Directed evolution creates diversity in subsequent rounds of mutagenesis in the quest of increased protein stability, substrate binding and catalysis. Although this technique does not require any structural/mechanistic knowledge of the system, the frequency of improved mutations is usually low. For this reason, computational tools are increasingly used to focus the search in sequence space, enhancing the efficiency of laboratory evolution. In particular, molecular modeling methods provide a unique tool to grasp the sequence/structure/function relationship The final publication is available at Springer via https://link.springer.com/chapter/10.1007/978-3-319-50413-1_10/fulltext.html of the protein to evolve, with the only condition that a structural model is provided. With this book chapter, we tried to guide the reader through the state of art of molecular modeling, discussing their strengths, limitations and directions. In addition, we suggest a possible future template for in silico directed evolution where we underline two main points: a hierarchical computational protocol combining several different techniques, and a synergic effort between simulations and experimental validation.
IntroductionBiotechnology needs catalysts that can work under harsh conditions, catalyze a broad range of substrates, generate maximum amount of product, and tolerate changes in the environment. Enzymes, which are biodegradable and reusable catalysts [1], in addition to remarkable reaction rates, can work in environmentally friendly pH and temperature ranges, and display control over stereochemistry and regioselectivity which makes them ideal for many applications [2,3]. When thinking about enzymes, people normally associate them to expressions such as "perfect catalysts" or "outstanding reaction rate". In fact, there are examples of enzymes that catalyze reactions at extremely high rates such as triose phosphate isomerase, superoxide dismutase or carbonic anhydrase [4]. These are often limited only by the rate of ligand diffusion into the active site (diffusion-controlled rate). Nevertheless, an extensive analysis by Bar-Even et al., of nearly 2000 enzymes, showed that the median maximal turnover rate value over all measured enzymes is about 10 s −1 nowhere close to the values of 10 5 or 10 6 normally associated with catalysts [5,6].So, it would appear that natural enzymes are "just good enough" for the function they must perform in a given organism [7]. One might conclude that if they had evolved to their optimum performance then trying to improve them (from a kinetic point of view) would be attempting the impossible. On the contrary, as seen by the distribution of reaction rates, k cat , most enzymes function at a lower rate than the diffusion-limit and thus, there is space to further increase their kinetic properties to meet industrial needs. Additionally, we need enzymes capable of catalyzing reactions for which no known enzymes exist, to work with different substrates and for particular conditions that are industrially...