Investigation into the site-specific binding interactions between chlorogenic acid and ovalbumin using multi-spectroscopic and in silico simulation studies

Abstract

The binding interactions of bioactive compounds with proteins are of great importance in the food, biochemistry and pharmaceutical fields. Herein, the binding mechanisms between 5-O-caffeoylquinic acid (5-CQA) and ovalbumin (OVA) were investigated by multi-spectroscopic studies combined with docking and molecular dynamics (MD) simulations. The emission intensity of OVA was quenched by 5-CQA and Stern-Volmer analysis indicated the existence of a static suppression by OVA–5-CQA complex formation. Thermodynamic parameters revealed that the formation of complex was spontaneously driven by electrostatic and hydrogen-bonding interactions. Circle dichroism analyses showed that 5-CQA decreased the α-helix content of OVA structure from 58.05% to 54.32% upon increased OVA:5-CQA ratio to 1:3. Molecular docking results suggested 5-CQA forms hydrogen bond interactions with N88, T91, K92, N94, S98, F99, S100 and L101 residues of OVA. The experimental values were in good agreement with the calculated binding free energy values obtained by MD simulation (R² = 0.89).

Communicated by Ramaswamy H. Sarma

Keywords:

• 5-O-caffeoylquinic acid
• ovalbumin
• multi-spectroscopy
• molecular docking
• molecular dynamics simulation

Author contribution statement

P. Manivel: Conceptualization, Methodology, Data curation, Writing-Original draft preparation and Editing, P.Marimuthu: insilico Studies and Analysis, Visualization and Investigation, X. Chen: Conceptualization, Funding acquisition, Reviewing and Editing.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

This study was supported by Jiangsu Specially-Appointed Professor Program (19TPJS-002) and Senior Talent Startup Fund of Jiangsu University (4111360002) to X. Chen. P. Manivel acknowledges the China Postdoctoral Science Foundation and Jiangsu University for the financial Support. Parthiban, M. gratefully acknowledges the use of the bioinformatics infrastructure facility supported by Biocenter Finland, grants from the Joe, Pentti and Tor Borg Memorial Fund in 2020, the Sigrid Juselius Foundation and the CSC-IT Center for Science (Project: 2000461) for the computational facility; Dr. Jukka Lehtonen for the IT support; Prof. Mark Johnson (SBL) and Prof. Outi Salo-Ahen (Pharmacy) Åbo Akademi University for providing the lab support.