Studies of structural determinants of substrate binding in the Creatine Transporter (CreaT, SLC6A8) using molecular models.
Aquifex
Bacterial Proteins
/ ultrastructure
Binding Sites
Creatine
/ chemistry
Ligands
Molecular Docking Simulation
Nerve Tissue Proteins
/ chemistry
Plasma Membrane Neurotransmitter Transport Proteins
/ chemistry
Protein Conformation, alpha-Helical
Sequence Alignment
Sequence Homology, Amino Acid
Serotonin Plasma Membrane Transport Proteins
/ ultrastructure
Substrate Specificity
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
10 04 2020
10 04 2020
Historique:
received:
14
01
2020
accepted:
26
03
2020
entrez:
12
4
2020
pubmed:
12
4
2020
medline:
15
12
2020
Statut:
epublish
Résumé
Creatine is a crucial metabolite that plays a fundamental role in ATP homeostasis in tissues with high-energy demands. The creatine transporter (CreaT, SLC6A8) belongs to the solute carrier 6 (SLC6) transporters family, and more particularly to the GABA transporters (GATs) subfamily. Understanding the molecular determinants of specificity within the SLC6 transporters in general, and the GATs in particular is very challenging due to the high similarity of these proteins. In the study presented here, our efforts focused on finding key structural features involved in binding selectivity for CreaT using structure-based computational methods. Due to the lack of three-dimensional structures of SLC6A8, our approach was based on the realization of two reliable homology models of CreaT using the structures of two templates, i.e. the human serotonin transporter (hSERT) and the prokaryotic leucine transporter (LeuT). Our models reveal that an optimal complementarity between the shape of the binding site and the size of the ligands is necessary for transport. These findings provide a framework for a deeper understanding of substrate selectivity of the SLC6 family and other LeuT fold transporters.
Identifiants
pubmed: 32277128
doi: 10.1038/s41598-020-63189-z
pii: 10.1038/s41598-020-63189-z
pmc: PMC7148354
doi:
Substances chimiques
Bacterial Proteins
0
Ligands
0
Nerve Tissue Proteins
0
Plasma Membrane Neurotransmitter Transport Proteins
0
SLC6A4 protein, human
0
SLC6A8 protein, human
0
Serotonin Plasma Membrane Transport Proteins
0
Creatine
MU72812GK0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
6241Références
Salomons, G. S. et al. X-linked creatine transporter defect: an overview. Journal of inherited metabolic disease 26, 309–318, https://doi.org/10.1023/a:1024405821638 (2003).
doi: 10.1023/a:1024405821638
pubmed: 12889669
Rosenberg, E. H. et al. High prevalence of SLC6A8 deficiency in X-linked mental retardation. American journal of human genetics 75, 97–105, https://doi.org/10.1086/422102 (2004).
doi: 10.1086/422102
pubmed: 15154114
pmcid: 1182013
Broer, S. & Gether, U. The solute carrier 6 family of transporters. Br J Pharmacol 167, 256–278, https://doi.org/10.1111/j.1476-5381.2012.01975.x (2012).
doi: 10.1111/j.1476-5381.2012.01975.x
pubmed: 22519513
pmcid: 3481037
Kristensen, A. S. et al. SLC6 neurotransmitter transporters: structure, function, and regulation. Pharmacological reviews 63, 585–640, https://doi.org/10.1124/pr.108.000869 (2011).
doi: 10.1124/pr.108.000869
pubmed: 21752877
Lie, M. E. K. et al. Glial GABA Transporters as Modulators of Inhibitory Signalling in Epilepsy and Stroke. Advances in neurobiology 16, 137–167, https://doi.org/10.1007/978-3-319-55769-4_7 (2017).
doi: 10.1007/978-3-319-55769-4_7
pubmed: 28828609
Clarkson, A. N., Huang, B. S., Macisaac, S. E., Mody, I. & Carmichael, S. T. Reducing excessive GABA-mediated tonic inhibition promotes functional recovery after stroke. Nature 468, 305–309, https://doi.org/10.1038/nature09511 (2010).
doi: 10.1038/nature09511
pubmed: 21048709
pmcid: 3058798
Drew, D. & Boudker, O. Shared Molecular Mechanisms of Membrane Transporters. Annual review of biochemistry 85, 543–572, https://doi.org/10.1146/annurev-biochem-060815-014520 (2016).
doi: 10.1146/annurev-biochem-060815-014520
pubmed: 27023848
Forrest, L. R., Kramer, R. & Ziegler, C. The structural basis of secondary active transport mechanisms. Biochimica et biophysica acta 1807, 167–188, https://doi.org/10.1016/j.bbabio.2010.10.014 (2011).
doi: 10.1016/j.bbabio.2010.10.014
pubmed: 21029721
Forrest, L. R. & Rudnick, G. The rocking bundle: a mechanism for ion-coupled solute flux by symmetrical transporters. Physiology (Bethesda) 24, 377–386, https://doi.org/10.1152/physiol.00030.2009 (2009).
doi: 10.1152/physiol.00030.2009
Beuming, T., Shi, L., Javitch, J. A. & Weinstein, H. A comprehensive structure-based alignment of prokaryotic and eukaryotic neurotransmitter/Na+ symporters (NSS) aids in the use of the LeuT structure to probe NSS structure and function. Mol Pharmacol 70, 1630–1642, https://doi.org/10.1124/mol.106.026120 (2006).
doi: 10.1124/mol.106.026120
pubmed: 16880288
Loland, C. J. The use of LeuT as a model in elucidating binding sites for substrates and inhibitors in neurotransmitter transporters. Biochimica et biophysica acta 1850, 500–510, https://doi.org/10.1016/j.bbagen.2014.04.011 (2015).
doi: 10.1016/j.bbagen.2014.04.011
pubmed: 24769398
Nyola, A. et al. Substrate and drug binding sites in LeuT. Current opinion in structural biology 20, 415–422, https://doi.org/10.1016/j.sbi.2010.05.007 (2010).
doi: 10.1016/j.sbi.2010.05.007
pubmed: 20739005
pmcid: 2925194
Coleman, J. A. et al. Serotonin transporter-ibogaine complexes illuminate mechanisms of inhibition and transport. Nature 569, 141–145, https://doi.org/10.1038/s41586-019-1135-1 (2019).
doi: 10.1038/s41586-019-1135-1
pubmed: 31019304
pmcid: 6750207
Coleman, J. A. & Gouaux, E. Structural basis for recognition of diverse antidepressants by the human serotonin transporter. Nature structural & molecular biology 25, 170–175, https://doi.org/10.1038/s41594-018-0026-8 (2018).
doi: 10.1038/s41594-018-0026-8
Coleman, J. A., Green, E. M. & Gouaux, E. X-ray structures and mechanism of the human serotonin transporter. Nature 532, 334–339, https://doi.org/10.1038/nature17629 (2016).
doi: 10.1038/nature17629
pubmed: 27049939
pmcid: 4898786
Penmatsa, A., Wang, K. H. & Gouaux, E. X-ray structure of dopamine transporter elucidates antidepressant mechanism. Nature 503, 85–90, https://doi.org/10.1038/nature12533 (2013).
doi: 10.1038/nature12533
pubmed: 24037379
pmcid: 3904663
Dayan, O. et al. An Extra Amino Acid Residue in Transmembrane Domain 10 of the gamma-Aminobutyric Acid (GABA) Transporter GAT-1 Is Required for Efficient Ion-coupled Transport. The Journal of biological chemistry 292, 5418–5428, https://doi.org/10.1074/jbc.M117.775189 (2017).
doi: 10.1074/jbc.M117.775189
pubmed: 28213519
pmcid: 5392685
Kickinger, S. et al. Structural and molecular aspects of betaine-GABA transporter 1 (BGT1) and its relation to brain function. Neuropharmacology, https://doi.org/10.1016/j.neuropharm.2019.05.021 (2019).
Schlessinger, A. et al. High Selectivity of the gamma-Aminobutyric Acid Transporter 2 (GAT-2, SLC6A13) Revealed by Structure-based Approach. Journal of Biological Chemistry 287, 37745–37756, https://doi.org/10.1074/jbc.M112.388157 (2012).
doi: 10.1074/jbc.M112.388157
pubmed: 22932902
Vogensen, S. B. et al. Structure activity relationship of selective GABA uptake inhibitors. Bioorganic & medicinal chemistry 23, 2480–2488, https://doi.org/10.1016/j.bmc.2015.03.060 (2015).
doi: 10.1016/j.bmc.2015.03.060
Ponzoni, L., Zhang, S., Cheng, M. H. & Bahar, I. Shared dynamics of LeuT superfamily members and allosteric differentiation by structural irregularities and multimerization. Philosophical transactions of the Royal Society of London. Series B, Biological sciences 373, https://doi.org/10.1098/rstb.2017.0177 (2018).
Eswar, N. et al. Tools for comparative protein structure modeling and analysis. Nucleic acids research 31, 3375–3380 (2003).
doi: 10.1093/nar/gkg543
Shen, M. Y. & Sali, A. Statistical potential for assessment and prediction of protein structures. Protein Sci 15, 2507–2524 (2006).
doi: 10.1110/ps.062416606
Dodd, J. R. & Christie, D. L. Selective amino acid substitutions convert the creatine transporter to a gamma-aminobutyric acid transporter. The Journal of biological chemistry 282, 15528–15533, https://doi.org/10.1074/jbc.M611705200 (2007).
doi: 10.1074/jbc.M611705200
pubmed: 17400549
Dodd, J. R. & Christie, D. L. Cysteine 144 in the third transmembrane domain of the creatine transporter is located close to a substrate-binding site. The Journal of biological chemistry 276, 46983–46988, https://doi.org/10.1074/jbc.M107137200 (2001).
doi: 10.1074/jbc.M107137200
pubmed: 11598117
Dodd, J. R. & Christie, D. L. Substituted cysteine accessibility of the third transmembrane domain of the creatine transporter: defining a transport pathway. The Journal of biological chemistry 280, 32649–32654, https://doi.org/10.1074/jbc.M506723200 (2005).
doi: 10.1074/jbc.M506723200
pubmed: 16049011
Guimbal, C. & Kilimann, M. W. A creatine transporter cDNA from Torpedo illustrates structure/function relationships in the GABA/noradrenaline transporter family. Journal of molecular biology 241, 317–324, https://doi.org/10.1006/jmbi.1994.1507 (1994).
doi: 10.1006/jmbi.1994.1507
pubmed: 8057375
Guimbal, C. & Kilimann, M. W. A Na(+)-dependent creatine transporter in rabbit brain, muscle, heart, and kidney. cDNA cloning and functional expression. The Journal of biological chemistry 268, 8418–8421 (1993).
pubmed: 8473283
Genheden, S. R. U. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opinion on Drug Discovery. 10, 449–461 (2015).
doi: 10.1517/17460441.2015.1032936
Colas, C. et al. Chemical Modulation of the Human Oligopeptide Transporter 1, hPepT1. Molecular pharmaceutics 14, 4685–4693, https://doi.org/10.1021/acs.molpharmaceut.7b00775 (2017).
doi: 10.1021/acs.molpharmaceut.7b00775
pubmed: 29111754
pmcid: 5826771
Colas, C., Smith, D. E. & Schlessinger, A. Computing Substrate Selectivity in a Peptide Transporter. Cell Chem Biol 23, 211–213, https://doi.org/10.1016/j.chembiol.2016.02.001 (2016).
doi: 10.1016/j.chembiol.2016.02.001
pubmed: 26971872
pmcid: 5457801
Samsudin, F. et al. Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter. Cell Chemical Biology 23, 299–309, https://doi.org/10.1016/j.chembiol.2015.11.015 .
Navratna, V. & Gouaux, E. Insights into the mechanism and pharmacology of neurotransmitter sodium symporters. Current opinion in structural biology 54, 161–170, https://doi.org/10.1016/j.sbi.2019.03.011 (2019).
doi: 10.1016/j.sbi.2019.03.011
pubmed: 30921707
pmcid: 6592764
Bismuth, Y., Kavanaugh, M. P. & Kanner, B. I. Tyrosine 140 of the gamma-aminobutyric acid transporter GAT-1 plays a critical role in neurotransmitter recognition. The Journal of biological chemistry 272, 16096–16102, https://doi.org/10.1074/jbc.272.26.16096 (1997).
doi: 10.1074/jbc.272.26.16096
pubmed: 9195904
Colas, C., Pajor, A. M. & Schlessinger, A. Structure-Based Identification of Inhibitors for the SLC13 Family of Na(+)/Dicarboxylate Cotransporters. Biochemistry 54, 4900–4908, https://doi.org/10.1021/acs.biochem.5b00388 (2015).
doi: 10.1021/acs.biochem.5b00388
pubmed: 26176240
pmcid: 4781755
Newstead, S. et al. Crystal structure of a prokaryotic homologue of the mammalian oligopeptide-proton symporters, PepT1 and PepT2. Embo J 30, 417–426, https://doi.org/10.1038/emboj.2010.309 (2011).
doi: 10.1038/emboj.2010.309
pubmed: 21131908
Kuhlbrandt, W. Biochemistry. The resolution revolution. Science 343, 1443–1444, https://doi.org/10.1126/science.1251652 (2014).
doi: 10.1126/science.1251652
pubmed: 24675944
Ceska, T., Chung, C. W., Cooke, R., Phillips, C. & Williams, P. A. Cryo-EM in drug discovery. Biochemical Society transactions 47, 281–293, https://doi.org/10.1042/BST20180267 (2019).
doi: 10.1042/BST20180267
pubmed: 30647139
Yamashita, A., Singh, S. K., Kawate, T., Jin, Y. & Gouaux, E. Crystal structure of a bacterial homologue of Na+/Cl−-dependent neurotransmitter transporters. Nature 437, 215–223 (2005).
doi: 10.1038/nature03978
Pei, J., Kim, B. H. & Grishin, N. V. PROMALS3D: a tool for multiple protein sequence and structure alignments. Nucleic acids research 36, 2295–2300, https://doi.org/10.1093/nar/gkn072 (2008).
doi: 10.1093/nar/gkn072
pubmed: 18287115
pmcid: 2367709
Cooley, R. B., Arp, D. J. & Karplus, P. A. Evolutionary origin of a secondary structure: pi-helices as cryptic but widespread insertional variations of alpha-helices that enhance protein functionality. Journal of molecular biology 404, 232–246, https://doi.org/10.1016/j.jmb.2010.09.034 (2010).
doi: 10.1016/j.jmb.2010.09.034
pubmed: 20888342
pmcid: 2981643
Eswar, N. et al. Comparative protein structure modeling using Modeller. Curr Protoc Bioinformatics Chapter 5, Unit 5 6, https://doi.org/10.1002/0471250953.bi0506s15 (2006).
Fiser, A., Do, R. K. & Sali, A. Modeling of loops in protein structures. Protein science: a publication of the Protein. Society 9, 1753–1773, https://doi.org/10.1110/ps.9.9.1753 (2000).
doi: 10.1110/ps.9.9.1753
Ray, A., Lindahl, E. & Wallner, B. Model quality assessment for membrane proteins. Bioinformatics 26, 3067–3074, https://doi.org/10.1093/bioinformatics/btq581 (2010).
doi: 10.1093/bioinformatics/btq581
pubmed: 20947525
Laskowski, R. A., MacArthur, M. W., Moss, D. S. & Thornton, J. M. PROCHECK: a program to check the stereochemical quality of protein structures. Journal of Applied Crystallography 26, 283–291, https://doi.org/10.1107/S0021889892009944 (1993).
doi: 10.1107/S0021889892009944
Schrödinger, R.-. M, Schrödinger, LLC, New York, NY (2019).
Schrödinger, R.-. Protein Preparation Wizard; Epik, Schrödinger, LLC, New York, NY, 2016; Impact, Schrödinger, LLC, New York, NY, 2016; Prime, Schrödinger, LLC, New York, NY (2019).
Schrödinger, R.-. Ligprep, Schrödinger, LLC, New York, NY (2019).
Schrödinger, R.-. Induced Fit Docking protocol; Glide, Schrödinger, LLC, New York, NY, 2016; Prime, Schrödinger, LLC, New York, NY, 2019.
Friesner, R. A. et al. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. Journal of medicinal chemistry 47, 1739–1749, https://doi.org/10.1021/jm0306430 (2004).
doi: 10.1021/jm0306430
pubmed: 15027865
Li, J. et al. The VSGB 2.0 model: a next generation energy model for high resolution protein structure modeling. Proteins 79, 2794–2812, https://doi.org/10.1002/prot.23106 (2011).
doi: 10.1002/prot.23106
pubmed: 21905107
pmcid: 3206729
Schrodinger, L. L. C. The PyMOL Molecular Graphics System, Version 2.2.
Clamp, M., Cuff, J., Searle, S. M. & Barton, G. J. The Jalview Java alignment editor. Bioinformatics 20, 426–427, https://doi.org/10.1093/bioinformatics/btg430 (2004).
doi: 10.1093/bioinformatics/btg430
pubmed: 14960472
Durrant, J. D., Votapka, L., Sorensen, J. & Amaro, R. E. POVME 2.0: An Enhanced Tool for Determining Pocket Shape and Volume Characteristics. Journal of chemical theory and computation 10, 5047–5056, https://doi.org/10.1021/ct500381c (2014).
doi: 10.1021/ct500381c
pubmed: 25400521
pmcid: 4230373
Dai, W., Vinnakota, S., Qian, X., Kunze, D. L. & Sarkar, H. K. Molecular characterization of the human CRT-1 creatine transporter expressed in Xenopus oocytes. Archives of biochemistry and biophysics 361, 75–84, https://doi.org/10.1006/abbi.1998.0959 (1999).
doi: 10.1006/abbi.1998.0959
pubmed: 9882430
Al-Khawaja, A. et al. Pharmacological Characterization of [(3)H]ATPCA as a Substrate for Studying the Functional Role of the Betaine/GABA Transporter 1 and the Creatine Transporter. ACS chemical neuroscience 9, 545–554, https://doi.org/10.1021/acschemneuro.7b00351 (2018).
doi: 10.1021/acschemneuro.7b00351
pubmed: 29131576
Dodd, J. R., Birch, N. P., Waldvogel, H. J. & Christie, D. L. Functional and immunocytochemical characterization of the creatine transporter in rat hippocampal neurons. Journal of neurochemistry 115, 684–693, https://doi.org/10.1111/j.1471-4159.2010.06957.x (2010).
doi: 10.1111/j.1471-4159.2010.06957.x
pubmed: 20731764