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Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1573-4064
ISSN (Online): 1875-6638

Research Article

Structure-Based Virtual Screening to Identify Negative Allosteric Modulators of NMDA

Author(s): Zaid Anis Sherwani, Ruqaiya Khalil, Mohammad Nur-e-Alam, Sarfaraz Ahmed and Zaheer Ul-Haq*

Volume 18, Issue 9, 2022

Published on: 17 May, 2022

Page: [990 - 1000] Pages: 11

DOI: 10.2174/1573406418666220304224150

Price: $65

Abstract

Background: NMDA (N-methyl-D-aspartate) receptor is one of the ionotropic receptor subtypes of glutamate, the most abundant excitatory neurotransmitter in the human brain. Besides physiological roles in learning and memory, neuronal plasticity and somatosensory function NMDAR overstimulation are also implicated in a pathophysiological mechanism of ‘excitotoxicity.’ In this study, an allosteric site has been focused on to design inhibitors of the most abundant form of this receptor of utility in many acute (stroke, traumatic brain injury) and chronic neurodegenerative diseases such as Parkinson’s disease, Huntington’s, Alzheimer’s, and others.

Methods: In order to target this specific site at the interdimer interface of the ligand-binding domain of GluN2A-containing NMDA-Rs, blood-brain barrier-permeable potentially therapeutic compounds, as opposed to only pharmacological tools currently available, were sought. Pharmacophorebased virtual screening, docking, computational ADME prediction techniques, and MD simulation studies were used.

Results: Proceeding through the in-silico methodology, the study was successful at reaching 5 compounds from ChEMBL Database, which were predicted to be potential NMDA inhibitor drugs.

Conclusion: The products of the study are compounds that have been validated through pharmacophore and score-based screening and MD simulation techniques to be allosterically inhibiting NMDA receptors and with favorable pharmacokinetic profiles. They are likely to be therapeutic agents ready for in-vitro and in-vivo testing.

Keywords: NMDA, ADME, excitotoxicity, MD simulations, virtual screening, inhibitor drugs, neurotransmitter.

Graphical Abstract

[1]
Leyrer-Jackson, J.M.; Olive, M.F.; Gipson, C.D. Whole-cell patch-clamp electrophysiology to study ionotropic glutama-tergic receptors and their roles in addiction. Methods Mol. Biol., 2019, 1941, 107-135.
[http://dx.doi.org/10.1007/978-1-4939-9077-1_9]
[2]
Meldrum, B.S. Glutamate as a neurotransmitter in the brain: Review of physiology and pathology. J. Nutr., 2000, 130(Suppl. 4), 1007S-1015S.
[http://dx.doi.org/10.1093/jn/130.4.1007S] [PMID: 10736372]
[3]
Gu, Q.; Wang, C. The NMDA receptors: Physiology and neu-rotoxicity in the developing brain. In: Handbook of Develop-mental Neurotoxicology; Slikker, W.; Paule, M.G.; Wang, C., Eds.; Elsevier: Amsterdam, 2018; pp. 207-214.
[http://dx.doi.org/10.1016/B978-0-12-809405-1.00018-3]
[4]
Liu, Z.Y.; Zhong, Q.W.; Tian, C.N.; Ma, H.M.; Yu, J.J.; Hu, S. NMDA receptor-driven calcium influx promotes ischemic human cardiomyocyte apoptosis through a p38 MAPK-mediated mechanism. J. Cell. Biochem., 2019, 120(4), 4872-4882.
[http://dx.doi.org/10.1002/jcb.27702] [PMID: 30614047]
[5]
Sucher, N.J.; Awobuluyi, M.; Choi, Y-B.; Lipton, S.A. NMDA receptors: From genes to channels. Trends Pharmacol. Sci., 1996, 17(10), 348-355.
[http://dx.doi.org/10.1016/S0165-6147(96)80008-3] [PMID: 8979769]
[6]
Jalali-Yazdi, F.; Gouaux, E. NMDA Receptors’ structural asymmetry. Microsc. Microanal., 2019, 25(Suppl. 2), 1218-1219.
[http://dx.doi.org/10.1017/S1431927619006822] [PMID: 32025192]
[7]
Hu, R.; Chen, J.; Lujan, B.; Lei, R.; Zhang, M.; Wang, Z.; Liao, M.; Li, Z.; Wan, Y.; Liu, F.; Feng, H.; Wan, Q. Glycine triggers a non-ionotropic activity of GluN2A-containing NMDA receptors to confer neuroprotection. Sci. Rep., 2016, 6, 34459.
[http://dx.doi.org/10.1038/srep34459] [PMID: 27694970]
[8]
Li, V.; Wang, Y.T. Molecular mechanisms of NMDA recep-tor-mediated excitotoxicity: implications for neuroprotective therapeutics for stroke. Neural Regen. Res., 2016, 11(11), 1752-1753.
[http://dx.doi.org/10.4103/1673-5374.194713] [PMID: 28123410]
[9]
Wu, Q.J.; Tymianski, M. Targeting NMDA receptors in stroke: New hope in neuroprotection. Mol. Brain, 2018, 11(1), 15.
[http://dx.doi.org/10.1186/s13041-018-0357-8] [PMID: 29534733]
[10]
Akgül, G.; McBain, C.J. Diverse roles for ionotropic glutamate receptors on inhibitory interneurons in developing and adult brain. J. Physiol., 2016, 594(19), 5471-5490.
[http://dx.doi.org/10.1113/JP271764] [PMID: 26918438]
[11]
Rosini, M.; Simoni, E.; Caporaso, R.; Basagni, F.; Catanzaro, M.; Abu, I.F.; Fagiani, F.; Fusco, F.; Masuzzo, S.; Albani, D.; Lanni, C.; Mellor, I.R.; Minarini, A. Merging memantine and ferulic acid to probe connections between NMDA receptors, oxidative stress and amyloid-β peptide in Alzheimer’s dis-ease. Eur. J. Med. Chem., 2019, 180, 111-120.
[http://dx.doi.org/10.1016/j.ejmech.2019.07.011] [PMID: 31301562]
[12]
Zhou, H.; Clapham, D.E. Mammalian MagT1 and TUSC3 are required for cellular magnesium uptake and vertebrate em-bryonic development. Proc. Natl. Acad. Sci. USA, 2009, 106(37), 15750-15755.
[http://dx.doi.org/10.1073/pnas.0908332106] [PMID: 19717468]
[13]
Magi, S. Intracellular calcium dysregulation: Implications for Alzheimer’s disease. BioMed Res. Int., 2016, 2016, 6701324.
[14]
Heine, M.; Heck, J.; Ciuraszkiewicz, A.; Bikbaev, A. Dynamic compartmentalization of calcium channel signalling in neu-rons. Neuropharmacology, 2020, 169, 107556.
[PMID: 30851307]
[15]
Kumar, V.; Abbas, A.K.; Fausto, N.; Aster, J.C. Robbins and Cotran Pathologic Basis of Disease; Elsevier Health Sciences: Amsterdam, The Netherland, 2014.
[16]
Brooks, H.; Barrett, E.K.; Boitano, S.; Barman, M.S. Ga-nong’s Review of Medical Physiology, 25th ed; McGraw Hill Education: New York, USA, 2015.
[17]
Zanos, P.; Gould, T.D. Mechanisms of ketamine action as an antidepressant. Mol. Psychiatry, 2018, 23(4), 801-811.
[http://dx.doi.org/10.1038/mp.2017.255] [PMID: 29532791]
[18]
Carvajal, F.J.; Mattison, H.A.; Cerpa, W. Role of NMDA re-ceptor-mediated glutamatergic signaling in chronic and acute neuropathologies. Neural Plast., 2016, 2016, 2701526.
[http://dx.doi.org/10.1155/2016/2701526]
[19]
Abdallah, C.G.; Adams, T.G.; Kelmendi, B.; Esterlis, I.; Sanacora, G.; Krystal, J.H. Ketamine’s mechanism of action: A path to rapid-acting antidepressants. Depress. Anxiety, 2016, 33(8), 689-697.
[http://dx.doi.org/10.1002/da.22501] [PMID: 27062302]
[20]
Zhu, S.; Paoletti, P. Allosteric modulators of NMDA recep-tors: Multiple sites and mechanisms. Curr. Opin. Pharmacol., 2015, 20, 14-23.
[http://dx.doi.org/10.1016/j.coph.2014.10.009] [PMID: 25462287]
[21]
Folch, J.; Busquets, O.; Ettcheto, M.; Sánchez-López, E.; Castro-Torres, R.D.; Verdaguer, E.; Garcia, M.L.; Olloquequi, J.; Casadesús, G.; Beas-Zarate, C.; Pelegri, C.; Vilaplana, J.; Auladell, C.; Camins, A. Memantine for the treatment of de-mentia: A review on its current and future applications. J. Alzheimers Dis., 2018, 62(3), 1223-1240.
[http://dx.doi.org/10.3233/JAD-170672] [PMID: 29254093]
[22]
Monaghan, D.T.; Irvine, M.W.; Costa, B.M.; Fang, G.; Jane, D.E. Pharmacological modulation of NMDA receptor activity and the advent of negative and positive allosteric modulators. Article, 2012, 61(4), 581-592.
[http://dx.doi.org/10.1016/j.neuint.2012.01.004] [PMID: 22269804]
[23]
Burger, P.B. Mapping the binding of GluN2B-selective NMDA receptor negative allosteric modulators. Mol. Pharmacol., 2012, 82(2), 344-359.
[24]
Buemi, M.R.; De Luca, L.; Ferro, S.; Russo, E.; De Sarro, G.; Gitto, R. Structure-guided design of new indoles as Negative Allosteric Modulators (NAMs) of N-Methyl-D-Aspartate Re-ceptor (NMDAR) containing GluN2B subunit. Bioorg. Med. Chem., 2016, 24(7), 1513-1519.
[http://dx.doi.org/10.1016/j.bmc.2016.02.021] [PMID: 26912202]
[25]
Katzman, B.M.; Perszyk, R.E.; Yuan, H.; Tahirovic, Y.A.; Sotimehin, A.E.; Traynelis, S.F.; Liotta, D.C. A novel class of negative allosteric modulators of NMDA receptor function. Bioorg. Med. Chem. Lett., 2015, 25(23), 5583-5588.
[http://dx.doi.org/10.1016/j.bmcl.2015.10.046] [PMID: 26525866]
[26]
Tajima, N.; Karakas, E.; Grant, T.; Simorowski, N.; Diaz-Avalos, R.; Grigorieff, N.; Furukawa, H. Activation of NMDA receptors and the mechanism of inhibition by ifenprodil. Nature, 2016, 534(7605), 63-68.
[http://dx.doi.org/10.1038/nature17679] [PMID: 27135925]
[27]
Yi, F.; Mou, T.C.; Dorsett, K.N.; Volkmann, R.A.; Menniti, F.S.; Sprang, S.R.; Hansen, K.B. Structural basis for negative allosteric modulation of GluN2A-containing NMDA recep-tors. Neuron, 2016, 91(6), 1316-1329.
[http://dx.doi.org/10.1016/j.neuron.2016.08.014] [PMID: 27618671]
[28]
Hansen, K.B.; Ogden, K.K.; Traynelis, S.F. Subunit-selective allosteric inhibition of glycine binding to NMDA receptors. J. Neurosci., 2012, 32(18), 6197-6208.
[http://dx.doi.org/10.1523/JNEUROSCI.5757-11.2012] [PMID: 22553026]
[29]
Volkmann, R.A.; Fanger, C.M.; Anderson, D.R.; Sirivolu, V.R.; Paschetto, K.; Gordon, E.; Virginio, C.; Gleyzes, M.; Buisson, B.; Steidl, E.; Mierau, S.B.; Fagiolini, M.; Menniti, F.S. MPX-004 and MPX-007: New pharmacological tools to study the physiology of NMDA receptors containing the GluN2A subunit. PLoS One, 2016, 11(2), e0148129.
[http://dx.doi.org/10.1371/journal.pone.0148129] [PMID: 26829109]
[30]
Allec, S.I.; Sun, Y.; Sun, J.; Chang, C-A.; Wong, B.M. Hetero-geneous CPU+ GPU-enabled simulations for DFTB molecular dynamics of large chemical and biological systems. J. Chem. Theory Comput., 2019, 15(5), 2807-2815.
[http://dx.doi.org/10.1021/acs.jctc.8b01239] [PMID: 30916958]
[31]
Bhattacharya, S.; Asati, V.; Mishra, M.; Das, R.; Kashaw, V.; Kashaw, S.K. Integrated computational approach on sodium-glucose co-transporter 2 (SGLT2) inhibitors for the develop-ment of novel antidiabetic agents. J. Mol. Struct., 2021, 1227, 129511.
[http://dx.doi.org/10.1016/j.molstruc.2020.129511]
[32]
Berman, H.M.; Battistuz, T.; Bhat, T.N.; Bluhm, W.F.; Bourne, P.E.; Burkhardt, K.; Feng, Z.; Gilliland, G.L.; Iype, L.; Jain, S.; Fagan, P.; Marvin, J.; Padilla, D.; Ravichandran, V.; Schneider, B.; Thanki, N.; Weissig, H.; Westbrook, J.D.; Zar-decki, C. The protein data bank. Acta Crystallogr. D Biol. Crystallogr., 2002, 58(Pt 6 No1), 899-907.
[http://dx.doi.org/10.1107/S0907444902003451] [PMID: 12037327]
[33]
Jespersen, A.; Tajima, N.; Fernandez-Cuervo, G.; Garnier-Amblard, E.C.; Furukawa, H. Structural insights into competi-tive antagonism in NMDA receptors. Neuron, 2014, 81(2), 366-378.
[http://dx.doi.org/10.1016/j.neuron.2013.11.033] [PMID: 24462099]
[34]
Schreiber, J.A.; Müller, S.L.; Westphälinger, S.E.; Schepmann, D.; Strutz-Seebohm, N.; Seebohm, G.; Wünsch, B. Systematic variation of the benzoylhydrazine moiety of the GluN2A se-lective NMDA receptor antagonist TCN-201. Eur. J. Med. Chem., 2018, 158, 259-269.
[http://dx.doi.org/10.1016/j.ejmech.2018.09.006] [PMID: 30218911]
[35]
Müller, S.L.; Schreiber, J.A.; Schepmann, D.; Strutz-Seebohm, N.; Seebohm, G.; Wünsch, B. Systematic variation of the ben-zenesulfonamide part of the GluN2A selective NMDA recep-tor antagonist TCN-201. Eur. J. Med. Chem., 2017, 129, 124-134.
[http://dx.doi.org/10.1016/j.ejmech.2017.02.018] [PMID: 28222314]
[36]
Edman, S.; McKay, S.; Macdonald, L.J.; Samadi, M.; Livesey, M.R.; Hardingham, G.E.; Wyllie, D.J. TCN 201 selectively blocks GluN2A-containing NMDARs in a GluN1 co-agonist dependent but non-competitive manner. Neuropharmacology, 2012, 63(3), 441-449.
[http://dx.doi.org/10.1016/j.neuropharm.2012.04.027] [PMID: 22579927]
[37]
Mysinger, M.M.; Carchia, M.; Irwin, J.J.; Shoichet, B.K. Di-rectory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking. J. Med. Chem., 2012, 55(14), 6582-6594.
[http://dx.doi.org/10.1021/jm300687e] [PMID: 22716043]
[38]
Irwin, J.J.; Shoichet, B.K. ZINC--a free database of commer-cially available compounds for virtual screening. J. Chem. Inf. Model., 2005, 45(1), 177-182.
[http://dx.doi.org/10.1021/ci049714+] [PMID: 15667143]
[39]
Gaulton, A.; Bellis, L.J.; Bento, A.P.; Chambers, J.; Davies, M.; Hersey, A.; Light, Y.; McGlinchey, S.; Michalovich, D.; Al-Lazikani, B.; Overington, J.P. ChEMBL: A large-scale bio-activity database for drug discovery. Nucleic Acids Res., 2012, 40, D1100-D1107.
[http://dx.doi.org/10.1093/nar/gkr777] [PMID: 21948594]
[40]
Friesner, R.A.; Banks, J.L.; Murphy, R.B.; Halgren, T.A.; Klicic, J.J.; Mainz, D.T.; Repasky, M.P.; Knoll, E.H.; Shelley, M.; Perry, J.K.; Shaw, D.E.; Francis, P.; Shenkin, P.S. Glide: A new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem., 2004, 47(7), 1739-1749.
[http://dx.doi.org/10.1021/jm0306430] [PMID: 15027865]
[41]
Trott, O.; Olson, A.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem., 2010, 31(2), 455-461.
[PMID: 19499576]
[42]
Salentin, S.; Schreiber, S.; Haupt, V.J.; Adasme, M.F.; Schroeder, M. PLIP: Fully automated protein-ligand interac-tion profiler. Nucleic Acids Res., 2015, 43(W1), W443-7.
[http://dx.doi.org/10.1093/nar/gkv315] [PMID: 25873628]
[43]
Daina, A.; Michielin, O.; Zoete, V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medici-nal chemistry friendliness of small molecules. Sci. Rep., 2017, 7, 42717.
[http://dx.doi.org/10.1038/srep42717] [PMID: 28256516]
[44]
Case, D. AMBER 2018; 2018; University of California: San Francisco, 2018.
[45]
Lindorff-Larsen, K.; Piana, S.; Palmo, K.; Maragakis, P.; Klepeis, J.L.; Dror, R.O.; Shaw, D.E. Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins, 2010, 78(8), 1950-1958.
[http://dx.doi.org/10.1002/prot.22711] [PMID: 20408171]
[46]
Wang, J.; Wolf, R.M.; Caldwell, J.W.; Kollman, P.A.; Case, D.A. Development and testing of a general amber force field. J. Comput. Chem., 2004, 25(9), 1157-1174.
[http://dx.doi.org/10.1002/jcc.20035] [PMID: 15116359]
[47]
Jorgensen, W.L.; Chandrasekhar, J.; Madura, J.D.; Impey, R.W.; Klein, M.L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys., 1983, 79(2), 926-935.
[http://dx.doi.org/10.1063/1.445869]
[48]
Kräutler, V.; Van Gunsteren, W.F.; Hünenberger, P.H. A fast SHAKE algorithm to solve distance constraint equations for small molecules in molecular dynamics simulations. J. Comput. Chem., 2001, 22(5), 501-508.
[http://dx.doi.org/10.1002/1096-987X(20010415)22:5<501:AID-JCC1021>3.0.CO;2-V]
[49]
Roe, D.R.; Cheatham, T.E. PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory da-ta. J. Chem. Theory Comput., 2013, 9(7), 3084-3095.
[http://dx.doi.org/10.1021/ct400341p] [PMID: 26583988]
[50]
Franchini, L.; Carrano, N.; Di Luca, M.; Gardoni, F. Synaptic GluN2A-containing NMDA receptors: From physiology to pathological synaptic plasticity. Int. J. Mol. Sci., 2020, 21(4), 1538.
[http://dx.doi.org/10.3390/ijms21041538] [PMID: 32102377]
[51]
Wyllie, D.J.; Livesey, M.R.; Hardingham, G.E. Influence of GluN2 subunit identity on NMDA receptor function. Neuropharmacology, 2013, 74, 4-17.
[http://dx.doi.org/10.1016/j.neuropharm.2013.01.016] [PMID: 23376022]
[52]
Sievers, F.; Wilm, A.; Dineen, D.; Gibson, T.J.; Karplus, K.; Li, W.; Lopez, R.; McWilliam, H.; Remmert, M.; Söding, J.; Thompson, J.D.; Higgins, D.G. Fast, scalable generation of high-quality protein multiple sequence alignments using Clus-tal Omega. Mol. Syst. Biol., 2011, 7(1), 539.
[http://dx.doi.org/10.1038/msb.2011.75] [PMID: 21988835]
[53]
Consortium, U. UniProt: A hub for protein information. Nucleic Acids Res., 2015, 43(Database issue), D204-D212.
[http://dx.doi.org/10.1093/nar/gku989] [PMID: 25348405]

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