I have modeled a wild protein structure and their five mutant structure. Now i have analyzed their potential energy for normal and mutants. Potential energy calculated for wild, Pro420Arg, Arg386Cys, Phe216Ser, Met38Arg and Ala291Ser were -1575.30, -1570.45, -1619.0, -948.13, -1547.1 and -1559.21 kcal/mol respectively. How i can explain these P.E value with reference to their stability?
Dear Abdul,
You can compare potential energies of systems ONLY when the systems have the same molecular structure. For example isomers in general such as, isopropane and n-propane; cis and trans alkenes (the same number of C,H) can be compared.
If your proteins differ in one or more atoms the potential energy comparison is not useful. Only in the cases where the the proteins have the same atom type and number the comparison is valid.
From the values you listed in your question some of these proteins have different molecular structures.
Hoping this will be helpful,
Rafik
Dear Karaman, thanks for ur answer.
if i conclude the value like this that the normal has low P.E as compared to mutants as listed above value..so wild is stable as compared to mutants????
Dear Abdul,
Send me the structures along with the energies and I will give you my opinion regarding the stability.
Rafik
Dear Abdul,
Do you change atoms in the protein when you make mutation? If yes. There is no meaning to energy comparisons.
Rafik
Dear Sir,
yes i have changed atoms in the protein.
I have followed this paper "An In Silico Analysis of Troponin I Mutations in Hypertrophic Cardiomyopathy of Indian Origin" \. in this paper they have compared P.E of the protein with mutant by just replacing residue.. as "Asp222 of Troponin C is also reduced due to the comparatively neutral nature of mutant Gln98. Hence the change in nature and size of residues due to mutation Arg98Gln in Troponin I protein significantly reduces the protein-protein interactions with Troponin C in the troponin complex. The calculated potential energy of the wild type protein is −3313 kcal/ mol compared to −3220 kcal/mol for mutant protein. This may be due to the loss of intramolecular hydrogen bonds between side chain of Gln98 and neighbouring residues".
in another para they write as " Loss of intra-chain contacts occurs as the shorter Gln162 in mutant Troponin I can retain only the hydrogen bonded contact with Glu165 (Fig. 6b). Hence, the mutant is less stable which is supported by a decrease in (less negative) in potential energy (−3231 kcal/mol) as compared to wild type troponin I (−3313 kcal/mol)"
Dear Abdul,
Would you please send me the in -silico paper?
Thanks,
Rafik
sure sir, find here,
https://www.researchgate.net/publication/256073034_An_In_Silico_Analysis_of_Troponin_I_Mutations_in_Hypertrophic_Cardiomyopathy_of_Indian_Origin
Article An In Silico Analysis of Troponin I Mutations in Hypertrophi...
Dear Abdul,
The most stable one is Arg386Cys with an energy of -1619.0 followed by the wild with -1575.30. Pro420Arg in place number 3 with an energy of -1570.45. In the fourth place is Ala291Ser with -1559.21, in the fifth place Met38Arg with an energy of -1547.1 and in the last place Phe216Ser with an energy of -948.13.
To explain your results you should look at possible interactions that can stabilize the protein such as hydrogen bonding, Van der Waals interactions, ionic interactions, pi-pi interactions and etc.
If you tackle any problem explaining the energy differences, please let me know. However, I prefer to have the chemical structures of the wild and mutants in order to examine the possible interactions.
Good luck,
Rafik
It sounds like you are looking for the ddG of folding, the difference in the change in free energy of the unfolded to folded transition between the WT and mutant.
ddGWT->Mutant=dGunfolded->folded(WT) - dGunfolded->folded(mutant)
=PEWT_folded-PEWT_unfolded--PEMutant_folded+PEMutant_unfolded
Subtracting the PE of two folded conformations only takes into account two terms of this equation. It is assuming that PEMutant_unfolded = PEWT_unfolded, which is in general not true.
This problem can be eliminated by using a potential energy function that takes into account the energetics of the unfolded state, such as FoldX
- Badges
- Science topic
- Similar topics
- Bioinformatics
- Bioinformatics and Computational Biology