QSAR Analysis of the Effect of Metal Ions on the Peptidase Bacillus thuringiensis var. israelensis IMV B-7465 Activity

Abstract

Background. The catalytic activity of enzymes, which is their most important characteristic, can change significantly under the influence of effectors, for example, metal ions, and is the subject of special studies that are important for biochemistry, biotechnology, medicine, and other branches of science. Usually, the activity of enzymes in the presence of metals is assessed by the change in the rate of the enzymatic reaction. However, conducting such experimental studies, especially for new enzymes, as in the case of peptidase Bacillus thuringiensis var. israelensis IMV B-7465, requires significant resources and extensive kinetic studies. Therefore, it is advisable to use the methods of computational chemistry, the basic task of which is to search for the structure–property relationship, to build a model that can assess the effect of metal ions on peptidase activity with a high degree of probability.

Objective. We are aimed to develop QSAR models for analysis and prediction of the effect of metal ions on the activity of peptidase Bacillus thuringiensis var. israelensis IMV B-7465.

Methods. The effect of metal ions was studied by determining the proteolytic activity of peptidase after co-incubation for 30 min in 0.0167 M Tris-HCl buffer solution (pH 7.5, 37 °C). The final concentration of metal chlorides Li⁺; Na⁺; K⁺; Cs⁺; Cu²⁺; Be²⁺; Mg²⁺; Ca²⁺; Sr²⁺; Ba²⁺; Zn²⁺; Cd²⁺; Hg²⁺; Cr³⁺; Mn²⁺; Co²⁺; Ni²⁺ in the buffer solution was 4 mmol/dm³. To search for the quantitative structure–property relationship, we used the reference data on the properties of metal ions, as well as trend vector and random forest methods.

Results. A study of the effect of metal ions on the proteolytic activity of peptidase Bacillus thuringiensis var. israelensis IMV B-7465 showed that some metal ions (Li⁺, Mn²⁺ и Co²⁺) activated peptidase, while others (Cu²⁺, Be²⁺, Cd²⁺, Hg²⁺, Cr³) inhibited the enzyme activity. Adequate statistical models without classification errors and activity class prediction errors for the test set were constructed by nonlinear trend vector and random forest methods. Both models show that the most important characteristics of metal ions affecting enzyme activity are electronegativity (EN_Pol), the first ionization potential (IP₁), the entropy of ions in aqueous solution (S), and the electron affinity energy (E_ae).

Conclusions. QSAR analysis methods in combination with nonlinear trend vector and random forest methods allow adequately describing the effect of metal ions on the peptidase Bacillus thuringiensis var. israelensis IMV B-7465 activity due to descriptors reflecting a certain balance of their electron-donating and electron-accepting properties (electronegativity, the first ionization potential, the electron affinity energy) and thermodynamic properties in aqueous solution (entropy of solvation). Both statistical methods give similar values of the importance of descriptors, but only the trend vector method allows us to analyze the direction of influence of specific characteristics of ions.