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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

Bound Conformations of Inhibitor Candidates.Equilibrated bound conformers of the (a) reference peptide, (b) the top scoring peptide, RVTWEGKF, (c) the second highest scoring peptide, RGTFEGRF, and (d) the third best scoring peptide, RITFEIKF, to the Aβ42 fibril are shown. The conformations at time instant 2ns of the CMD are depicted. The protein is represented in transparent tube representation. The GxMxG motif is shown by its residue type. The peptide and all residues within 3.5Å of it are shown by the licorice drawing method. To distinguish the peptide and protein residues easily, peptide carbons were colored in black.
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pone-0066178-g004: Bound Conformations of Inhibitor Candidates.Equilibrated bound conformers of the (a) reference peptide, (b) the top scoring peptide, RVTWEGKF, (c) the second highest scoring peptide, RGTFEGRF, and (d) the third best scoring peptide, RITFEIKF, to the Aβ42 fibril are shown. The conformations at time instant 2ns of the CMD are depicted. The protein is represented in transparent tube representation. The GxMxG motif is shown by its residue type. The peptide and all residues within 3.5Å of it are shown by the licorice drawing method. To distinguish the peptide and protein residues easily, peptide carbons were colored in black.

Mentions: 23 single-residue mutations were performed based on the grouping system provided in Table 1. Mutations are shown schematically in Fig. 3. 11 single residue mutations resulted in higher Goldscore docking scores than the reference peptide and are shown with red letters in the figure. The ICL was initialized with these 11 one-point mutated residues. The recursive combine-mutate-dock cycle was performed twice and mutations were accepted or rejected depending on their Goldscores. At the end of these two cycles the ICL contained N = 300 peptides. In order to further decrease this number, their Chemscore docking scores were evaluated. Among the 300 peptides, only 11 showed better Chemscores than the reference peptide. These11 peptides, which bind the amyloid surface with a better Chemscore and Goldscore values than the reference peptide, are listed in Table 2 together with these values. The binding conformations of the top scoring 3 peptides and the reference peptide are shown in their bound form in Fig. 4.


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)

Bound Conformations of Inhibitor Candidates.Equilibrated bound conformers of the (a) reference peptide, (b) the top scoring peptide, RVTWEGKF, (c) the second highest scoring peptide, RGTFEGRF, and (d) the third best scoring peptide, RITFEIKF, to the Aβ42 fibril are shown. The conformations at time instant 2ns of the CMD are depicted. The protein is represented in transparent tube representation. The GxMxG motif is shown by its residue type. The peptide and all residues within 3.5Å of it are shown by the licorice drawing method. To distinguish the peptide and protein residues easily, peptide carbons were colored in black.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0066178-g004: Bound Conformations of Inhibitor Candidates.Equilibrated bound conformers of the (a) reference peptide, (b) the top scoring peptide, RVTWEGKF, (c) the second highest scoring peptide, RGTFEGRF, and (d) the third best scoring peptide, RITFEIKF, to the Aβ42 fibril are shown. The conformations at time instant 2ns of the CMD are depicted. The protein is represented in transparent tube representation. The GxMxG motif is shown by its residue type. The peptide and all residues within 3.5Å of it are shown by the licorice drawing method. To distinguish the peptide and protein residues easily, peptide carbons were colored in black.
Mentions: 23 single-residue mutations were performed based on the grouping system provided in Table 1. Mutations are shown schematically in Fig. 3. 11 single residue mutations resulted in higher Goldscore docking scores than the reference peptide and are shown with red letters in the figure. The ICL was initialized with these 11 one-point mutated residues. The recursive combine-mutate-dock cycle was performed twice and mutations were accepted or rejected depending on their Goldscores. At the end of these two cycles the ICL contained N = 300 peptides. In order to further decrease this number, their Chemscore docking scores were evaluated. Among the 300 peptides, only 11 showed better Chemscores than the reference peptide. These11 peptides, which bind the amyloid surface with a better Chemscore and Goldscore values than the reference peptide, are listed in Table 2 together with these values. The binding conformations of the top scoring 3 peptides and the reference peptide are shown in their bound form in Fig. 4.

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