Abstract
γ-Aminobutyric acid transporters are responsible for regulating the GABA level in the synaptic cleft. In this way, they affect GABA-ergic transmission which is important for the proper functioning of the central nervous system. The exact structure of GABA transporters is still unknown, which hinders the design of new, potent and selective inhibitors. For these reasons, we decided to create models of all types of human gamma-aminobutyric acid transporters. They were built based on crystal structures of related proteins from the SLC6 family using homology modeling methods. The reliability of the received models has been confirmed by a number of tools assessing the quality of protein models. To determine the ligand binding mode and indicate the amino acids responsible for selectivity, docking studies and molecular dynamics simulations were performed. The amino acids lining the bottom of the main binding site have a major impact on the selective ligand binding. In addition, an important element is the non-helical fragment of the transmembrane domain 10, and several amino acids within the vestibule of the transporters, which affect its volume. To check whether obtained models are suitable to distinguish active compounds from inactive ones, enrichment plots were prepared. Results suggest that our models may be useful in the search for new inhibitors of GABA transporters of the desired selectivity.
Highlights
Introduction γAminobutyric acid (GABA) is a major inhibitory neurotransmitter in the central nervous system [1]
It can be seen that the best models for each type of Gamma-aminobutyric acid (GABA) transporter were built on 4XP9, 4XP4 and 4XPH templates (Table 1S and Fig. 2S, Supporting information)
The nipecotic acid fragment of tiagabine is arranged in a way that allows the formation of hydrophobic interactions between the carbon atoms of the piperidine ring and side chains of TYR60 and LEU300
Summary
Models of the GABA transporter were built applying homology modeling. Considering the similarity of the amino acid sequence, the best templates for building GAT models seem to be the crystal structures of dopamine and serotonin transporters (Table 1). In order to evaluate the quality of the generated models, various tools were used: QMEAN, DOPE score, Verify3D and Ramachandran plots These tools check a number of different parameters important from the viewpoint of the correctness of built models and their similarities to actual protein structures. GAT models built on dDAT and hSERT templates were higher rated than those built on aLeuT It is not surprising, given the higher degree of amino acid sequence similarity with GABA transporters. Given the higher degree of amino acid sequence similarity with GABA transporters All of these models constructed on monoamine transporters have over 90% of the amino acids in the most favored regions in the Ramachandran plot (Fig. 2S, Supporting information), and almost have over 80% amino acids with score ≥0.2 according to Verify 3D. These models were taken into account in docking studies
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