synthesizes data from multiple prediction models, allows it to leverage a broader range of information about protein structure and mutations. CUPSATS evaluation of mean force potentials specific to the environment allows it to focus on the immediate structural context of the residue. The more in depth analysis of the physics of each mutation provided by CUPSAT could potentially help it work better than DUET as an alternative.
AppendixQ1 part 1Predicted G for each mutant at each positionAmino acidResidue 47 Residue 200Residue 402Residue 533Residue 601GLY-0.54-4.59-3.22-1.580.17ALA0.05-2.83-2.72-4.35(wildtype AA)VAL0.4(wildtype AA)-1.09-3.790.32LEU-0.011.16-2.65-4.390.48ILE-0.311.38-1.98-3.761.33MET-0.521.59-3.831.190.07PRO1.52-3.06-2.0(wildtype AA)0.59TRP1.163.62-0.96-9.81-0.48SER(wildtype AA)-3.56-1.38-3.590.54THR0.31-1.5-0.67-5.551.01PHE0.961.13(wildtype AA)-1.95-0.49GLN0.8-2.79-1.36-3.79-0.86LYS-0.26-7.22-4.080.990.29TYR0.111.64-1.53-3.98-0.89ASN-0.38-0.86-1.64-3.420.7CYS0.110.820.56-7.140.56GLU0.3-4.99-1.79-2.47-0.4ASP-0.15-1.24-1.86-5.890.09ARG-0.32-2.78-2.31-0.01-0.39HIS-0.45-1.46-0.58-0.970.15Q1 part 2Mutations at residue 533 (wildtype proline)Mutant amino AcidΔΔG mCSMΔΔG DUETA-1.844-1.259 V-1.212-0.273
L-0.801-0.033 G-2.236-1.997 S-2.085-1.952 W-1.512-1.289 T-1.837-1.437 Q-1.478-1.135 E-1.87-1.383 C-2.061-1.685 R-0.976-0.707 D-1.988-1.537 F-1.337-0.882 I-0.801-0.068 H-1.65-1.203 N-1.415-0.981 M-1.19-0.827 Y-1.187-0.957 K-1.271-0.938 ReferencesCamargo, A., Machado, K. and Werhli, A. (2015) ‘Evaluation of computational tools for thermodynamics and structural analysis of protein stability upon point mutation prediction’, Proceedings of MOL2NET, International Conference on Multidisciplinary Sciences [Preprint]. doi:10.3390/mol2net-1-f001.