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Identification of small-molecule binding pockets in the soluble monomeric form of the Aβ42 peptide
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Image of FIG. 1.
FIG. 1.

Scheme illustrating the strategy discussed in this work in which molecular dynamics simulations are combined with computer-based fragment-based hot spot mapping to identify potential binding sites on the soluble monomeric form of the Aβ42 peptide. (a) Representative structures are selected by a clustering procedure within an ensemble of conformations representing the natively unfolded state of the Aβ42 peptide. (b) Hot spot regions are mapped on these structures using a set of small molecule fragments. (c) Neighbouring hot spot regions are identified as potential small-molecule binding sites.

Image of FIG. 2.
FIG. 2.

Analysis of the convergence of the molecular dynamics simulations used in this work to generate an ensemble of structures representing the soluble monomeric form of the Aβ42 peptide: (a) Time series of the correlation between experimental and calculated Cα chemical shifts, which indicate that after about 40 ns (out of a total of 100 ns) a good correlation is reached between experimental and calculated chemical shifts. (b) Time series of the radius of gyration. (c) Time series of the solvent accessible surface area (SASA).

Image of FIG. 3.
FIG. 3.

Validation of the ensemble of conformations representing the soluble monomeric form of the Aβ42 peptide used in this work. (a)–(c) Correlation between experimental and back-calculated chemical shifts: Cα (a), Hα (b), and N (c). (d) Comparison between experimental (black) and back-calculated (red) couplings (Hz). (e) Comparison between experimental (black) and back-calculated (red) residual dipolar couplings (RDCs, Hz). For reference, couplings and RDCs are also shown as predicted by the statistical coil model (grey). (f) Inter-residue distance map (Å).

Image of FIG. 4.
FIG. 4.

Free energy landscape of the Aβ42 peptide as a function of the number of hydrogen bonds (backbone-backbone, backbone-sidechain, and sidechain-sidechain) and of the solvent-exposed surface area of hydrophobic residues. Hydrogen bonds were defined using the GROMACS g_hbond function, when hydrogen donors and acceptors are within 3.5 Å and the hydrogen-donor-acceptor angles are within 30°. The most populated clusters are found in different regions of the free energy landscape.

Image of FIG. 5.
FIG. 5.

Characterisation of eight representative clusters of structures within the ensemble of conformations of the soluble monomeric form of the Aβ42 peptide used in this work. We consider here the five most populated clusters (cluster 1–5) together with three more examples of clusters found to contain binding pockets (clusters 10, 27, and 35). Highly populated clusters may (as clusters 1 and 2) or may not (as clusters 3, 4, and 5) exhibit binding pockets. For each cluster we report the secondary structure elements determined by DSSP (yellow: turns; blue: α-helices; red: β-sheets) and the side-chain distance maps. The five shortest long-range side-chain contacts (i.e., more than three residues apart along the amino acid sequence) are indicated by red lines.

Image of FIG. 6.
FIG. 6.

Illustration of the ten binding pockets identified by fragment-probe mapping in the ten most populated clusters (see Table I ) within the Aβ42 structural ensemble used in this work.

Image of FIG. 7.
FIG. 7.

Examples of adjacent binding pockets in the soluble monomeric form of the Aβ42 peptide identified through the approach described in this work. Results for clusters 2 and 35 (see Fig. 4 ) are shown together with a characterisation of the corresponding hot spots, the potential ligand efficiency ( ) (in kcal/mol, see Methods section).

Image of FIG. 8.
FIG. 8.

Comparison between the potential ligand efficiency ( ) (x-axis, in kcal/mol, see Methods section) and the number of hydrogen bonds (y axis) for all the poses of the fragments in the binding hot spots identified in this work within the Aβ42 structural ensemble (red circles) and those in model globular proteins (black crosses, see Methods section and Tables S1 and S2 in the supplementary material ); the red circles correspond to the hot-spot IDs listed in Table I .

Image of FIG. 9.
FIG. 9.

Residue-specific probability of binding small molecular fragments in hot spots of the Aβ42 peptide, calculated by FTMap (see Methods section). Non-bonded (black bars) and hydrogen bond (red bars) interactions are shown separately. The central hydrophobic region (CHC, residues Leu17-Ala21) is particular involved in hot spot formation.

Image of FIG. 10.
FIG. 10.

Top binding modes of curcumin (left) and Congo red (right) with the Aβ42 peptide, which were identified through the analysis of the fragment-based mapping of the binding hot spots; hot spot labels refer to Table I and Figure 6 (pocket II in cluster 2 for curcumin and pocket V in cluster 18 for Congo red). Molecular dynamics simulations of the complexes show that the ligands remain bound over a 80 ns period.


Generic image for table
Table I.

List of the ten binding pockets (in roman numerals, column 2) and corresponding binding hot spots (in arabic numerals, column 3) identified within ten specific clusters of conformations (column 1) in the Aβ42 structural ensemble described in this work. Each of these ten clusters exhibits one binding pocket comprising between two and five binding hot spots; for example binding pocket VI is found in cluster 24 and comprises four hot spots. The remaining 35 clusters among the 45 that we analysed in detail did not exhibit binding pockets. The specific residues in the hot spots are also reported (column 4). The structures of the ten binding pockets are shown in Figure 6 .


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Identification of small-molecule binding pockets in the soluble monomeric form of the Aβ42 peptide