Challenges and advances in validating enzyme design proposals: the case of kemp eliminase catalysis.

Department of Chemistry, 418 SGM Building, University of Southern California, 3620 McClintock Avenue, Los Angeles, California 90089-1062, USA.
Biochemistry (Impact Factor: 3.38). 03/2011; 50(18):3849-58. DOI: 10.1021/bi200063a
Source: PubMed

ABSTRACT One of the fundamental challenges in biotechnology and biochemistry is the ability to design effective enzymes. Despite recent progress, most of the advances on this front have been made by placing the reacting fragments in the proper places, rather than by optimizing the preorganization of the environment, which is the key factor in enzyme catalysis. Thus, rational improvement of the preorganization would require approaches capable of evaluating reliably the actual catalytic effect. This work considers the catalytic effects in different Kemp eliminases as a benchmark for a computer-aided enzyme design. It is shown that the empirical valence bond provides a powerful screening tool, with significant advantages over current alternative strategies. The insights provided by the empirical valence bond calculations are discussed with an emphasis on the ability to analyze the difference between the linear free energy relationships obtained in solution and those found in the enzymes. We also point out the trade-off between the reliability and speed of the calculations and try to determine what it takes to realize reliable computer-aided screening.

  • [Show abstract] [Hide abstract]
    ABSTRACT: We propose a new computational approach for predicting the impact of point mutations on residual enzymatic activities. We build on the general linear trends existing between free energy and enthalpy of transfer of substrates from cytosol to enzyme active sites (protein–ligand binding), therefore linking the docking energies to the binding free energies. In this very first step, we rationalize these trends in terms of a compensation effect decomposed into explicit thermodynamics contributions. In a second step, we combine the latter with the assumption that free energies of transfer, estimated from docking, and free energies of activation are linearly related through a Brönsted–Evans–Polanyi (BEP) relationship, allowing us in fine to predict enzyme activity. As a result, we propose generic Langmuir–Hinshelwood kinetic equations “trained” on the wild type, which provide excellent predictions of rates of catalytic transformations for mutated enzymes from the combination of in silico docking energies to a set of system-specific experimental data. This generalized approach is validated against clinical data on the particular case of human fumarase with major implications for the understanding of hereditary fumarase deficiency.
    ACS Catalysis 11/2012; 2(12):2673–2686. DOI:10.1021/cs300538z · 7.57 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the ‘search space’ of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the ‘best’ amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.
    Chemical Society Reviews 12/2014; DOI:10.1039/C4CS00351A · 30.43 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: One of the greatest challenges in biotechnology and in biochemistry is the ability to design efficient enzymes. In fact, such ability would be one of the most convincing manifestations of a full understanding of the origin of enzyme catalysis. Despite some progress on this front most of the advances have been made by placing the reacting fragments in the proper places rather than by optimizing the environment preorganization, which is the key factor in enzyme catalysis. A rational improvement of the preorganization and a consistent assessment of the effectiveness of different design options require approaches, capable of evaluating reliably the actual catalytic effect. In this work we examine the ability of the empirical valence bond (EVB) to reproduce the results of directed evolution improvements of the catalysis of diethyl 7-hydroxycoumarinyl by a previously designed mononuclear zinc metalloenzyme. Encouragingly, our study reproduced the catalytic effect obtained by directed evolution and offers a good start for further studies of this system.
    The Journal of Physical Chemistry B 09/2014; 118(42). DOI:10.1021/jp507592g · 3.38 Impact Factor

Full-text (2 Sources)

Available from
Jul 2, 2014