During the years, adsorption has garnered considerable attention being one of the most cost-effective and efficient methods for separating contaminants out of liquid phase. A comprehensive understanding of adsorption mechanisms entails several crucial steps, including adsorbent characterization, batch and column adsorption tests, fitting of predefined kinetic and isotherm models, and meticulous thermodynamic analysis. These combined efforts serve to provide clarity and insights into the intricate workings of adsorption phenomena. However, the vast amount of literature published in the field each year is riddled with ill-considered model selections and incorrect parameter analyses. Therefore, the aim of this paper is to establish guidelines for the proper employment of these numerous kinetic, isotherm, and fixed-bed models in various applications. A thorough review has been undertaken, encompassing more than 45 kinetic models, 70 isotherm models, and 45 fixed bed models available hitherto, with their classification determined based on the adsorption mechanisms expounded within each of them. Moreover, five general approaches for modifying fixed-bed models were provided. The physical meanings, assumptions, and interconversion relationships of the models were discussed in detail, along with the information criterion used to evaluate their validity. In addition to commonly used activation energy and Gibbs energy analysis, the methods for calculating site energy distribution were also summarized.

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Protein stability is crucial in enzymatic catalysis. To improve the efficiency in the searching for thermostablizing mutations, we applied a sequence consensus approach focusing on dimeric interface residues of ketoreductase ChKRED20. The strategy returned a success rate of 43%, revealing 9 beneficial mutations from 21 candidates with improved kinetic or thermodynamic stability. Several combinatorial mutants were then constructed, and mutant M8K displayed the highest thermostability, with a melting temperature (Tm) of 89 °C and a half-inactivation temperature (T50) of 93.4 °C, both of over 35 °C increase compared to the wild-type. M8K could remain stable for at least 7 days at its optimal reaction temperature of 55 °C. Its inactivation half-life (t1/2) was 110 min at 90 °C, while the wild-type was 18.6 min at 60 °C. The results were interpreted in the context of structural and molecular dynamic simulation analysis, which revealed the addition of intramolecular interactions, decreased conformational flexibility and increased compactness, all in agreement with the observed effect.

The 2020 consensus guidelines for vancomycin therapeutic monitoring recommend using Bayesian estimation targeting the ratio of the area under the curve over 24 hours to minimum inhibitory concentration as an optimal approach to individualize therapy in pediatric patients. To support institutional guideline implementation in children, the objective of this study was to comprehensively assess and compare published population-based pharmacokinetic (PK) vancomycin models and available Bayesian estimation tools, specific to neonatal and pediatric patients.
PubMed and Embase databases were searched from January 1994 to December 2020 for studies in which a vancomycin population PK model was developed to determine clearance and volume of distribution in neonatal and pediatric populations. Available Bayesian software programs were identified and assessed from published articles, software program websites, and direct communication with the software company. In the present review, 14 neonatal and 20 pediatric models were included. Six programs (Adult and Pediatric Kinetics, BestDose, DoseMeRx, InsightRx, MwPharm++, and PrecisePK) were evaluated.
Among neonatal models, Frymoyer et al and Capparelli et al used the largest PK samples to generate their models, which were externally validated. Among the pediatric models, Le et al used the largest sample size, with multiple external validations. Of the Bayesian programs, DoseMeRx, InsightRx, and PrecisePK used clinically validated neonatal and pediatric models.
To optimize vancomycin use in neonatal and pediatric patients, clinicians should focus on selecting a model that best fits their patient population and use Bayesian estimation tools for therapeutic area under the -curve-targeted dosing and monitoring.

BACKGROUND: Enzymatic quantification of creatinine has become an essential method for clinical evaluation of renal function. Although creatinase (CR) is frequently used for this purpose, its poor thermostability severely limits industrial applications. Herein, we report a novel creatinase from Alcaligenes faecalis (afCR) with higher catalytic activity and lower KM value, than currently used creatinases. Furthermore, we developed a non-biased phylogenetic consensus method to improve the thermostability of afCR.
RESULTS: We applied a non-biased phylogenetic consensus method to identify 59 candidate consensus residues from 24 creatinase family homologs for screening afCR mutants with improved thermostability. Twenty-one amino acids of afCR were selected to mutagenesis and 11 of them exhibited improved thermostability compared to the parent enzyme (afCR-M0). Combination of single-site mutations in sequential screens resulted in a quadruple mutant D17V/T199S/L6P/T251C (M4-2) which showed ~ 1700-fold enhanced half-life at 57 °C and a 4.2 °C higher T5015 than that of afCR-M0. The mutant retained catalytic activity equivalent to afCR-M0, and thus showed strong promise for application in creatinine detection. Structural homology modeling revealed a wide range of potential molecular interactions associated with individual mutations that contributed to improving afCR thermostability.
CONCLUSIONS: Results of this study clearly demonstrated that the non-biased-phylogenetic consensus design for improvement of thermostability in afCR is effective and promising in improving the thermostability of more enzymes.

Exponentially increasing protein sequence data enables artificial enzyme design using sequence-based protein design methods, including full-consensus protein design (FCD). The success of artificial enzyme design is strongly dependent on the nature of the sequences used. Hence, sequences must be selected from databases and curated libraries prepared to enable a successful design by FCD. In this study, we proposed a selection approach regarding several key residues as sequence motifs. We used l-threonine 3-dehydrogenase (TDH) as a model to test the validity of this approach. In the classification, four residues (143, 174, 188, and 214) were used as key residues. We classified thousands of TDH homologous sequences into five groups containing hundreds of sequences. Utilizing sequences in the libraries, we designed five artificial TDHs by FCD. Among the five, we successfully expressed four in soluble form. Biochemical analysis of artificial TDHs indicated that their enzymatic properties vary; half of the maximum measured enzyme activity (t1/2) and activation energies were distributed from 53 to 65 °C and from 38 to 125 kJ/mol, respectively. The artificial TDHs had unique kinetic parameters, distinct from one another. Structural analysis indicates that consensus mutations are mainly introduced in the secondary or outer shell. The functional diversity of the artificial TDHs is due to the accumulation of mutations that affect their physicochemical properties. Taken together, our findings indicate that our proposed approach can help generate artificial enzymes with unique enzymatic properties.

The alkene-isocyanate cycloaddition method affords β-lactams from glycals with high regio- and stereoselectivity, but the factors that determine substrate reactivity are poorly understood. Thus, we synthesized a library of 17 electron-rich alkenes (glycals) with varied protecting groups to systematically elucidate the factors that influence their reactivity toward the electron-poor trichloroacetyl isocyanate. The experimentally determined reaction rates exponentially correlate with the computationally determined highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap and natural bond orbital (NBO) valence energies. The electron-withdrawing ability of the protecting groups, but not bulk, impacts the electron density of the glycal allyloxocarbenium system when oriented pseudo-axially (i.e., stereoelectronics). In this conformation, ring σC-O* orbitals oriented antiperiplanar to the allyloxocarbenium system decrease glycal reactivity via negative hyperconjugation as protecting group electron withdrawal increases. Transition-state calculations reveal that protecting group stereoelectronics direct the reaction to proceed via an asynchronous one-step mechanism through a zwitterionic species. The combined experimental and computational findings, along with experimental validation on an unknown glycal, provide insight on the reaction mechanism and the role of distant protecting groups in glycal reactivity. Together, these studies will aid in the synthesis of new β-lactam antibiotics, β-lactamase inhibitors, and bicyclic carbohydrate-β-lactam monomers prepared by the alkene-isocyanate method.

γ-Aminobutyrate (GABA) is an important bioactive compound synthesized through decarboxylation of L-glutamate by the glutamate decarboxylase (GAD). In this study, stabilized variants of the GAD from Lactobacillus brevis were constructed by consensus mutagenesis. Using Consensus Finder ( http://cbs-kazlab.oit.umn.edu/ ), eight positions with the most prevalent amino acid (over 60% threshold) among the homologous family members were identified. Subsequently, these eight residues were individually mutated to match the consensus sequence using site-directed mutagenesis. Compared to the wild-type, T383K variant displayed the largest shift in thermostability among the single variants, with a 3.0 °C increase in semi-inactivation temperature (T5015), a 1.7-fold improvement of half-life (t1/2) at 55 °C, and a 1.2-fold improvement of t1/2 at 37 °C, respectively, while its catalytic efficiency (kcat/Km) was reduced. To obtain the mutant with improvement in both thermostability and catalytic activity, we performed a site-saturation mutation at T383. Notably, mutants T383V and T383G exhibited an increasement in thermostability and kcat/Km than that of wild-type. This study not only emphasizes the value of consensus mutagenesis for improving the thermostability of GAD but also sheds a powerful guidance to study the thermal stability of other enzymes.

The link between food and human health is increasingly a topic of interest. One avenue of study has been to assess food disintegration and interactions within the gastrointestinal tract. In vitro digestion models have been widely used to overcome the constrictions associated with in vivo methodology. The COST Action INFOGEST developed an international, harmonised protocol for static simulation of digestion in the upper gastrointestinal tract of adults. This protocol is widely used; however, it is restricted to providing end-point assessment without considering the possible structural changes. On the other hand, there are dynamic models that provide more physiologically relevant data but are expensive and difficult to access. There is a gap between these models. The method outlined in this article provides an intermediate model; it builds upon the harmonised static model and now includes crucial kinetic aspects associated with the gastric phase of digestion, including gradual acidification, fluid and enzyme secretion and emptying. This paper provides guidance and standardised recommendations of a physiologically relevant semi-dynamic in vitro simulation of upper gastrointestinal tract digestion, with particular focus on the gastric phase. Adaptations of this model have already been used to provide kinetic data on nutrient digestion and structural changes during the gastric phase that impact on nutrient absorption. Moreover, it provides a simple tool that can be used in a wide range of laboratories.

Kinetic models are nowadays a basic tool to ensure food safety. Most models used in predictive microbiology have model parameters, whose precision is crucial to provide meaningful predictions. Kinetic parameters are usually estimated based on experimental data, where the experimental design can have a great impact on the precision of the estimates. In this sense, Optimal Experiment Design (OED) applies tools from optimization and information theory to identify the most informative experiment under a set of constrains (e.g. mathematical model, number of samples, etc). In this work, we develop a methodology for the design of optimal isothermal inactivation experiments. We consider the two dimensions of the design space (time and temperature), as well as a temperature-dependent maximum duration of the experiment. Functions for its application have been included in the bioOED R package. We identify design patterns that remain optimum regardless of the number of sampling points for three inactivation models (Bigelow, Mafart and Peleg) and three model microorganisms (Escherichia coli, Salmonella Senftenberg and Bacillus coagulans). Samples at extreme temperatures and close to the maximum duration of the experiment are the most informative. Moreover, the Mafart and Peleg models require some samples at intermediate time points due to the non-linearity of the survivor curve. The impact of the reference temperature on the precision of the parameter estimates is also analysed. Based on numerical simulations we recommend fixing it to the mean of the maximum and minimum temperatures used for the experiments. The article ends with a discussion presenting guidelines for the design of isothermal inactivation experiments. They combine these optimum results based on information theory with several practical limitations related to isothermal inactivation experiments. The application of these guidelines would reduce the experimental burden required to characterize thermal inactivation.