Directed evolution can be achieved by two major approaches, either by randomly recombining a set of related sequences (e.g. gene shuffling), or by introducing random changes in single protein sequences (e.g. error-prone PCR). The advantage of directed evolution is that no structural information is needed and that variations at unexpected positions distant from the active site can be introduced. However, usually the changes are small and several rounds of evolution have to be applied and thus a high number of variants have to be screened, which is time and labor consuming and requires cheap, fast and reliable high-throughput as says.
In rational design biochemical data, protein structures and molecular modelling data are evaluated to propose mutations, which are introduced by site-specific mutagenesis. One of the advantages of a rational design approach is an increased probability of beneficial mutations and a significant reduction of the library size and thus less effort and time has to be applied for the screening of the library. This is especially advantageous if no high-throughput assay system is available.
Semi-rational design combines advantages of rational and random protein design creating smaller smarter libraries based on knowledge derived from biochemical and/or structural data. An example for a semi-rational approach is CASTing (combinatorial active site saturation test), which uses the information derived from structural data to identify amino acids in interesting regions (e.g. active site), which are then mutated randomly or by site-saturation mutagenesis one by one or in combination. Random combination of mutations or correlated mutations at targeted positions can result in synergistic effects that might have been missed in single site-specific mutagenesis. However, these combinatorial approaches increase the library sizes tremendously and various computational methods have been developed in recent years, that help to decrease the library size by screening of virtual libraries and eliminating mutations predicted to be unfavorable for the protein fold.
Enzymes have been used since time immemorial in cheese manufacturing and indirectly via yeasts and bacteria in food manufacturing. Isolated enzymes were first used in the year 1914, their protein nature proven in 1926 and their large-scale microbial production started in 1960s. The industrial enzyme business is steadily growing due to improved production technologies, engineered enzyme properties and new application fields. In 2004, global demand for industrial enzyme was $2.5 billion with an annual growth rate of 5–10%.
Major applications of enzymes are in
The use of immobilized and stable enzymes as biosensors has immense potential in the enzymatic analysis of clinical, industrial and environmental samples.
Potential advantages of enzymes like high specificity (molecular and chiral), unrivalled activity under mild conditions, high turnover number, biodegradability are offset by the glaring disadvantage of intrinsic instability (characteristic of their complex structure). Technical applications of enzymes in the industry are feasible only if the enzymes are stabilized against temperature, pH extremes and in the presence of salts, alkalis and surfactants. Major applications of enzymes are at high temperature (for example, washing 60 to 700C, starch gelatinization 1000C, textile desizing 80 to 900C, etc.), under high salt concentrations (in food industry), under alkaline conditions and in the presence of surfactants (for example, in detergents and in several biotransformation reaction systems among others). So in order to Enzymes should have high activity as well as high specificity and enantioselectivity towards frequently very challenging substrates. Moreover, they need to be stable during storage and resist a variety of – sometimes harsh – reaction conditions such as elevated temperature, extreme pH, high substrate/product concentrations and organic solvents.
To minimize costs, industries require stable, selective and productive catalysts that operate under the desired process conditions. Engineering enzymes for such a process starts by defining the engineering goal, such as increased stability, selectivity, substrate range.