126
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Determining the stoichiometry and binding constant of Lamotrigine with human serum albumin using voltammetry analysis and molecular modeling

, , , , , & show all
Pages 10117-10124 | Received 12 Sep 2022, Accepted 24 Nov 2022, Published online: 07 Dec 2022
 

Abstract

In this study, the interaction of an anticonvulsant drug that used in the treatment of epilepsy, Lamotrigine (LTG) with the most important transport protein of the blood, human serum albumin (HSA) has been studied by using the electrochemical methods and molecular modeling techniques. For this purpose, a simple carbon paste electrode (CPE) was applied for electrocatalytic oxidation and investigation of LTG interaction with HSA. The stoichiometry of the complex between LTG and HSA and the binding constant (Kb) of the reaction were calculated from the calibration curves. The results show that binding of LTG to HSA formed two complexes with different stoichiometries with Kb1 (2.46 × 103) and Kb2 (1.75 × 107), respectively. In agreement with the experimental data, molecular modeling approach also confirmed that LTG can bind to the subdomain IIA and IB of HSA.

Communicated by Ramaswamy H. Sarma

Acknowledgments

The authors gratefully acknowledge Kermanshah University of Medical Sciences for financial support (Grant No. 400447)

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,074.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.