Molecular Modeling Investigation of the Interaction between Humicola insolens Cutinase and SDS Surfactant Suggests a Mechanism for Enzyme Inactivation

Abstract

One of the largest commercial applications of enzymes and surfactants is as main components in modern detergents. The high concentration of surfactant compounds usually present in detergents can, however, negatively affect the enzymatic activity. To remedy this drawback, it is of great importance to characterize the interaction between the enzyme and the surfactant molecules at an atomistic resolution. The protein enzyme cutinase from the thermophilic and saprophytic fungus called Humicola insolens (HiC) is a promising candidate for use in detergents thanks to its hydrolase activity targeting mostly biopolyesters (e.g., cutin). HiC is, however, inhibited by low concentrations of sodium dodecyl sulfate (SDS), an ubiquitous surfactant. In this work, we investigate the interaction between HiC and SDS using molecular dynamics simulations. Simulations of HiC dissolved in different aqueous concentrations of SDS show the interaction between HiC and SDS monomers, as well as the formation and dynamics of SDS micelles on the surface of the enzyme. These results suggest a mechanism of cutinase inhibition by SDS, which involves the nucleation of aggregates of SDS molecules on hydrophobic patches on the cutinase surface. Notably, a primary binding site for monomeric SDS is identified near the active site of HiC constituting a possible nucleation point for micelles and leading to the blockage of the entrance to the enzymatic site. Detailed analysis of the simulations allow us to suggest a set of residues from the SDS binding site on HiC to probe as engineered mutations aimed at reducing SDS binding to HiC, thereby decreasing SDS inhibition of HiC.

Simulating Multiple Substrate-Binding Events by γ-Glutamyltransferase Using Accelerated Molecular Dynamics

“…This is a clustering method for the identification of clusters of protein residues making simultaneous contacts with a ligand through an MD trajectory. , It uses a distance metric based on the surprisal of a pair of residues to be in contact with a ligand: d ( i , j ) = −log­(( n ( i , j ) + 1)/ N ), where n ( i , j ) is the number of simultaneous contacts for residues i and j over a trajectory containing N frames. Note that d ( i , j ) ∼ 0 and d ( i , j ) = log­( N ) correspond to residues i and j always in contact with the ligand and no simultaneous contacts throughout the trajectory, respectively.…”

“…Phrases clustering analysis: This is a clustering method for the identification of clusters of protein residues making simultaneous contacts with a ligand through an MD trajectory 51,52 . It uses a distance metric based on the surprisal of a pair of residues to be in contact with a ligand:…”

A Celebration of Women in Computational Chemistry

“…The main emphasis of the work is to define the basis of interaction between the protein and SDS in order to understand how SDS may reduce its activity. The results suggest a mechanism of cutinase inhibition by SDS, which involves the nucleation of aggregates of SDS molecules on hydrophobic patches on the cutinase surface …”

Production, Purification, and Characterization of Extracellular Alkaline Protease From Bacillus Firmus Var. Arosia NCIB 10557

“…P45 [53], in both cases, the Triton X-100 acted by destabilizing the enzymatic structure. In contrast, the SDS that is cited in the literature as an enzyme inhibitor [54] stimulated protease activity (Table 2). Proteases from Bacillus safensis CK [55] and Bacillus pumilus D3 [56] in the presence of SDS also showed an increase in the values of enzyme activity, demonstrating that the inhibitor did not have a negative effect on these enzymes.…”