QSAR analysis of the effect of metal ions on the peptidase activity of Bacillus thuringiensis var. israelensis IMV B-7465

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 similar 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 research. Therefore, it is advisable to use the methods of computer chemistry, the basic task of which is to search for the structure-property relationship, to build a model that can, with a high degree of probability, assess the effect of metal ions on the activity of peptidase. Objective: Objective: to develop of QSAR models to analyze and prediction 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 joint incubation for 30 min in 0.0167 M Tris-HCl buffer solution (pH 7.5, 37 ° C). 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 and trend vector and random forest methods. Results: the effect of metal ions on the proteolytic activity of peptidase Bacillus thuringiensis var. israelensis IMV B-7465, some metal ions (Li +, Mn2 +, and Co2 +) activated peptidase, while others (Cu2 +, Be2 +, Cd2 +, Hg2 +, Cr3 +) inhibited the enzyme activity. Adequate statistical models without classification errors and prediction errors for the test set were constructed by nonlinear methods of trend-vector and random forest. Both models show that the most important characteristics of metal ions that affect enzyme activity are electronegativity (ENPol), first ionization potential (IP1), the entropy of ions in aqueous solution (S) and the electron affinity energy (Eae). Conclusions: methods of QSAR analysis in combination with nonlinear methods of trend vector and random forest allow to adequately describe the influence of metal ions on the activity of peptidase Bacillus thuringiensis var. israelensis IMV B-7465 due to descriptors that reflect a certain balance of their electron-donor and electron-acceptor properties (electronegativity, first ionization potential, electron affinity energy) and the degree of the hydrate shell structurization (entropy of solvation). Both statistical methods give similar values of the importance of descriptors, but only the trend vector method allows to analyze the direction of influence of specific characteristics of ions.