Severity of Illness Scores May Misclassify Critically Ill Obese Patients.

OBJECTIVE: Severity of illness scores rest on the assumption that patients have normal physiologic values at baseline and that patients with similar severity of illness scores have the same degree of deviation from their usual state. Prior studies have reported differences in baseline physiology, including laboratory markers, between obese and normal weight individuals, but these differences have not been analyzed in the ICU. We compared deviation from baseline of pertinent ICU laboratory test results between obese and normal weight patients, adjusted for the severity of illness. DESIGN: Retrospective cohort study in a large ICU database. SETTING: Tertiary teaching hospital. PATIENTS: Obese and normal weight patients who had laboratory results documented between 3 days and 1 year prior to hospital admission. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Seven hundred sixty-nine normal weight patients were compared with 1,258 obese patients. After adjusting for the severity of illness score, age, comorbidity index, baseline laboratory result, and ICU type, the following deviations were found to be statistically significant: WBC 0.80 (95% CI, 0.27-1.33) × 10/L; p = 0.003; log (blood urea nitrogen) 0.01 (95% CI, 0.00-0.02); p = 0.014; log (creatinine) 0.03 (95% CI, 0.02-0.05), p < 0.001; with all deviations higher in obese patients. A logistic regression analysis suggested that after adjusting for age and severity of illness at least one of these deviations had a statistically significant effect on hospital mortality (p = 0.009). CONCLUSIONS: Among patients with the same severity of illness score, we detected clinically small but significant deviations in WBC, creatinine, and blood urea nitrogen from baseline in obese compared with normal weight patients. These small deviations are likely to be increasingly important as bigger data are analyzed in increasingly precise ways. Recognition of the extent to which all critically ill patients may deviate from their own baseline may improve the objectivity, precision, and generalizability of ICU mortality prediction and severity adjustment models.

Dimerization of the adaptor Gads facilitates antigen receptor signaling by promoting the cooperative binding of Gads to the adaptor LAT.

The accurate assembly of signalosomes centered on the adaptor protein LAT (linker of activated T cells) is required for antigen receptor signaling in T cells and mast cells. During signalosome assembly, members of the growth factor receptor-bound protein 2 (Grb2) family of cytosolic adaptor proteins bind cooperatively to LAT through interactions with its phosphorylated tyrosine (pTyr) residues. We demonstrated the Src homology 2 (SH2) domain-mediated dimerization of the Grb2 family member, Grb2-related adaptor downstream of Shc (Gads). Gads dimerization was mediated by an SH2 domain interface, which is distinct from the pTyr binding pocket and which promoted cooperative, preferential binding of paired Gads to LAT. This SH2 domain-intrinsic mechanism of cooperativity, which we quantified by mathematical modeling, enabled Gads to discriminate between dually and singly phosphorylated LAT molecules. Mutational inactivation of the dimerization interface reduced cooperativity and abrogated Gads signaling in T cells and mast cells. The dimerization-dependent, cooperative binding of Gads to LAT may increase antigen receptor sensitivity by reducing signalosome formation at incompletely phosphorylated LAT molecules, thereby prioritizing the formation of complete signalosomes.

The catalytic activity of the kinase ZAP-70 mediates basal signaling and negative feedback of the T cell receptor pathway.

T cell activation by antigens binding to the T cell receptor (TCR) must be properly regulated to ensure normal T cell development and effective immune responses to pathogens and transformed cells while avoiding autoimmunity. The Src family kinase Lck and the Syk family kinase ZAP-70 (ζ chain-associated protein kinase of 70 kD) are sequentially activated in response to TCR engagement and serve as critical components of the TCR signaling machinery that leads to T cell activation. We performed a mass spectrometry-based phosphoproteomic study comparing the quantitative differences in the temporal dynamics of phosphorylation in stimulated and unstimulated T cells with or without inhibition of ZAP-70 catalytic activity. The data indicated that the kinase activity of ZAP-70 stimulates negative feedback pathways that target Lck and thereby modulate the phosphorylation patterns of the immunoreceptor tyrosine-based activation motifs (ITAMs) of the CD3 and ζ chain components of the TCR and of signaling molecules downstream of Lck, including ZAP-70. We developed a computational model that provides a 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 incorporated negative feedback regulation of Lck activity by the kinase activity of ZAP-70 and predicted the order in which tyrosines in the ITAMs of TCR ζ chains must be phosphorylated to be consistent with the experimental data.

On the challenge of exploring the evolutionary trajectory from phosphotriesterase to arylesterase using computer simulations.

The ability to design effective enzymes presents a fundamental challenge in biotechnology and also in biochemistry. Unfortunately, most of the progress on this field has been accomplished by bringing the reactants to a reasonable orientation relative to each other, rather than by rational optimization of the polar preorganization of the environment, which is the most important catalytic factor. True computer based enzyme design would require the ability to evaluate the catalytic power of designed active sites. This work considers the evolution from a phosphotriesterase (with the paraoxon substrate) to arylesterase (with the 2-naphthylhexanoate (2NH) substrate) catalysis. Both the original and the evolved enzymes involve two zinc ions and their ligands, making it hard to obtain a reliable quantum mechanical description and then to obtain an effective free energy sampling. Furthermore, the options for the reaction path are quite complicated. To progress in this direction we started with DFT calculations of the energetics of different mechanistic options of cluster models and then used the results to calibrate empirical valence bond (EVB) models and to generate properly sampled free energy surfaces for different mechanisms in the enzyme. Interestingly, it is found that the catalytic effect depends on the Zn-Zn distance making the mechanistic analysis somewhat complicated. Comparing the activation barriers of paraoxon and the 2NH ester at the beginning and end of the evolutionary path reproduced the observed evolutionary trend. However, although our findings provide an advance in exploring the nature of promiscuous enzymes, they also indicate that modeling the reaction mechanism in the case of enzymes with a binuclear zinc center is far from trivial and presents a challenge for computer-aided enzyme design.

Computer aided enzyme design and catalytic concepts.

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.

Monovalent engagement of the BCR activates ovalbumin-specific transnuclear B cells.

Valency requirements for B cell activation upon antigen encounter are poorly understood. OB1 transnuclear B cells express an IgG1 B cell receptor (BCR) specific for ovalbumin (OVA), the epitope of which can be mimicked using short synthetic peptides to allow antigen-specific engagement of the BCR. By altering length and valency of epitope-bearing synthetic peptides, we examined the properties of ligands required for optimal OB1 B cell activation. Monovalent engagement of the BCR with an epitope-bearing 17-mer synthetic peptide readily activated OB1 B cells. Dimers of the minimal peptide epitope oriented in an N to N configuration were more stimulatory than their C to C counterparts. Although shorter length correlated with less activation, a monomeric 8-mer peptide epitope behaved as a weak agonist that blocked responses to cell-bound peptide antigen, a blockade which could not be reversed by CD40 ligation. The 8-mer not only delivered a suboptimal signal, which blocked subsequent responses to OVA, anti-IgG, and anti-kappa, but also competed for binding with OVA. Our results show that fine-tuning of BCR-ligand recognition can lead to B cell nonresponsiveness, activation, or inhibition.

Electrostatic origin of the catalytic effect of a supramolecular host catalyst.

The development of enzyme mimetic catalysts as well as the analysis of the catalytic effects of such catalysts has been a major challenge for synthetic chemists. One of the impressive examples of artificial catalysts has been the development of a highly charged host compound that provides a significant acceleration to the hydrolysis of orthoformates and other systems. However, the origin of the catalytic effect has not been quantified, and its origin remains somewhat unclear. The understanding of the corresponding supramolecular catalysis has thus become a major challenge, both in terms of computational modeling and in terms of the analysis of the corresponding acid-catalyzed reaction. Here we present a computer simulation study and kinetic analyses that reproduce the experimentally observed catalytic effect, establishing that this effect is due to electrostatic stabilization of the positively charged transition state (relative to the uncharged bound complex). Our study illustrates the crucial need for careful analysis of the complex kinetics of the catalytic effect and the host system, as well as the need for computational modeling in analyzing the catalytic effect and in the potential design of better catalysts. Finally, our finding of the large stabilization of the bound H(3)O(+) points out the very low "local pH" inside the host system even when the solvent is kept at a high pH.

Nitroxide sensing of a DNA microenvironment: mechanistic insights from EPR spectroscopy and molecular dynamics simulations.

The behavior of the nitroxide spin labels 1-oxyl-4-bromo-2,2,5,5-tetramethylpyrroline (R5a) and 1-oxyl-2,2,5,5-tetramethylpyrroline (R5) attached at a phosphorothioate-substituted site in a DNA duplex is modulated by the DNA in a site- and stereospecific manner. A better understanding of the mechanisms of R5a/R5 sensing of the DNA microenvironment will enhance our capability to relate information from nitroxide spectra to sequence-dependent properties of DNA. Toward this goal, electron paramagnetic resonance (EPR) spectroscopy and molecular dynamics (MD) simulations were used to investigate R5 and R5a attached as R(p) and S(p) diastereomers at phosphorothioate (pS)C(7) of d(CTACTG(pS)C(7)Y(8)TTAG). d(CTAAAGCAGTAG) (Y = T or U). X-band continuous-wave EPR spectra revealed that the dT(8) to dU(8) change alters nanosecond rotational motions of R(p)-R5a but produces no detectable differences for S(p)-R5a, R(p)-R5, and S(p)-R5. MD simulations were able to qualitatively account for these spectral variations and provide a plausible physical basis for the R5/R5a behavior. The simulations also revealed a correlation between DNA backbone B(I)/B(II) conformations and R5/R5a rotational diffusion, thus suggesting a direct connection between DNA local backbone dynamics and EPR-detectable R5/R5a motion. These results advance our understanding of how a DNA microenvironment influences nitroxide motion and the observed EPR spectra. This may enable use of R5/R5a for a quantitative description of the sequence-dependent properties of large biologically relevant DNA molecules.

Validating the vitality strategy for fighting drug resistance.

The current challenge in designing effective drugs against HIV-1 is to find novel candidates with high potency, but with a lower susceptibility to mutations associated with drug resistance. Trying to address this challenge, we developed in our previous study (Ishikita and Warshel, Angew Chem Int Ed Engl 2008; 47:697-700) a novel computational strategy for fighting drug resistance by predicting the likely moves of the virus through constraints on binding and catalysis. This has been based on calculating the ratio between the vitality values ((K(i) k(cat)/K(M))(mutant)/(K(i) k(cat)/K(M))(wild-type)) and using it as a guide for predicting the moves of the virus. The corresponding calculations of the binding affinity, K(i), were carried out using the semi-macroscopic version of the protein dipole Langevin dipole (PDLD/S) in its linear response approximation (LRA) in its ß version (PDLD/S-LRA/ß). We also calculate the proteolytic efficiency, k(cat)/K(M), by evaluating the transition state (TS) binding free energies using the PDLD/S-LRA/ß method. Here we provide an extensive validation of our strategy by calculating the vitality of six existing clinical and experimental drug candidates. It is found that the computationally determined vitalities correlate reasonably well with those derived from the corresponding experimental data. This indicates that the calculated vitality may be used to identify mutations that would be most effective for the survival of the virus. Thus, it should be possible to use our approach in screening for mutations that would provide the most effective resistance to any proposed antiviral drug. This ability should be very useful in guiding the design of drug molecules that will lead to the slowest resistance.

Towards quantitative computer-aided studies of enzymatic enantioselectivity: the case of Candida antarctica lipase A.

The prospect for consistent computer-aided refinement of stereoselective enzymes is explored by simulating the hydrolysis of enantiomers of an α-substituted ester by wild-type and mutant Candida antarctica lipase A, using several strategies. In particular, we focused on the use of the empirical valence bond (EVB) method in a quantitative screening for enantioselectivity, and evaluate both k(cat) and k(cat)/K(M) of the R and S stereoisomers. We found that an extensive sampling is essential for obtaining converging results. This requirement points towards possible problems with approaches that use a limited conformational sampling. However, performing the proper sampling appears to give encouraging results and to offer a powerful tool for the computer-aided design of enantioselective enzymes. We also explore faster strategies for identifying mutations that will help in augmenting directed-evolution experiments, but these approaches require further refinement.

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

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.

Exploring challenges in rational enzyme design by simulating the catalysis in artificial kemp eliminase.

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 previously 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.