Related Experiment Video
Updated: Jul 12, 2026
05:08
Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
Published on: July 8, 2025
Applications and limitations of AI tools in enzyme design
Rosa Teijeiro-Juiz1, Nina Egeler2, Grzegorz Jamróg2
1Institute of Chemistry and Biochemistry, Laboratory of Structural Biochemistry, Freie Universität Berlin, Berlin, Germany.
Protein Science : a Publication of the Protein Society
|July 10, 2026
Summary
Artificial intelligence (AI) is revolutionizing enzyme engineering by accelerating the design of novel enzymes. This review guides experimentalists in applying AI computational methods for efficient enzyme design and optimization.
Area of Science:
- Biochemistry
- Computational Biology
- Protein Engineering
Background:
- Enzymes offer superior efficiency and selectivity over synthetic catalysts.
- Protein engineering has enabled enzyme design for specific or novel reactions.
- Experimental validation of computational designs and limited knowledge of enzyme mechanisms are key bottlenecks.
Purpose of the Study:
- To provide a comprehensive overview of current artificial intelligence (AI)-driven methods for enzyme design.
- To serve as an accessible guide for experimental researchers interested in AI-based computational enzyme engineering.
Main Methods:
- Review of AI-driven approaches for enzyme design, including reaction-to-sequence design.
- Focus on AI applications in structure prediction, substrate scope prediction, and engineering stable variants.
- Exploration of AI for designing enzymes with non-canonical amino acids and de novo design.
Main Results:
- AI methods offer powerful tools to overcome bottlenecks in traditional enzyme engineering.
- AI facilitates reaction-to-sequence design, improving catalytic performance.
- AI aids in predicting enzyme structures, substrate scopes, and engineering stability.
Conclusions:
- AI-driven computational methods are essential for advancing enzyme engineering.
- This review empowers experimentalists to integrate AI tools into their research.
- AI accelerates the discovery and optimization of enzymes for diverse applications.
Related Concept Videos
01:07Catalytically Perfect Enzymes
The theory of catalytically perfect enzymes was first proposed by W.J. Albery and J. R. Knowles in 1976. These enzymes catalyze biochemical reactions at high-speed. Their catalytic efficiency values range from 108-109 M-1s-1. These enzymes are also called 'diffusion-controlled' as the only rate-limiting step in the catalysis is that of the substrate diffusion into the active site. Examples include triose phosphate isomerase, fumarase, and superoxide dismutase.
02:34Enzymes
Inside living organisms, enzymes act as catalysts for many biochemical reactions involved in cellular metabolism. The role of enzymes is to reduce the activation energies of biochemical reactions by forming complexes with its substrates. The lowering of activation energies favor an increase in the rates of biochemical reactions.
Enzyme deficiencies can often translate into life-threatening diseases. For example, a genetic abnormality resulting in the deficiency of the enzyme G6PD...
Enzyme deficiencies can often translate into life-threatening diseases. For example, a genetic abnormality resulting in the deficiency of the enzyme G6PD...
01:22Introduction to Enzymes
The use of enzymes by humans dates to 7000 BCE. Humans first used enzymes to ferment sugars and produce alcohol without knowing that this was an enzyme-catalyzed reaction. Wilhelm Kuhne coined the term 'enzyme' in 1877 from the Greek words ‘en’ meaning ‘in’ or ‘within’ and ‘zyme’ meaning ‘yeast.’
Most enzymes are proteins that speed up biochemical reactions without being consumed. Enzymes contain one or more active sites that bind the substrates and convert them into products. Many enzymes also...
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01:13Introduction to Mechanisms of Enzyme Catalysis
For many years, scientists thought that enzyme-substrate binding took place in a simple "lock-and-key" fashion. This model stated that the enzyme and substrate fit together perfectly in one instantaneous step. However, current research supports a more refined view scientists call induced fit. The induced-fit model expands upon the lock-and-key model by describing a more dynamic interaction between enzyme and substrate. As the enzyme and substrate come together, their interaction causes a mild...
01:30Enzyme Inhibition
Inhibitors are molecules that reduce enzyme activity by binding to the enzyme. In a normally functioning cell, enzymes are regulated by a variety of inhibitors. Drugs and other toxins can also inhibit enzymes. Some inhibitors bind to the enzyme’s active site, while others inhibit enzymatic activity by binding to other sites on the protein structure.
01:33Enzyme-Linked Immunosorbent Assay
In 1971, Peter Perlman and Eva Engvall developed an Enzyme-linked immunosorbent assay (ELISA or EIA). ELISA differs from western blot in that the assays are conducted in microtiter plates or in vivo rather than on an absorbent membrane.
There are many different types of ELISAs, but they all involve an antibody molecule whose constant region binds an enzyme, leaving the variable region free to bind its specific antigen. Enzyme-substrate reaction allows the antigen to be visualized or quantified.
There are many different types of ELISAs, but they all involve an antibody molecule whose constant region binds an enzyme, leaving the variable region free to bind its specific antigen. Enzyme-substrate reaction allows the antigen to be visualized or quantified.