Enzymdesign

Enzymdesign is a field at the intersection of biotechnology, biochemistry, and computational biology that aims to create enzymes or modify existing ones to catalyze chosen chemical reactions with specified activity, selectivity, and stability. It includes de novo design of catalytic proteins and rational design via mutagenesis and directed evolution.

Methods combine computational modeling, sequence design, and experimental screening. Computational design tools, such as Rosetta, model active-site geometry, transition-state stabilization, and scaffold compatibility. Rational design uses structural and mechanistic hypotheses; directed evolution generates large variant libraries and selects improved functions. Recent work integrates machine learning to predict beneficial mutations and guide design choices.

History: Early efforts in the 1990s and 2000s showed that catalytic motifs could be transplanted into scaffolds, but initial designs often had limited activity. Advances in computation and high-throughput screening enabled iterative design–evolution cycles, yielding enzymes with substantial improvements and enabling novel-to-nature reactions.

Applications and challenges: Applications span industrial biocatalysis, green chemistry, pharmaceutical synthesis, and environmental remediation. Benefits include milder conditions, high specificity, and reduced metal catalysts. Limitations include achieving high catalytic efficiency comparable to natural enzymes, narrow substrate scope, stability under process conditions, and the translation of model designs to scalable systems.

See also Enzyme engineering; Computational protein design; Directed evolution.