headerpos: 12198
 
 
 

Proceedings of the Estonian Academy of Sciences

ISSN 1736-7530 (electronic)   ISSN 1736-6046 (print)
Formerly: Proceedings of the Estonian Academy of Sciences, series Physics & Mathematics and  Chemistry
Published since 1952

Proceedings of the Estonian Academy of Sciences

ISSN 1736-7530 (electronic)   ISSN 1736-6046 (print)
Formerly: Proceedings of the Estonian Academy of Sciences, series Physics & Mathematics and  Chemistry
Published since 1952
Publisher
Journal Information
» Editorial Board
» Editorial Policy
» Archival Policy
» Article Publication Charges
» Copyright and Licensing Policy
Guidelines for Authors
» For Authors
» Instructions to Authors
» LaTex style files
Guidelines for Reviewers
» For Reviewers
» Review Form
Open Access
List of Issues
» 2019
» 2018
» 2017
Vol. 66, Issue 4
Vol. 66, Issue 3
Vol. 66, Issue 2
Vol. 66, Issue 1
» 2016
» 2015
» 2014
» 2013
» 2012
» 2011
» 2010
» 2009
» 2008
» Back Issues Phys. Math.
» Back Issues Chemistry
» Back issues (full texts)
  in Google. Phys. Math.
» Back issues (full texts)
  in Google. Chemistry
» Back issues (full texts)
  in Google Engineering
» Back issues (full texts)
  in Google Ecology
» Back issues in ETERA Füüsika, Matemaatika jt
Subscription Information
» Prices
Internet Links
Support & Contact
Publisher
» Staff
» Other journals

Kinetic tools for the identification of ligand–receptor interaction mechanisms; pp 202–213

(Full article in PDF format) https://doi.org/10.3176/proc.2017.2.08


Authors

Siim Kukk, Peep Miidla, Jaak Järv

Abstract

Tools for the identification of receptor–ligand interaction mechanisms were developed by mathematical modeling of the influence of a ligand on the kinetics of a reporter ligand binding with a receptor. This approach allows kinetic differentiation between ligands of both rapid and slow binding modes, but also distinguishes compounds that share the same binding site with the reporter ligand or bind non-competitively to a distinct binding site. In order to simulate the kinetic behavior of this system, a mathematical model comprising ordinary differential equations was derived and solved numerically.

Keywords

ligand binding kinetics, receptor–ligand complex isomerization, drug residence time, mathematical modeling.

References

1. Strickland , S. , Palmer , G. , and Massey , V. Determination of dissociation constants and specific rate constants of enzyme–substrate (or protein–ligand) interactions from rapid reaction kinetic data. J. Biol. Chem. 1975 , 250(11) , 4048–4052.

2. Guo , D. , Hillger , J. M. , Ijzerman , A , P , and Heitman , L. H. Drug-target residence time – a case for G protein-coupled receptors. Med. Res. Rev. , 2014 , 34(4) , 856–892.
https://doi.org/10.1002/med.21307

3. Copeland , R. A. The drug-target residence time model: a 10-year retrospective. Nat. Rev. Drug Discov. , 2016 , 15(2) , 87–95.

https://doi.org/10.1038/nrd.2015.18

4. Järv , J. , Hedlund , B. , and Bartfai , T. Isomerization of the muscarinic receptor . antagonist complex. J. Biol. Chem. , 1979 , 254(13) , 5595–5598.

5. Dowling , M. R. and Charlton , S. J. Quantifying the association and dissociation rates of unlabelled antagonists at the muscarinic M3 receptor. Br. J. Pharmacol. , 2006 , 148 , 927–937.
https://doi.org/10.1038/sj.bjp.0706819

6. Schliebs , R. and Bigl , V. Kinetics of the interaction of dihydroalprenolol with beta-adrenergic receptors in rat cerebral-cortex. Gen. Physiol. Biophys. , 1984 , 3(1) , 31–46.

7. Lepiku , M. , Rinken , A. , Järv , J. , and Fuxe , K. Kinetic evidence for isomerization of the dopamine receptor-raclopride complex. Neurochem. Int. , 1996 , 28(5–6) , 591–595.
https://doi.org/10.1016/0197-0186(95)00123-9

8. Oras , A. and Järv , J. Kinetics of [35S]dATPaS interaction with P2Y1 purinoceptor in rat brain membranes. Neurosci Lett. , 2004 , 355 , 9–12.
https://doi.org/10.1016/j.neulet.2003.10.029

9. Stepanov , V. and Järv , J. Slow isomerization step in the interaction between mouse dopamine transporter and dopamine re-uptake inhibitor N-(3-iodoprop-2E-enyl)-2β-carbo-[3H]methoxy-3β-(4'-methylphenyl)nortropane. Neurosci Lett. , 2006 , 410(3) , 218–221.
https://doi.org/10.1016/j.neulet.2006.10.007

10. Kukk , S. and Järv , J. Differentiating between drugs with short and long residence times. MedChemComm , 2016 , 7(8) , 1654–1656.
https://doi.org/10.1039/C6MD00269B

11. Järv , J. , Hedlund , B. , and Bartfai , T. Kinetic studies on muscarinic antagonist-agonist competition. J. Biol. Chem. , 1980 , 255(7) , 2649–2651.

12. Cheng , Y-C. and Prusoff , W. H. Relationship between the inhibition constant (Ki) and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an enzymatic reaction. Biochem. Pharmacol. , 1973 , 22 , 3099–3108.
https://doi.org/10.1016/0006-2952(73)90196-2

13. Motulsky , H. J. and Mahan , L. C. The kinetics of competitive radioligand binding predicted by the law of mass action. Mol. Pharmacol. ASPET , 1984 , 25(1) , 1–9.

14. Wanant , S. and Quon , M. J. Insulin receptor binding kinetics: Modeling and simulation studies. J. Theor. Biol. , 2000 , 205(3) , 355–364.
https://doi.org/10.1006/jtbi.2000.2069

15. Wittmann , H.-J. and Strasser , A. Competitive association binding kinetic assays: a new tool to detect two different binding orientations of a ligand to its target protein under distinct conditions? Naunyn Schmiedebergs Arch. Pharmacol. , 2017 , 1–18.
https://doi.org/10.1007/s00210-017-1362-7

 
Back

Current Issue: Vol. 68, Issue 3, 2019




Publishing schedule:
No. 1: 20 March
No. 2: 20 June
No. 3: 20 September
No. 4: 20 December