Search

Nature has developed large groups of enzymatic catalysts with the aim to transfer substrates into useful products, which enables biosystems to perform all their natural functions. As such, all biochemical processes in our body (we drink, we eat, we breath, we sleep, etc.) are governed by enzymes. One of the problems associated with research on biocatalysts is that they react so fast that details of their reaction mechanisms cannot be obtained with experimental work. In recent years, major advances in computational hardware and software have been made and now large (bio)chemical systems can be studied using accurate computational techniques. One such technique is the quantum mechanics/molecular mechanics (QM/MM) technique, which has gained major momentum in recent years. Unfortunately, it is not a black-box method that is easily applied, but requires careful set-up procedures. In this work we give an overview on the technical difficulties and caveats of QM/MM and discuss work-protocols developed in our groups for running successful QM/MM calculations.

With computational resources becoming more efficient and more powerful and at the same time cheaper, computational methods have become more and more popular for studies on biochemical and biomimetic systems. Although large efforts from the scientific community have gone into exploring the possibilities of computational methods for studies on large biochemical systems, such studies are not without pitfalls and often cannot be routinely done but require expert execution. In this review we summarize and highlight advances in computational methodology and its application to enzymatic and biomimetic model complexes. In particular, we emphasize on topical and state-of-the-art methodologies that are able to either reproduce experimental findings, e.g., spectroscopic parameters and rate constants, accurately or make predictions of short-lived intermediates and fast reaction processes in nature. Moreover, we give examples of processes where certain computational methods dramatically fail.