A multiscale computational protocol combining bioinformatics, classical force field-based simulations and quantum mechanics. A superior tool that combines bioinformatics and 3D molecular modeling to identify your best target enzymes in the shortest possible time. ZYMEVOLVER is a multi-approach in silico design software that combines sequence- and physics-oriented tools, to identify the most beneficial mutations (consensus and uncommon). BIOMATCHMAKER combines the power of bioinformatics and 3D molecular modeling to identify the best target enzyme for your application in less than two weeks. Only up to 10 wild type enzymes have to be tested! If required, the selected enzyme can always be further improved with ZYMEVOLVER technology. Enzymes are made of amino acids whose identity and position shape function. Bioinformatics provides insights about sequence-function relationships by analyzing in detail protein sequence databases and activity data. It allows to focus the search for improved variants in the portion of sequence space that actually matters. Enzymes are dynamic molecules and all parts should be free to move. Side chain flexibility deals with amino acid side chain movement. These days, while many companies do include a degree of side chain flexibility, this is normally associated with rigid backbone structures. In addition to the side chains, the protein backbone is another important part of the system. Including backbone flexibility is computationally very expensive and time-consuming, so most companies omit it. However, a realistic representation of protein-substrate dynamics requires a fully flexible system. That’s why we have devised methodologies that account for this effect while remaining time- and cost-effective (Gil, 2016). Most computer-guided engineering centers only on amino acids at the active site since, in general, this is the most important area of the protein when looking to improve activity, selectivity or specificity. Nevertheless, experimental directed evolution has shown that this is true only to a certain extent, and amino acids in other parts of the protein are often required for effective improvements. Therefore, we are currently implementing this extremely challenging feature to make our simulations even more powerful and be able to compete with experimental techniques in this area at a fraction of their cost. Most of our competitors use implicit solvent representation via dielectric constant to simulate solvent effect (typically for water, ε=78) The alternative is to use explicit water molecules (3 atom particles) that permit a far more realistic representation of the solvent but are computationally much more expensive. We use a multi-scale protocol that allows us to screen a large number of variants in a first phase with implicit water or another solvent before increasing the level of theory in the second filter to include explicit solvent over a smaller number of selected variants. Includes electronic-based simulations that can account for the fundamental enzyme processes of bond breaking/forming and electron transfer. Most companies rely exclusively on “cheaper” classical force field-based methods or on bioinformatics alone. ZYMEVOLVER uses a hybrid method called QM/MM (quantum mechanics/molecular mechanics, awarded the Nobel Prize in Chemistry, 2013) that allows us to study reaction chemistry with electronic structure methods like Density Functional Theory, and the rest of the system (protein and solvent) with classical MM. Our team has developed highly efficient methods—very economical from the computational point of view and very quick—that allow us to study the effect of point mutations in a time frame that can be used at the industrial level (Monza, 2015).In silico
enzyme
revolution®Produce millions of in silico enzyme variants and test in the lab only what matters
ZYMEVOLVER
BIOMATCHMAKER
ZYMEVOLVER
BIOMATCHMAKER
ZYMVOL provides ALL important features for simulation of biocatalytic reactions
Bioinformatics
Side chain Flexibility
Backbone flexibility
Distant mutations
Explicit Solvent
Quantum mechanics
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