Multispectroscopic and Computational Analysis Insight into the Interaction of Cationic Diester-Bonded Gemini Surfactants with Serine Protease α-Chymotrypsin

Abstract

Accumulation of different protein–surfactant mixtures affords further knowledge about the structure–property interactions of biomacromolecules. They will help design suitable surfactants, which, in turn, can enhance the utilization of protein–surfactant complexes in biotechnologies, cosmetics, and food industry realms. Owing to their adaptable and remarkably notable properties, we are describing herein the interaction of C m -E2O-C m gemini surfactants (m = 12, 14, and 16) with α-CHT by employing various spectroscopic techniques including with molecular docking and density functional theory (DFT) method. Results have revealed complex formation, unfolding, and a static quenching mechanism in the interaction of gemini surfactants with α-CHT. The Stern–Volmer constant (K SV), quenching constant (k q), the number of binding sites (n), and binding constant (K b) were interrogated by utilizing the fluorescence quenching method, UV–vis, synchronous, 3-D, and resonance Rayleigh scattering fluorescence studies. The data perceive the α-CHT–C m -E2O-C m complex formation along with conformational alterations induced in α-CHT. The contribution of aromatic residues to a nonpolar environment is illustrated by pyrene fluorescence. Fourier transform infrared spectroscopy and circular dichroism outcomes reveal conformational modifications in the secondary structure of α-CHT with the permutation of gemini surfactants. The computational calculations (molecular docking and DFT) further corroborate the complex formation between α-CHT and C m -E2O-C m gemini surfactants and the contribution of electrostatic/hydrophobic interaction forces therein.

Enhancing the Antipsychotic Effect of Risperidone by Increasing Its Binding Affinity to Serotonin Receptor via Picric Acid: A Molecular Dynamics Simulation

“…Analysis of the best-docked pose of [(Ris) (PA)]-serotonin revealed that the amino acid residues, including His182, Asn187, Asn384, Lys320, and Arg173, formed hydrogen bond interactions. In addition, Leu325, Ala321, Ala108, and Ala176 established π-alkyl interactions while Asp172 formed a halogen (fluorine) interaction [ 27 , 28 ]. The best-docked pose of [(Ris) (PA)]-dopamine revealed that the amino acid residues, including Thr142, Ala185, His393, and Tyr408, formed hydrogen bond interactions, Val115 and Phe389 established π-alkyl interactions, Trp386 established π-sigma, and Cys118 formed a halogen (fluorine) interaction [ 29 , 30 ].…”

Enhancement of Haloperidol Binding Affinity to Dopamine Receptor via Forming a Charge-Transfer Complex with Picric Acid and 7,7,8,8-Tetracyanoquinodimethane for Improvement of the Antipsychotic Efficacy

“…As shown in Figure 5 a, CT complex [(HPL)(TCNQ)] with dopamine (CTtD) revealed that the amino acid residues, including His393, Ser193, and Tyr416, formed hydrogen bond interactions. Additionally, Val91 and Trp413 (π-Alkyl); Tyr408 (π-π T-Shaped); Cys118 (π-Alkyl); Thr412 and Leu94 (π-Sigma); and Asp114 (Attractive charge) interactions were present [ 15 , 16 ].…”

Increasing the Efficacy of Seproxetine as an Antidepressant Using Charge–Transfer Complexes

“…The Coats-Readfern and Horowitez-Metzegar methods [ 55 , 56 ] were used to collect the kinetic thermodynamic data of the maximal DTG peak decomposition steps of all charge–transfer complexes. The kinetic parameters, E , A , Δ S , Δ H , Δ G , and r were calculated, and the data are listed in Table 1 and displayed in Figure 4 .…”