Mathematical models to correlate molecular topology with substrate affinity of the glycine antagonist in glutamate receptors
Keywords:
glycine/antagonists & inhibitors, glutamate, N-methylaspartate/pharmacology
Abstract
Introduction. Mathematical models that correlate chemical structure with biological activity have been useful in the design of new drugs and can be used to predict biological behavior of new, chemically related molecules.Objectives. A mathematical model was generated to correlate the substrate affinities with variations in the molecular topology of glycine antagonists in NMDA sub-class glutamate receptor and, subsequently, to propose new molecules with antagonist activity.
Materials and methods. By use of molecular connectivity indexes, the electronic structure and atomic bonding patterns of 45 glycine antagonists were coded. Correlation between connectivity indexes and antagonist affinity was determined by regression analysis.
Results. The connectivity index that best described affinity behavior was 4Xvpc, which indicates the relative importance of heteroatoms, the vicinity of aromatic ring substitutes, and valency gradient. The equations generated predicted new antagonist affinities, and the model was able to suggest structural requirements for designating compounds with increased affinity. Twelve new molecules were proposed, from which three appeared promising-based of the affinities previously calculated by means of the new equations. Energetic interaction analysis was developed as a control for the mathematical methodology.
Conclusion. Glycine antagonists' structure were analyzed mathematically by means of connectivity indexes. The equations modeled receptor behavior and contributed useful information for new antagonist design.
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References
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34. Neubig RR, Spedding M, Kenakin T, Christopoulos A. International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification. XXXVIII. Update on terms and symbols in quantitative pharmacology. Pharmacol Rev 2003;55:597-606.
2. Kitchen DB, Decornez H, Furr JR, Bajorath J. Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 2004;3:935-49.
3. Brown N, Lewis RA. Exploiting QSAR methods in lead optimization. Curr Opin Drug Discov Devel 2006;9:419-24.
4. García D, Gálves J. Topología Molecular. Su papel en el diseño de nuevos fármacos. Investigación y Ciencia 1993;197:86-7.
5. Gonzalbes R, Doucet JP, Derouin F. Application of topological descriptors in QSAR and drug design: history and new trends. Curr Drug Targets Infect Disord 2002;2:93-102.
6. Randic M. On characterization of molecular branching. J Am Chem Soc 1975;97:6609-15.
7. Kier LB, Hall LH. The meaning of molecular connectivity: A bimolecular accessibility model. Croatia Chem Acta 2002;75:371-82.
8. Hall LH, Kier LB. Issues in representation of molecular structure the development of molecular connectivity. J Mol Graph Model 2001;20:4-18.
9. Kier LB, Hall LH. Molecular connectivity in structureactivity analysis England: Research Studies Press; 1986.
10. Hall LH, Kier LB. Molecular connectivity and substructure analysis. J Pharm Sci 1978;67:1743-7.
11. Kier LB, Hall LH. General definition of valence deltavalues for molecular connectivity. J Pharm Sci 1983;72:1170-3.
12. Kier LB, Hall LH. Molecular connectivity VII: specific treatment of heteroatoms. J Pharm Sci 1976;65:1806-9.
13. Rios-Santamarina I, Garcia-Domenech R, Galvez J, Cortijo J, Santamaria P, Morcillo E. New bronchodilators selected by molecular topology. Bioorg Med Chem Lett 1998;8:477-82.
14. de Gregorio Alapont C, Garcia-Domenech R, Galvez J, Ros MJ, Wolski S, Garcia MD. Molecular topology: a useful tool for the search of new antibacterials. Bioorg Med Chem Lett 2000;10:2033-6.
15. Agrawal VK, Sohgaura R, Khadikar PV. QSAR study on inhibition of brain 3-hydroxy-anthranilic acid dioxygenase (3-HAO): a molecular connectivity approach. Bioorg Med Chem 2001;9:3295-9.
16. Bajaj S, Sambi SS, Madan AK. Topological models for prediction of anti-HIV activity of acylthiocarbamates. Bioorg Med Chem 2005;13:3263-8.
17. Garcia-Garcia A, Galvez J, de Julian-Ortiz JV, Garcia-Domenech R, Munoz C, Guna R et al. New agents active against Mycobacterium avium complex selected by molecular topology: a virtual screening
method. J Antimicrob Chemother 2004;53:65-73.
18. Dingledine R, Borges K, Bowie D, Traynelis SF. The glutamate receptor ion channels. Pharmacol Rev 1999;51:7-61.
19. Candy S, Brickley S, Farrant M. NMDA receptor subunits: Diversity, development and disease. Curr Opin Neurobiol 2001;11:327-35.
20. Popescu G, Auerbach A. The NMDA receptor gating machine: lessons from single channels. Neuroscientist 2004;10:192-8.
21. Yun L, Juntian Z. Recent development in NMDA receptors. Chinese Med J 2000;113:948-56.
22. Kemp JA, McKernan RM. NMDA receptor pathways as drug targets. Nat Neurosci 2002;5(Suppl):1039-42.
23. Yosa J. Desarrollo y validación de un modelo para identificar factores que definen el tipo de acción de un ligando. Trabajo de grado (Magíster en Ciencias biológicas). Bogotá D.C.: Facultad de Ciencias, Pontificia Universidad Javeriana; 2005.
24. Leeson PD, Iversen LL. The glycine site on the NMDA receptor: structure-activity relationships and therapeutic potential. J Med Chem 1994;37:4053-67.
25. Danysz W, Parsons AC. Glycine and N-methyl-Daspartate receptors: physiological significance and possible therapeutic applications. Pharmacol Rev 1998;50:597-664.
26. Brown DG, Urbanek RA, Bare TM, McLaren FM, Horchler CL, Murphy M et al. Synthesis of 7-chloro-2,3-dihydro-2-[1-(pyridinyl)alkyl]-pyridazino[4,5-b]quinoline-1,4,10(5H)-triones as NMDA glycine-site
antagonists. Bioorg Med Chem Lett 2003;13:3553-6.
27. Furukawa H, Gouaux E. Mechanisms of activation, inhibition and specificity: crystal structures of the NMDA receptor NR1 ligand-binding core. Embo J 2003;22:2873-85.
28. RCSB Protein Data Bank. Crystal structure of the NR1 ligand binding core in complex with 5,7-dichlorokynurenic acid (DCKA) at 1.90 angstroms resolution. [Consultado: Mayo 27 de 2005]. Disponible en http://www.rcsb.org/pdb/explore/explore.do?structureId=1PBQ
29. Thompson M. ArgusLab version 4.0.1.. Seattle, WA: Planaria Software; 2004. [Consultado: mayo 27 de 2005] Disponible en http:// http://www.planaria-software.com/arguslab40.htm
30. Cai SX, Kher SM, Zhou ZL, Ilyin V, Espitia SA, Tran M et al. Structure-activity relationships of alkyl- and alkoxy-substituted 1,4-dihydroquinoxaline-2,3-diones: potent and systemically active antagonists for the glycine site of the NMDA receptor. J Med Chem 1997;40:730-8.
31. Cai SX, Zhou ZL, Huang JC, Whittemore ER, Egbuwoku ZO, Lu Y et al. Synthesis and structureactivity relationships of 1,2,3,4-tetrahydroquinoline-2,3,4-trione 3-oximes: novel and highly potent antagonists for NMDA receptor glycine site. J Med Chem 1996;39:3248-55.
32. Zhou ZL, Kher SM, Cai SX, Whittemore ER, Espitia SA, Hawkinson JE et al. Synthesis and SAR of novel di- and trisubstituted 1,4-dihydroquinoxaline-2,3-diones related to licostinel (Acea 1021) as NMDA/glycine site antagonists. Bioorg Med Chem 2003;11:1769-80.
33. Tikhonova IG, Baskin, II, Palyulin VA, Zefirov NS. CoMFA and homology-based models of the glycine binding site of N-methyl-d-aspartate receptor. J Med Chem 2003;46:1609-16.
34. Neubig RR, Spedding M, Kenakin T, Christopoulos A. International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification. XXXVIII. Update on terms and symbols in quantitative pharmacology. Pharmacol Rev 2003;55:597-606.
How to Cite
1.
Narváez G, Lareo L, Rincón J. Mathematical models to correlate molecular topology with substrate affinity of the glycine antagonist in glutamate receptors. biomedica [Internet]. 2007 Mar. 1 [cited 2024 May 16];27(1):116-32. Available from: https://revistabiomedica.org/index.php/biomedica/article/view/238
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Published
2007-03-01
Issue
Section
Original articles
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