In Silico Design of a Peptide Receptor for Dopamine Recognition

Abstract

Background: 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, owing to their sensitivity to changes in temperature and pH levels. Results: New peptide bioreceptors have been developed. Based on this, 45 in silico bioreceptors were designed to exhibit a higher affinity than that of the DA transporters (DATs). The design was based on the active sites of crystallized enzyme structures that are physiologically related to DA. These affinities were calculated using AutoDock Vina and by assessing the interaction energy between DA and the active DAT site. The controlled variables in the design were amino acids, bond type, steric volume, stereochemistry, affinity, and interaction distances. Conclusions: Three bioreceptor candidates presenting promising values ​​in terms of DA affinity and distance were obtained.

In Silico Design of a Peptide Receptor for Dopamine Recognition

“…Therefore, for the bioreceptor 2.1, the possible interactions that existed before adding the methylene bridges are lost. This result contradicts that in a previous report [18], but if it is considered that the substrate size in the previous study was much larger in terms of DA, it could be construed that the molecule can only generate a small number of interactions.…”

“…As expected, the results indicated the affinity of the three bioreceptors' affinity DA was low in terms of the interaction energy of the DAT, which is −5.2 kcal/mol. These results were expected because the steric hindrance exhibited by a peptide within this design length range is not comparable with that of the enzyme [18]. As previously reported [18], it is important to identify amino acids capable of generating interaction with the substrate and crucial to mimic the steric volume of the target protein with which competition is desired in terms of interaction energy for the substrate of interest because this is a criterion that directly influences affinity.…”

“…Thus, two options were considered. The first was to consider the number of residues between the selected amino acids and the second was to increase the steric volume of the bioreceptors to increase their affinity [18].…”

“…One of these bioreceptors are peptides and are emerging as an alternative for molecular recognition, in addition to being considered versatile molecules because they can be synthesized with a wide variety of structural modifications [16,17]. In silico models of peptide bioreceptors [18] and biosensors using peptide bioreceptors have already been designed for substrate recognition [19].…”

“…Therefore, as part of our study of our bioreceptor design group for the recognition of a particular substrate [18], the in silico design of possible bioreceptors that recognize in silico DA is being completed to subsequently perform its synthesis. This way, the in vitro design and testing process can be more efficient and faster owing to the implementation of bioinformatics tools, such as molecular modeling, to assess the bioreceptor-ligand interaction and improve it against the proteinligand complex interaction [20], which is usually formed with the DA transporter (DAT) in the biological process of dopaminergic neurotransmission [21].…”