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. 2020 Nov 25;25(23):5509.
doi: 10.3390/molecules25235509.

In Silico Design of a Peptide Receptor for Dopamine Recognition

Luna Rodriguez-Salazar  1 , James Guevara-Pulido  2 , Andrés Cifuentes  2
Affiliations

In Silico Design of a Peptide Receptor for Dopamine Recognition

Luna Rodriguez-Salazar et al. Molecules. .

Abstract

Dopamine (DA) is an important neurotransmitter with a fundamental role in regulatory functions related to the central, peripheral, renal, and hormonal nervous systems. Dopaminergic neurotransmission dysfunctions are commonly associated with several diseases; thus, in situ quantification of DA is a major challenge. To achieve this goal, enzyme-based biosensors have been employed for substrate recognition in the past. However, due to their sensitivity to changes in temperature and pH levels, new peptide bioreceptors have been developed. Therefore, in this study, four bioreceptors were designed in silico to exhibit a higher affinity for DA than the DA transporters (DATs). The design was based on the hot spots of the active sites of crystallized enzyme structures that are physiologically related to DA. The affinities between the chosen targets and designed bioreceptors were calculated using AutoDock Vina. Additionally, the binding free energy, ∆G, of the dopamine-4xp1 complex was calculated by molecular dynamics (MD). This value presented a direct relationship with the E_refine value obtained from molecular docking based on the ∆G functions obtained from MOE of the promising bioreceptors. The control variables in the design were amino acids, bond type, steric volume, stereochemistry, affinity, and interaction distances. As part of the results, three out of the four bioreceptor candidates presented promising values in terms of DA affinity and distance.

Keywords: bioreceptor; dopamine; in silico; molecular docking; molecular dynamics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
General scheme for the polymerization of the bioreceptors. (A) For those bioreceptors composed solely of peptides. (B) For those bioreceptors with methylene bridges within the amino acid sequence.
Figure 2
Figure 2
Polystyrene–NWR–polystyrene bioreceptor showing each of the amino acids that will be stereochemically modified.
Figure 3
Figure 3
General structure of the bioreceptors with variations in the amount of glycine.
Figure 4
Figure 4
The general structure of the receptors wherein the nature of amino acids is studied.
Figure 5
Figure 5
Representative ligand–complex interactions for the best score of the dopamine-4xp1 complex. (A) Analysis of 2D interactions. (B) Best score position in binding-pocket.
Figure 6
Figure 6
Docking score results for the dopamine–SD complex (docked with MOE). (A) Best score pose. (B) Best E_refine (molecule 2) with the best dopamine–bioreceptor non-covalent interactions.
Figure 7
Figure 7
Docking score results for the dopamine–SDW complex (docked with MOE). (A) Best score pose. (B) Best E_refine (molecule 3) with the best dopamine–bioreceptor non-covalent interactions.
Figure 8
Figure 8
Best docking score results of the dopamine–WFT complex (docked with MOE).
Figure 9
Figure 9
Visualization of the interaction between the DAT and DA. The length of the hydrogen bonds formed (Green dotted line) are shown.
Figure 10
Figure 10
Visualization of the interactions of the selected bioreceptors showing the measured hydrogen bonds formed between dopamine and the amino acids of the bioreceptor. (A) Bioreceptor WFT. (B) Bioreceptor SDW. (C) Bioreceptor SD.
Figure 10
Figure 10
Visualization of the interactions of the selected bioreceptors showing the measured hydrogen bonds formed between dopamine and the amino acids of the bioreceptor. (A) Bioreceptor WFT. (B) Bioreceptor SDW. (C) Bioreceptor SD.
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