Molecular Dynamics Simulations of a Conformationally Mobile Peptide-Based Catalyst for Atroposelective Bromination

Abstract

It is widely accepted that structural rigidity is required to achieve high levels of asymmetric induction in catalytic, enantioselective reactions. This fundamental design principle often does not apply to highly selective catalytic peptides that often exhibit conformational heterogeneity. As a result, these complex systems are particularly challenging to study both experimentally and computationally. Herein, we utilize molecular dynamics simulations to investigate the role of conformational mobility on the reactivity and selectivity exhibited by a catalytic, β-turn-biased peptide in an atroposelective bromination reaction. By means of cluster analysis, multiple distinct conformers of the peptide and a catalyst-substrate complex were identified in the simulations, all of which were corroborated by experimental NMR measurements. The simulations also revealed that a shift in the conformational equilibrium of the peptidic catalyst occurs upon addition of substrate, and the degree of change varies among different substrates. On the basis of these data, we propose a correlation between the composition of the peptide conformational ensemble and its catalytic properties. Moreover, these findings highlight the importance of conformational dynamics in catalytic, asymmetric reactions mediated by oligopeptides, unveiled through high-level, state-of-the-art computational modeling.

Keywords: Asymmetric Catalysis; Atropisomerism; Cluster Analysis; Conformation; Molecular Dynamics; Peptides.

Figure 1.

Three distinct conformers of peptide 3 observed in crystal structures. Based on the ϕ and ψ dihedrals of the loop region residues and the internal H-bonding network, conformers 3a and 3b are classified as type II′ β-hairpins. Conformer 3c classifies as a type I′ β-turn that is pre-helical in geometry.

Figure 2.

Joint distribution plots of backbone dihedral angles ϕ and ψ in the (a) i+1 and (b) i+2 residues of peptide 3 from MD simulations in benzene. The crystallographic values are marked by triangles.

Figure 3.

Representative structures of the confonners identified from the cluster analysis: (a) Conformer 3a/b, (b) overlay of confonners 3c (blue) and 3d (green), and (c) confonner 3e.

Figure 4.

Scatter plots of backbone dihedral angles ϕ and ψ in the (a) i+1 and (b) i+2 residues of peptide 3 from MD simulations in benzene (colored according to cluster). The crystallographic values and centroids of clusters are denoted by red triangles and black dots, respectively.

Figure 5.

Conformational composition from cluster analysis. (a) Peptide 3 alone in benzene. (b) Peptide 3 in the presence of substrate (aS)-1a. (c) Peptide 3 in the presence of substrate (aS)-1b. (d) Peptide 3 in the presence of substrate (aR)-1a. (e) Peptide 3 in the presence of substrate (aR)-1b.

Figure 6.

Joint distribution plots of backbone dihedral angles ϕ and ψ in the (a) i+1 and (b) i+2 residues of peptide 3 in the presence of substrate (aS)-1a from MD simulations in benzene. The crystallographic values are marked by triangles.

Figure 7.

Composition of binding poses in the cluster analysis of (a) 3+1a complex and (b) 3+1b complex. (c) Overlay of binding pose A in the 3+1a (grey) and 3+1b (cyan) complexes.

Figure 8.

Joint distribution plots of backbone dihedral angles ϕ and ψ in the (a) i+1 and (b) i+2 residues of peptide 3+1b from MD simulations in benzene. The crystallographic values are marked by triangles.

Figure 9.

Plot of through-space distances from NOESY measurements versus simulations, (a) Intramolecular interactions in peptide 3. (b) Intennolecular interactions between peptide 3 and substrates in binding pose A.

Scheme 1.

Peptide-catalyzed, atroposelective bromination of 3-arylquinazolin-4(3H)-ones 1.