One of the fundamental challenges in biotechnology and in biochemistry is the ability to design effective enzymes. Doing so would be a convincing manifestation of a full understanding of the origin of enzyme catalysis. Despite an impressive 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 environment preorganization, which is the key factor in enzyme catalysis. Rational improvement of the preorganization would require approaches capable of evaluating reliably the actual catalytic effect. This work takes apreviously designed kemp eliminases as a benchmark for a computer aided enzyme design, using the empirical valence bond as the main screening tool. The observed absolute catalytic effect and the effect of directed evolution are reproduced and analyzed (assuming that the substrate is in the designed site). It is found that, in the case of kemp eliminases, the transition state charge distribution makes it hard to exploit the active site polarity, even with the ability to quantify the effect of different mutations. Unexpectedly, it is found that the directed evolution mutants lead to the reduction of solvation of the reactant state by water molecules rather that to the more common mode of transition state stabilization used by naturally evolved enzymes. Finally it is pointed out that our difficulties in improving Kemp eliminase are not due to overlooking exotic effect, but to the challenge in designing a preorganized environment that would exploit the small change it charge distribution during the formation of the transition state.computer aided enzyme design | empirical valence bond | directed evolution R ational enzyme design is expected to have a great potential in industrial application and eventually in medicine (1). Furthermore, the ability to design efficient enzymes might be considered as the best manifestation of a true understanding of enzyme catalysis. However, at present there has been a limited success in most attempts of rational enzyme design, and the resulting constructs have been much less effective than the corresponding natural enzymes (1). Furthermore, despite the progress in directed evolution (e.g., ref.2), we do not have unique rationales for the resulting rate enhancements.Most attempts to identify the problems with the current rational design approaches (for review, see ref. 1) have not been based on actual simulations of the given effect. In fact, it has been argued (3,4), that the problems are due to the incomplete modeling of the transition state (TS) and to the limited awareness to the key role of the reorganization energy. Even a recent attempt to use a molecular orbital-combined quantum mechanical /molecular mechanics (MO-QM/MM) approach (5) has not provided a reasonable estimate of the observed catalytic effect or the trend of the mutational effects in an artificially design enzyme. Thus, reproducing the effect of directed evolution and eventually obtaining better performance in enzyme de...
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 advantage over current alternative strategies. The insights provided by the empirical valence bond calculations are discussed emphasizing the ability to analyze the difference between the linear free energy relationships obtained in solution to those found in the enzymes. We also point out the trade off between reliability and speed of the calculations and try to determine what it takes to obtain reliable computer aided screening.
Gaining a deeper understanding of enzyme catalysis is of great practical and fundamental importance. Over the years it has become clear that despite advances made in experimental mutational studies, a quantitative understanding of enzyme catalysis will not be possible without the use of computer modeling approaches. While we believe that electrostatic preorganization is by far the most important catalytic factor, convincing the wider scientific community of this may require the demonstration of effective rational enzyme design. Here we make the point that the main current advances in enzyme design are basically advances in directed evolution and that computer aided enzyme design must involve approaches that can reproduce catalysis in well-defined test cases. Such an approach is provided by the empirical valence bond method.
T cell activation must be properly regulated to ensure normal T cell development and effective immune responses to pathogens and transformed cells while avoiding autoimmunity. The mechanisms controlling the fine-tuning of T cell receptor (TCR) signaling and T cell activation are unclear. The Syk family kinase ζ chain–associated protein kinase of 70 kD (ZAP-70) is a critical component of the TCR signaling machinery that leads to T cell activation. To elucidate potential feedback targets that are dependent on the kinase activity of ZAP-70, we performed a mass spectrometry–based, phosphoproteomic study to quantify temporal changes in phosphorylation patterns after inhibition of ZAP-70 catalytic activity. Our results provide insights into the fine-tuning of the T cell signaling network before and after TCR engagement. The data indicate that the kinase activity of ZAP-70 stimulates negative feedback pathways that target the Src family kinase Lck and modulate the phosphorylation patterns of the immunoreceptor tyrosine-based activation motifs (ITAMs) of the CD3 and ζ-chain components of the TCR, and of downstream signaling molecules, including ZAP-70. We developed a computational model that provides a unified mechanistic explanation for the experimental findings on ITAM phosphorylation in wild-type cells, ZAP-70–deficient cells, and cells with inhibited ZAP-70 catalytic activity. This model incorporates negative feedback regulation of Lck activity by the kinase activity of ZAP-70 and makes unanticipated specific predictions for the order in which tyrosines in the ITAMs of TCR ζ-chains must be phosphorylated to be consistent with the experimental data.
Monovalent engagement can trigger BCR signal transduction, and fine-tuning of BCR-ligand recognition can lead to B cell nonresponsiveness, activation, or inhibition.
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