Technologies
inSEIT uses novel bioinformatic tools and clever screening techniques to excel in our enzymatic services.
How we work: the process.
01. Physicochemical Characteristics
Analysis of the protein of interest through various bioinformatic tools to characterize its polarity, hydrophobicity and physicochemical behavior.
02. Surface analysis
Analysis of the surface of the enzyme, allowing us to identify the chemical handles and distribution of the different residues that will be important for immobilization.
03. Dynamic analysis
Application of short molecular dynamics simulations to study not only a frame, but the full movie of your enzyme. Through this dynamic analysis, we study the changes in the structure that can affect the process of immobilization.
04. Reactivity and orientation control
With all the gathered data, we can make informed and rational decisions based on our extensive experience on the immobilization strategies that better fit the enzyme.
Heterogeneity solutions
“Forget one-fits-all, we unleash a Swiss Army knife of possibilities”
​
We know that in the field of immobilization, there is no unique technique that will work for all enzymes. We have gathered many solutions for this.​
​
We continuously push the boundaries of enzyme immobilization, driving innovation and exploring novel options in the field.
​
We are constantly growing our inventory to ensure we find the right combination of chemistry, support and conditions to enhance the stability and activity of any enzyme.
Different materials
We can immobilize your enzyme onto a variety of supports. From commercial methacrylic or silica resins, to more sustainable options such as polysaccharide matrices.
​
Different chemistries
We have optimal protocols for the application of multiple chemistries of immobilization (covalent or non-covalent) to ensure we maintain the maximum activity of the enzyme after immobilization.
​
Different immobilization conditions
​Enzymes are sensitive to their environment, and we explore a plethora of immobilization conditions to ensure the final catalyst has the maximum performance and stability.
We embraced a data-oriented approach
All the gathered data is stored in a comprehensive and standardized manner that allows us to apply machine learning approaches to predict the behavior of the immobilized enzyme. We have the ability to predict an unpredictable technique now.
Classification and data mining
We are capable of distinguishing between ‘good enzymes’ for immobilization and those whose immobilization will be difficult. Nonetheless, we have no restrictions in the enzyme we tackle – we can immobilize anything by combining different supports, chemistry, and immobilization conditions.
