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Computational design of new Peptide inhibitors for amyloid Beta (aβ) aggregation in Alzheimer's disease: application of a novel methodology.

Eskici G, Gur M - PLoS ONE (2013)

Bottom Line: Its efficiency lies in the fact that it does not perform all possible combinations of mutations, therefore decreasing the computational time drastically.The potential of mean forces (PMFs) were calculated by applying the Jarzynski's equality to results of steered molecular dynamics simulations.For all of the top scoring derivatives, the PMFs showed higher binding free energies than the reference peptide substantiating the usage of the introduced methodology to drug design.

View Article: PubMed Central - PubMed

Affiliation: Center for Computational Biology and Bioinformatics, Koc University, Istanbul, Turkey.

ABSTRACT
Alzheimer's disease is the most common form of dementia. It is a neurodegenerative and incurable disease that is associated with the tight packing of amyloid fibrils. This packing is facilitated by the compatibility of the ridges and grooves on the amyloid surface. The GxMxG motif is the major factor creating the compatibility between two amyloid surfaces, making it an important target for the design of amyloid aggregation inhibitors. In this study, a peptide, experimentally proven to bind Aβ40 fibrils at the GxMxG motif, was mutated by a novel methodology that systematically replaces amino acids with residues that share similar chemical characteristics and subsequently assesses the energetic favorability of these mutations by docking. Successive mutations are combined and reassessed via docking to a desired level of refinement. This methodology is both fast and efficient in providing potential inhibitors. Its efficiency lies in the fact that it does not perform all possible combinations of mutations, therefore decreasing the computational time drastically. The binding free energies of the experimentally studied reference peptide and its three top scoring derivatives were evaluated as a final assessment/valuation. The potential of mean forces (PMFs) were calculated by applying the Jarzynski's equality to results of steered molecular dynamics simulations. For all of the top scoring derivatives, the PMFs showed higher binding free energies than the reference peptide substantiating the usage of the introduced methodology to drug design.

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Related in: MedlinePlus

Potential of Mean Force for Unbinding.PMFs of the top scoring mutated peptides in Table 2 and the reference peptide with respect to the RC .
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pone-0066178-g006: Potential of Mean Force for Unbinding.PMFs of the top scoring mutated peptides in Table 2 and the reference peptide with respect to the RC .

Mentions: The reference peptide and the 3 top scoring inhibitor candidates were selected for further investigation. For each of these peptides, 14 independent SMD simulations were performed. The ensemble averages of the external forces along the RCs of the reference peptide and top scoring inhibitor candidate (RVTWEGKF) are shown in Fig.5. The difference between the curves indicates that the unbinding of the reference peptide is easier than the top scoring peptide. In Fig.6, the PMFs for the unbinding of the three top scoring inhibitor candidates and the reference peptide are shown along their RCs. The PMFs predict a higher binding energy for all of the three derivative peptides in agreement with the Gold- and Chemscores. However, it has to be noted that the top scoring second and third peptides switched their rankings in the PMF.


Computational design of new Peptide inhibitors for amyloid Beta (aβ) aggregation in Alzheimer's disease: application of a novel methodology.

Eskici G, Gur M - PLoS ONE (2013)

Potential of Mean Force for Unbinding.PMFs of the top scoring mutated peptides in Table 2 and the reference peptide with respect to the RC .
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3675214&req=5

pone-0066178-g006: Potential of Mean Force for Unbinding.PMFs of the top scoring mutated peptides in Table 2 and the reference peptide with respect to the RC .
Mentions: The reference peptide and the 3 top scoring inhibitor candidates were selected for further investigation. For each of these peptides, 14 independent SMD simulations were performed. The ensemble averages of the external forces along the RCs of the reference peptide and top scoring inhibitor candidate (RVTWEGKF) are shown in Fig.5. The difference between the curves indicates that the unbinding of the reference peptide is easier than the top scoring peptide. In Fig.6, the PMFs for the unbinding of the three top scoring inhibitor candidates and the reference peptide are shown along their RCs. The PMFs predict a higher binding energy for all of the three derivative peptides in agreement with the Gold- and Chemscores. However, it has to be noted that the top scoring second and third peptides switched their rankings in the PMF.

Bottom Line: Its efficiency lies in the fact that it does not perform all possible combinations of mutations, therefore decreasing the computational time drastically.The potential of mean forces (PMFs) were calculated by applying the Jarzynski's equality to results of steered molecular dynamics simulations.For all of the top scoring derivatives, the PMFs showed higher binding free energies than the reference peptide substantiating the usage of the introduced methodology to drug design.

View Article: PubMed Central - PubMed

Affiliation: Center for Computational Biology and Bioinformatics, Koc University, Istanbul, Turkey.

ABSTRACT
Alzheimer's disease is the most common form of dementia. It is a neurodegenerative and incurable disease that is associated with the tight packing of amyloid fibrils. This packing is facilitated by the compatibility of the ridges and grooves on the amyloid surface. The GxMxG motif is the major factor creating the compatibility between two amyloid surfaces, making it an important target for the design of amyloid aggregation inhibitors. In this study, a peptide, experimentally proven to bind Aβ40 fibrils at the GxMxG motif, was mutated by a novel methodology that systematically replaces amino acids with residues that share similar chemical characteristics and subsequently assesses the energetic favorability of these mutations by docking. Successive mutations are combined and reassessed via docking to a desired level of refinement. This methodology is both fast and efficient in providing potential inhibitors. Its efficiency lies in the fact that it does not perform all possible combinations of mutations, therefore decreasing the computational time drastically. The binding free energies of the experimentally studied reference peptide and its three top scoring derivatives were evaluated as a final assessment/valuation. The potential of mean forces (PMFs) were calculated by applying the Jarzynski's equality to results of steered molecular dynamics simulations. For all of the top scoring derivatives, the PMFs showed higher binding free energies than the reference peptide substantiating the usage of the introduced methodology to drug design.

Show MeSH
Related in: MedlinePlus