A tabela 2 resume os dados relativos ao nível de conhecimento sob

A tabela 2 resume os dados relativos ao nível de conhecimento sobre os fatores de risco e estratégias de prevenção do CCR. Apenas 40,5% dos respondentes foram capazes de dar a definição de CRC. As percentagens de respostas corretas sobre os fatores de risco de CCR não Sunitinib ultrapassaram os 52,2% para o fator de risco pólipos, seguido de 51,6% para elevada ingestão de gorduras, 46,8% para o tabaco, 42,8% para a história familiar de CCR e, por último, 29,9% para a baixa atividade física. Nos fatores de «não» risco para o CCR houve grandes oscilações, desde 80,2% para a ingestão de frutas e vegetais até 18,4% para as infecções intestinais. Relativamente ao conhecimento dos exames

de rastreio do CCR, 50,6% dos indivíduos identificou corretamente a PSOF e, logo a seguir, 49,9% a colonoscopia. A análise dos resultados relativos às atitudes dos

portuenses abrangeu a perceção do risco e da utilidade dos exames de rastreio do CCR e a atitude em relação à prevenção e ao tratamento do CCR (tabela 3). Na perceção individual do risco de contrair a doença, mais de 50% dos inquiridos respondeu não ter qualquer risco (1 valor) ou ter risco intermédio (5 valores). Quanto à perceção acerca FXR agonist da utilidade dos exames de rastreio, quase metade dos indivíduos classificou com a pontuação máxima. Relativamente à prevenção e ao tratamento, 78,3% dos inquiridos concordaram que o CCR pode ser prevenido e 83,2% assentiram que o CCR pode ser tratado. No que concerne Janus kinase (JAK) à recomendação de exames de rastreio, a colonoscopia foi aconselhada a 21% dos participantes e a PSOF a uma minoria de 8,2%. Em relação aos exames de rastreio realizados, a colonoscopia foi efetuada por 13,2% dos indivíduos, seguida da PSOF, realizada por 9,8%. A maioria dos indivíduos (64,7%) referiu nunca ter realizado nenhum exame de rastreio do CCR. De acordo com a análise descritiva das variáveis dependentes dos modelos estudados, no modelo 1 a baixa atividade física e a elevada ingestão de gorduras foram identificados, em simultâneo, como os

2 principais fatores de risco modificáveis para o CCR apenas por 25,4%. No modelo 2, o conhecimento de, pelo menos, um dos principais exames de rastreio do CCR foi demonstrado pela maioria dos inquiridos (63,2%). Quanto ao Modelo 3, a atitude positiva em relação à utilidade dos exames de rastreio do CCR foi evidenciada pela população em geral, visto que 49,7% da amostra atribuiu pontuação máxima à utilidade dos exames de rastreio do CCR (tabela 3). Por fim, no Modelo 4, a atitude positiva em relação à realização de exames de rastreio verificou-se em 20,4% dos indivíduos, os quais realizaram pelo menos um exame de rastreio do CCR. Após selecionar as variáveis que tiveram significado estatístico na análise bivariada, procedeu-se ao estudo multivariado, do qual os resultados são apresentados na tabela 4.

During such events every single movement of legs was accompanied

During such events every single movement of legs was accompanied by exceptional spikes in the CO2 production curve at these low temperatures, which could be clearly distinguished from the common resting gas exchange pattern (our own unpublished results). Thus we assume the wasp forced activity CTmin to be below 5.8 °C (our lowest experimental temperature with IR video observation). In any case our investigations demonstrate an increased cold hardiness of Vespula sp. foragers in comparison to A. mellifera. MacMillan and Sinclair (2011) proposed that in insects chill coma and CTmin are not caused by failure of cell respiration or the

circulatory system but by disruption of signal transmission leading to failure in the neuromuscular system. Hazell et al. (2008) and Hazell and Bale (2011) opine that selleck screening library voluntary and forced activity show an insects’ CTmin. Respiration data seem not to be of so much significance for them regarding the lower thermal limit. Insect respiration,

however, depends on active spiracle control and abdominal respiratory movements to achieve sufficient exchange of respiration gases via the tracheae. So respiration and muscular and neural activity are closely related. Like in CTmax determination, selleck chemicals the combination of respiratory and behavioral data seems to provide the most accurate results in defining CTmin. Our investigation showed that even closely

related groups like honeybees and wasps Monoiodotyrosine may show significant differences of resting metabolism (Fig. 7, compare No. 7 A. mellifera ( Kovac et al., 2007), No. 8 Vespula sp. (this study) and No. 9 P. dominulus ( Weiner et al., 2009)). In a comparison over several taxa Vespula sp. stands out with a high resting metabolic rate over the entire temperature range ( Fig. 7). At Ta = 20 °C the CO2 production of Vespula sp. is 60% higher than that of A. mellifera, an insect with similar body shape, weight and active thermoregulation: 18.054 μl mg−1 min−1 vs. 11.16 μl mg−1 min−1. This might be based on differences in the thermal activity range as well as diverse overwintering strategies (single Polistes- and Vespula-queens vs. whole Apis colony). Nowickia sp. has a comparable body mass, but an even lower resting metabolism of only 2.304 μl mg−1 min−1 ( Chappell and Morgan, 1987). This is only 13% of Vespula’s turnover. Measurements at only one temperature ( Fig. 8) or in the species’ preferred temperature range do not always show differences between species clearly. Only respiratory data gathered over the animals’ entire active temperature range allows profound comparison. The metabolic theory of ecology links the metabolic rate to mass and ambient temperature. It predicts a general decrease of mass-specific metabolism with body mass for all organisms (see e.g. Clarke, 2006).

e , following the tidal excursion) Neglecting cross-shore advect

e., following the tidal excursion). Neglecting cross-shore advection (including PD-0332991 chemical structure rips, etc.) will generally lead to conservative estimates of the contribution of physical dilution to FIB decay. In the AD model, FIB particles are advected alongshore by 20 min average currents (u), that vary in the cross-shore (y). FIB particles diffuse along- and cross-shore by horizontal diffusion (κh). For a particle starting at (xt, yt), its position at (xt+Δt, yt+Δt) is: equation(2) xt+Δt=xt+∂κh(yt)∂yΔt+R2κhryt+12∂κh∂yΔtΔt+uΔt equation(3) yt+Δt=yt+∂κh(yt)∂yΔt+R2κhryt+12∂κh∂yΔtΔtwhere R is a random

number with zero mean and variance r. For this model, r = 1/3, giving R a uniform distribution with range [−1 1] ( Ross and Sharples, 2004 and Tanaka and Franks, 2008). The time step was Δt = 1 s for all model runs. A reflecting boundary condition was used at the shoreline; otherwise particles could move anywhere in the domain. The AD model was initialized at

t0 = 0650 h (the earliest FIB sampling time) with 80,000 bacterial particles distributed uniformly within a rectangular (x, y) patch. Each particle represents a number of FIB (concentration C); the actual number of FIB per particle can be scaled to match the data, provided the same scaling is applied to every particle. Our scaling constants were determined such that the space–time mean of AD modeled FIB equaled Selleckchem INCB024360 the space–time mean of measured FIB (E. coli or Enterococcus). Initial patch boundaries (along and cross-shore) were identified by varying patch boundary locations over Niclosamide reasonable ranges to maximize the skill between the AD model and HB06 FIB data. Skill is defined as: equation(4) Skill=1-mean(Cobs-Cmod)2mean(Cobs-C¯obs)2where Cobs   are log FIB concentration

data, Cmod   are log AD model outputs, and C¯obs is the space–time mean of log(Cobs) for all stations and times ( Krause et al., 2005). Here, skill is a measure of how much better (or worse) the model explains fluctuations in the data than the data mean. A value of 0 indicates that the model performs the same as the data mean. A value of 1 indicates that the model explains all the variance after removing the mean, and a negative value indicates that the model performs worse than the data mean. Depending on the context, the numerator for skill was calculated for individual stations, groups of stations, or all stations together; the denominator was always the same (all stations). HB06 FIB observations showed the offshore FIB patch edge to be ∼140–300 m from the shoreline. The effect of this range of possible offshore patch edges was explored in the model. The northernmost patch edge was varied from 0 to 2000 m north of the sampling region, and the southernmost patch edge was varied from 0 to 2000 m south of the sampling region. The initial patch always included the 1 km-long sampling region.

Published by Elsevier Ltd This is an open access article under t

Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/). Schizophrenia is a debilitating psychiatric disorder, characterised by hallucinations, delusions, thought disorder and cognitive deficits, and has a lifetime prevalence of around 1%. Evidence for a substantial genetic contribution comes from family, twin and adoption studies [1] but the underlying causes and pathogenesis of the disorder remains unknown. Z-VAD-FMK purchase The past few years have witnessed marked progress in

our understanding of genetic risk at the level of DNA variation, which has been largely driven by applying advanced genomic technologies to very large samples. There is evidence that risk variants occur across the full allelic frequency spectrum, many of which are associated with other neuropsychiatric disorders. Moreover, genetic associations involving different classes of mutations have now implicated specific this website biological pathways in disease pathogenesis. This review will cover recent advances in schizophrenia genetics from studies of de novo mutation, rare copy number variation (CNV), rare single nucleotide variant (SNV, defined as point mutations with a frequency less than 1%) and small insertion/deletion (indel) mutations and single nucleotide polymorphisms (SNPs, defined as point mutations with a frequency greater than 1%) ( Figure 1). High heritability estimates for schizophrenia suggest that

much of the risk is inherited [2]. However, alleles which are not inherited, i.e. newly arising (de novo) mutations, have also been shown to contribute to risk. In addition, increased paternal age at conception, which is correlated with the number of de novo mutations observed in an individual [ 3 and 4], has been

associated with increased Thymidylate synthase schizophrenia risk [ 5]. The first molecular evidence associating de novo mutation with schizophrenia came from studies of CNVs [ 6, 7 and 8]. Across studies, the CNV de novo mutation rate was found to be significantly elevated in schizophrenia (∼5%) versus controls (∼2%), with some evidence for a higher rate among patients with no family history of the disorder [ 6, 7 and 8]. The median size of de novo CNVs > 100 Kb found in schizophrenia cases (574 Kb [ 6, 7 and 8]) is also larger compared with that in controls (337 Kb [ 6, 7, 8 and 9]). Selection coefficients (s) between 0.12 and 0.88 have been estimated for CNVs robustly associated with schizophrenia (a selection coefficient of 1 being reproductively lethal) [ 10]. With this intensity of selection, de novo CNVs at schizophrenia-associated loci are purged from the population in less than five generations [ 10]. Studying gene-sets overrepresented for being disrupted by de novo mutation in schizophrenia has provided novel insights into biological pathways underlying the disorder. For example, genes disrupted by schizophrenia de novo CNVs are enriched for those in the post-synaptic-density proteome [ 6].

The contents of each tube were then

diluted 1 in 10 and a

The contents of each tube were then

diluted 1 in 10 and analysed by ICP-MS as per the method specified above. Five of each sample type were analysed. In order to ascertain whether a worker with a “steady” history of lead exposure would produce differing results to one whose lead exposure had fluctuated, it was necessary to quantify the degree to which each worker’s historical exposure had fluctuated. Over 90% of the lead content of whole blood is contained in the erythrocytes (Goyer, 2001). The average survival time of erythrocytes in the bloodstream is 120 days (Dessypris, 1999). To account for this, the mean of all blood lead values acquired since January 2009, and recorded ≥120 days Selleck Doxorubicin prior to the measurement of the study sample, was calculated for each individual. The difference between the result of the study blood lead value and the mean of the historical observations (Δ) was then calculated. The median Δ was −1 μg/dL, and the 25th and 75th percentiles −2 μg/dL and +1 μg/dL respectively. However, the presence of a small number of large Δ values produced an overall standard deviation Selleck Pexidartinib of 9.49 μg/dL. It was decided to categorise the samples for their exposure history according to the magnitude of Δ. History “1” included all samples where Δ ≤ ± 1 μg/dL; history

“2” all samples where Δ ≤ ± 2 μg/dL; history “3” all samples where Δ ≤ ± 3 μg/dL. Samples where Δ > ± 3 μg/dL were categorised as “fluctuating history”. Samples with no blood lead values recorded ≥120 days prior to the measurement of the study sample were categorised as “no sample history”. Neither the blood lead nor the salivary lead data were normally distributed, with the salivary

lead data more skewed than the blood Resminostat lead data. Both datasets could be much more closely approximated to a log-normal distribution; therefore the relationship between log(saliva lead) and log(blood lead) was investigated. Log(saliva lead) was plotted against log(blood lead) and the Pearson’s correlation coefficient (r) was calculated, for the entire dataset and for the various history categories. Multiple regression analyses were also carried out to investigate whether smoking status or the age of the participant had any effect on the saliva or blood lead levels, or on the relationship between the two. For the blood lead analysis, all CRM results were within the certified range. Values obtained for the CRMs were as follows: level 1 lot 36741 (certified range 9.39–14.1 μg/dL): n = 91 mean 11.1 μg/dL, standard deviation (SD) 0.63 μg/dL; level 3 lot 36743 (certified range 43.7–65.5 μg/dL): n = 91, mean 52.5 μg/dL, SD 2.81 μg/dL. The limit of detection (LOD) for the saliva analysis for the study was 0.011 μg/L, based on the mean of all the blank samples, plus three times the standard deviation of the mean (McNaught and Wilkinson, 1997). All results were greater than the LOD and therefore no non-detects were observed.

The polymerization of the resin subsequently proceeded at 60 °C f

The polymerization of the resin subsequently proceeded at 60 °C for 48 h. The embedded samples were sectioned MG-132 cost in ∼70 nm thick slices using a diamond knife. The sections were transferred to supported gold grids and stained with uranyl acetate and Pb-citrate. The samples were observed under a Carl-Zeiss Model LEO906 transmission electron microscope. The surface-response methodology was used to study the effect of the plasticizer concentration (Cg or Cs) and process temperature (Tp) on dependent variables (mechanical properties and solubility).

The levels of the independent variables were defined according to a 22 full-factorial central composite design (star configuration) (Table 1 and Table 2).

An analysis of variance (ANOVA), a multiple comparison test, and all statistical analyses were performed using the Statistica 6.0 software. The data were fitted to a second order equation (Eq. (2)) as a function of the independent variables. equation(2) Yi=b0+b1X1+b2X2+b12X1X2+b11X11+b22X22where bn are constant regression coefficients, Yi are dependent variables (puncture force (PF), puncture deformation (PD), tensile strength (TS), elongation at break (E), Young’s modulus (YM), and solubility (S)), and X1 and X2 are the coded independent variables (plasticizer concentration and process temperature, respectively). After the surface-response results, were obtained, HAS1 optimization

of the process conditions was carried out by multi-response analysis Talazoparib cell line (Derringer & Suich, 1980). This method involves the transformation of response variables (Yi) to an individual function of dimensionless desirability (gi) (Eq. (4)), ranging from 0 (undesirable response) to 1 (desired response). From the geometric means of individual desires, the overall desirability function (G) (Eq. (3)) is obtained. G was later maximized using the software Mathematic 5.0. equation(3) G=(g1n1,g2n2,……,gknk)1/kwhere: equation(4) gi=Yi−YminYmax−Yminwhere Ymin is the response minimum value and Ymax is the response maximum value, k is the number of considered responses, and ni is the weight of each response. In the case of solubility, Eq. (4) had to be redesigned, so that the minimum values for these responses could be obtained (Eq. (5)). equation(5) gi=Ymax−YiYmax−Ymin Finally, the Tukey’s test was applied at a 5% significance level to compare means for mechanical, solubility, moisture content, barrier properties, and GAB parameters of glycerol and sorbitol films prepared using the optimal formulation. The amaranth flour contains 9.0 ± 0.4 g/100 g moisture, 2.1 ± 0.0 g/100 g ash, 7.9 ± 0.2 g/100 g lipids, 14.1 ± 0.3 g/100 g protein, and 75.8 ± 0.2 g/100 g starch (among which 11.9 ± 0.3 g/100 g was amylose) (dry basis).

This inhibitory trend was maintained after cessation of juglone i

This inhibitory trend was maintained after cessation of juglone infusion. Fig. 3B allows an evaluation of the effects of several juglone concentrations on oxygen uptake and glucose production from lactate in the range of 5.0–50 μM. The final values observed at the end of the juglone infusion period (60 min perfusion time) were represented against the juglone concentrations. Glucose learn more production was inhibited over the whole range of the juglone concentrations. Numerical

interpolation revealed 50% inhibition at the juglone concentration of 14.9 μM. Oxygen uptake, on the other hand, was stimulated by juglone up to 20 μM, with maximal stimulation at 5 μM. Inhibition occurred at 50 μM, as also shown in Fig. 3A. Alanine gluconeogenesis was also investigated. This substrate induces

a more oxidized state when compared to lactate BLZ945 concentration and the transfer of the amine group also influences the urea cycle and several related pathways. Fig. 4A shows the effects of 50 μM juglone on the carbon fluxes and oxygen uptake due to alanine infusion whereas Fig. 4B illustrates the changes in the nitrogen fluxes. The infusion of 2.5 mM alanine caused a rapid increase in glucose production and oxygen uptake (Fig. 4A). The subsequent infusion of 50 μM juglone was strongly inhibitory for glucose production. Oxygen consumption underwent an initial transitory increase that was reversed to inhibition at 60 min perfusion time (Fig. 4A). Finally, 50 μM juglone strongly stimulated lactate and pyruvate production. The nitrogen fluxes were also

affected (Fig. 4B). Ammonia and glutamate production Pyruvate dehydrogenase were both clearly stimulated by the drug. Urea production underwent an initial transitory increase, which was followed by inhibition. The concentration dependences of the juglone effects on alanine metabolism are shown in Fig. 5. Inhibition of glucose production presents a clear concentration dependence, with 50% inhibition at the concentration of 15.7 μM. Stimulations of ammonia and glutamate productions were saturable functions of the juglone concentration in the range up to 50 μM, with half-maximal stimulations at 4.15 and 5.1 μM, respectively. Lactate and urea production were stimulated in the range up to 20 μM, with a declining tendency at 50 μM. Oxygen uptake was also stimulated by juglone up to 20 μM, but diminished to values below the basal ones at the concentration of 50 μM. Pyruvate production, finally, was stimulated over the whole concentration range with a parabolic dependence. For the sake of comparison the experiments with alanine as the substrate were repeated using the classical uncoupler 2,4-dinitrophenol (experiments not shown). The effects of this compound were similar to the actions of juglone. Gluconeogenesis was 50% inhibited at a concentration of 17.9 μM. Ammonia release and urea production were also stimulated by 2,4-dinitrophenol, with half-maximal effects at 4.55 and 4.76 μM, respectively.

As shown in Fig 1, three-dimensional structural analyses were pe

As shown in Fig. 1, three-dimensional structural analyses were performed by the SkyScan software for the following regions: (1) 0.5-mm-long sections at proximal (25% of the bones’ length from their proximal ends), proximal/middle (37%), middle (50%) and distal (75%) sites in cortical bone of the tibiae; The parameters

evaluated included periosteally enclosed volume, bone volume and medullary volume in the regions of cortical bone and percent bone volume (bone volume/tissue volume), trabecular number and trabecular thickness in the trabecular regions. After scanning by μCT, the bones were dehydrated, cleared and embedded in methyl methacrylate as previously described [33]. Transverse segments were Ku-0059436 manufacturer obtained by cutting with an annular diamond saw. Images of calcein and alizarin-labelled

bone sections were visualized using the argon 488-nm laser and the HeNe 543-nm laser, respectively, of a confocal laser scanning microscope (LSM 510; Carl Zeiss MicroImaging GmbH, Jena, Germany) at similar regions as the μCT analysis. In the cortical regions, periosteal and endosteal labels and inter-label bone areas were measured as newly formed bone area at each region and normalized by total cortical bone area using ImageJ software (version 1.42; http://rsbweb.nih.gov/ij/) [30]. All data are shown as mean ± SE. Body weight was compared by one-way ANOVA. In the analysis of bones, the left and right sides in each group were compared by paired t-test, and then those in all three groups by one-way ANOVA followed by a post hoc Bonferroni or Dunnett T3 test. Statistical find more analysis was performed using SPSS for Windows (version

17.0; SPSS Inc., Chicago, IL), and p < 0.05 was considered as significant. As shown in Table 1 and Table 2, there were no statistically significant differences in body weight or longitudinal lengths of the tibiae, fibulae, femora, ulnae and radii. Analysis by μCT showed that in the cortical regions of the tibiae in the DYNAMIC + STATIC group, fantofarone periosteally enclosed and cortical bone volumes in the right loaded side were markedly higher than those of the contra-lateral non-loaded side at the proximal (+15.5 ± 1.0% and +35.9 ± 3.2%, respectively; p < 0.01), proximal/middle (+18.8 ± 0.6% and +32.7 ± 1.6%, respectively; p < 0.01) and middle (+13.3 ± 2.2% and +24.0 ± 2.2%, respectively; p < 0.01) sites ( Table 3; Fig. 2A). There were no significant differences at the distal site. Medullary volume in the cortical region of the right loaded tibiae was smaller compared to that of the left tibiae at the proximal site (− 10.2 ± 2.8%; p < 0.01). In contrast to these differences between loaded and non-loaded bones in the DYNAMIC + STATIC group, there were no significant differences in the periosteally enclosed bone volume, cortical bone volume or medullary volume between the left and right tibiae in the STATIC or NOLOAD group.

Furthermore, the results

Furthermore, the results 17-AAG mouse from the individual chromatograms (Fig. 1B) of the venoms clearly demonstrates the presence of isoforms of crotamine, crotapotin and phospholipase A2, of the crotoxin complex. The phospholipase A2 isoforms were found in more abundance, being observed in the majority of the chromatograms of the studied groups. Despite the

high variability in the concentrations, the chromatographic profiles did not present variation of venom proteins when considering the captivity time and ontogenetic variation. The RP-HPLC profile of the crotamine-positive and -negative venoms can be observed in Fig. 2A and B respectively. The contents of major peaks were determined by manual collection of the fraction followed by Edman degradation. In the case of crotapotin, the peptide was reduced with Dithiothreitol and alkylated with iodoacetamide (following standard protocols) and resubmitted to another chromatographic separation before individual sequencing of the peaks. The results on toxicity and coagulant activity are presented in Table 2 that shows LD50 statistical difference between males and females wild life groups. Statistical difference was observed also for clotting Z-VAD-FMK price time (CT) to newborns and reference venom group. The group of animals

inoculated with crotamine-positive venom presented hypertonicity of the hind paws followed by complete paralysis. The groups inoculated with crotamine-negative venom and control did not present any neurological activities. The monitoring of biological, biochemical and pharmacological activities of venoms should be one of the great concerns of institutions that produce antivenom, given that studies conducted in the last 50 years have demonstrated variation in these activities attributable

to sex, Montelukast Sodium age range, geographic origin, diet, captivity, season of the year and/or possible environmental changes (Ferreira et al., 2009, 2010a, in press; Campagner et al., in press; Schenberg, 1959b; Furtado et al., 2003; Pimenta et al., 2007; Calvete et al., 2009). This variability has direct implications on the antivenom type produced and, depending on the favorable response or lack thereof, on the treatment of snakebite patients (Chippaux et al., 1991; Warrel, 1997; Calvete et al., 2009). In the present study a large number of adult Cdt snakes (males and females) and newborns were evaluated, comparing the biological activities of animals newly born in the wild with those maintained for at least three years in captivity, finding a high variability in their venoms. Thus, the protein profile evaluated did not present a difference among the adult individuals corroborating Cárdenas et al. (1995) who found values of 76.9% in Brazilian snakes and 81.4% for Argentinean ones. On the other hand, the venom from the offspring showed a protein content of 60%, a value below that observed in adults (75%).

In the most active design for stereoselective bimolecular Diels-A

In the most active design for stereoselective bimolecular Diels-Alder reaction, the theozyme was grafted on a six bladed β-propeller scaffold (PDB id: 1E1A), the active site pocket of which was tightly filled by hydrophobic residues [ 31]. As nonspecific hydrophobic pockets did not catalyze the reaction, activity was not due to medium effect. Instead, close packing ensured the right orientation of the functional groups, in accord

with their sensitivity to mutations back to the original scaffold. An active retro-aldolase design employed a TIM barrel scaffold, where a hydrophobic pocket interacted with the aromatic part of the substrate [32••]. Applying a more diverse rotamer library for screening optimized the packing at the active site, which resulted in ∼10 fold improvement in kcat [ 33]. Hydrophobic AG14699 residues contributed Selleck ERK inhibitor to only ∼10 fold rate acceleration in RA61 retro-aldolase design via medium effect, by shifting the pKa of the Schiff-base lysine residue [ 34]. Packing also influenced the hydrogen-bonding network, which positioned the active site water molecules [ 32••]. In accord, simultaneous mutation of water coordinating residues caused almost 103 fold drop in catalytic activity [ 23]. In underpacked cases these water molecules remain rather mobile and decrease the preorganization of the enzymatic environment. Hence including a water-mediated hydrogen bond in retro-aldolase

designs with a catalytic His-Asp dyad increased the number of active variants [ 32••]. These observations illustrate that tighter

packing is not necessarily required for desolvation, instead it optimizes polar, preorganized environment. The low activity of the enzyme designs Molecular motor in various cases is due to dynamical rearrangements in the real enzyme, which deviate from the ideal catalytic configuration in small models. MD simulations on a retro-aldolase (RA22) found that nearly iso-energetic conformations in ab initio calculations significantly changed preference in heterogeneous protein environment [ 35]. An altered substrate conformation for example, rearranged the hydrogen-bonding network at the active site, which hampered the formation of the catalytic His233-Asp53 dyad. Another covalent retro-aldolase complex showed that wobbling of a catalytic lysine residue is compromising for activity by reducing efficiency of a proton transfer [ 23]. Dynamics can also distinguish between active and inactive designs. In MD simulations, the active KE70 Kemp eliminase exhibited minor deviations from the designed structure [ 26], while the catalytic dyad of the inactive KE38 adopted a significantly different geometry. Such instabilities, similarly to that of retro-aldolases [ 35] alter hydrogen-bonding geometry and perturb proton shuttling. Hence considering dynamic effects is critical in maintaining polar networks.