A general framework improving teaching ligand binding to a macromolecule.

Jacques Haiech, Yves Gendrault, Marie-Claude Kilhoffer, Raoul Ranjeva, Morgan Madec, Christophe Lallement

Journal: Biochimica et biophysica acta 2014;1843(10):2348-55

PMID: 24657812

Abstract

The interaction of a ligand with a macromolecule has been modeled following different theories. The tenants of the induced fit model consider that upon ligand binding, the protein-ligand complex undergoes a conformational change. In contrast, the allosteric model assumes that only one among different coexisting conformers of a given protein is suitable to bind the ligand optimally. In the present paper, we propose a general framework to model the binding of ligands to a macromolecule. Such framework built on the binding polynomial allows opening new ways to teach in a unified manner ligand binding, enzymology and receptor binding in pharmacology. Moreover, we have developed simple software that allows building the binding polynomial from the schematic description of the biological system under study. Taking calmodulin as a canonical example, we show here that the proposed tool allows the easy retrieval of previously experimental and computational reports. This article is part of a Special Issue entitled: Calcium Signaling in Health and Disease. Guest Editors: Geert Bultynck, Jacques Haiech, Claus W. Heizmann, Joachim Krebs, and Marc Moreau.

Copyright © 2014. Published by Elsevier B.V.

Address: LIT, Therapeutic Innovation Laboratory, UMR7200 CNRS, University of Strasbourg, Faculty of Pharmacy, Illkirch, France. Electronic address: [email protected].; ICube, Engineering, Computer and Imaging Science Laboratory, UMR7357 CNRS, University of Strasbourg, Telecom - Strasbourg, France.; LIT, Therapeutic Innovation Laboratory, UMR7200 CNRS, University of Strasbourg, Faculty of Pharmacy, Illkirch, France.

Link outs

Bant logo

© Copyright 2026, Nutrition Evidence

NED wishes to thank the following organisations for their support:

We use cookies to improve your experience and analyze site traffic with Google Analytics. By continuing to use our site, you agree to our use of cookies. Learn more.