Design considerations and computer modeling related to the development of molecular scaffolds and peptide mimetics for combinatorial chemistry

Summary A critical issue in drug discovery utilizing combinatorial chemistry as part of the discovery process is the choice of scaffolds to be used for a proper presentation, in a three-dimensional space, of the critical elements of structure necessary for molecular recognition (binding) and information transfer (agonist/ antagonist). In the case of polypeptide ligands, considerations related to the properties of various backbone structures (-helix, -sheets, etc.; , space) and those related to three-dimensional presentation of side-chain moieties (topography; (chi) space) must be addressed, although they often present quite different elements in the molecular recognition puzzle. We have addressed aspects of this problem by examining the three-dimensional structures of chemically different scaffolds at various distances from the scaffold to evaluate their putative diversity. We find that chemically diverse scaffolds can readily become topographically similar. We suggest a topographical approach involving design in chi space to deal with these problems.     

Learning to align organizational design and data

The relationship between organizational learning and organizational design is explored. In particular, we examine the information processing aspects of organizational learning as they apply to a two-valued decision making task and the relation of such aspects to organizational structure. Our primary contribution is to extend Carley's (1992) model of this process. The original model assumes that all data input into the decision making processes are of equal importance or weight in determining the correct overall organizational decision. The extension described here allows for the more natural situation of non-uniform weights of evidence. Further extensions to the model are also discussed. Such organizational learning performance measures provide an interesting framework for analyzing the recent trend towards flatter organizational structures. This research suggests that flatter structures are not always better, but rather that data environment, ultimate performance goals, and relative need for speed in learning can be used to form a contingency model for choosing organizational structure.     

正交试验选择组织电极的最佳分析条件

本文用正交试验法对花椰菜组织Ｌ－抗坏血酸传感器和香蕉组织儿茶酚类化合物传感器的分析条件进行了优化，通过与单因子分析方法及４种儿茶酚类化合物之间正交试验结果的比较，说明用正交试验选择组织传感器的最佳分析条件，在少量的试验次数内，得到较多的分析实验信息，是一种较理想的试验方法。     

Preprocessing of rotamers for protein design calculations

We have developed a process that significantly reduces the number of rotamers in computational protein design calculations. This process, which we call Vegas, results in dramatic computational performance increases when used with algorithms based on the dead-end elimination (DEE) theorem. Vegas estimates the energy of each rotamer at each position by fixing each rotamer in turn and utilizing various search algorithms to optimize the remaining positions. Algorithms used for this context specific optimization can include Monte Carlo, self-consistent mean field, and the evaluation of an expression that generates a lower bound energy for the fixed rotamer. Rotamers with energies above a user-defined cutoff value are eliminated. We found that using Vegas to preprocess rotamers significantly reduced the calculation time of subsequent DEE-based algorithms while retaining the global minimum energy conformation. For a full boundary design of a 51 amino acid fragment of engrailed homeodomain, the total calculation time was reduced by 12-fold.     

Optimisation of the chlorthalidone chiral separation by capillary electrochromatography using an achiral stationary phase and cyclodextrin in the mobile phase

The separation of chlorthalidone enantiomers in capillary electrochromatography on an achiral stationary phase when adding a chiral selector, hydroxypropyl-β-cyclodextrin, to the mobile phase, was optimised. The goal was to investigate the feasibility of modelling retention times and resolution when during the optimisation procedure regular replacement of columns is required due to their fragility. Therefore, it is essential that the packing procedure delivers reproducible columns. The optimisation of an existing chlorthalidone separation was chosen as case study. The influence of two factors, chiral selector concentration and organic modifier content, on the responses was modelled. The experiments performed prior to modelling were defined by a central composite design. Results on different columns, obtained under identical experimental conditions, were found comparable and thus modelling was possible in situations where several columns were required to complete a design. A second-order polynomial model was built for both responses. Optimal separations were also predicted using Derringer’s desirability functions. The optimum was found at 33 mM cyclodextrin and 16% (v/v) acetonitrile on two types of columns (with different packing times) leading to a strong reduction in analysis time for an equally good separation compared to the initial conditions. Measured and predicted responses were found comparable, indicating that acceptable models were obtained.     

De novo designed contrasteric Diels-Alder reactions of 5-(2-oxazolynyl)-1,2,3,4,5-pentamethylcyclopentadiene

5-(2-Oxazolynyl)cyclopentadiene was designed on the basis of the orbital mixing rule to react with dienophiles with highly contrasteric manner in Diels-Alder reactions. The design was validated by the synthesis and reactions of the corresponding pentamethyl derivative, 5-(2-oxazolynyl)-1,2,3,4,5-pentamethylcyclopentadiene, to afford the products with the ratios of syn/anti=89-93/11-7.     

Optimisation of chiral separation of omeprazole and one of its metabolites on immobilized α1-acid glycoprotein using chemometricsglycoprotein using chemometrics

Summary A strategy for the optimisation of direct chiral separation of omeprazole and a metabolite, hydroxi-omeprazole, in reversed phase liquid chromatography is described. A factorial design was used, where mobile phase pH, concentration of a mobile phase modifier, ionic strength and column temperature were tested as the variables and enantioselective retention, column efficiency and asymmetry factor as the responses. The experimental results were evaluated with multivariate analyses, which demonstrated that the column temperature and content of mobile phase acetonitrile were by far the most important variables. The enantiomers of omeprazole and one of its metabolites were baseline resolved within 15 minutes. The optimised chromatographic system was used for a separation of the enantiomers of omeprazole and its main metabolite in a patient plasma sample.     

Exact rotamer optimization for protein design

Computational methods play a central role in the rational design of novel proteins. The present work describes a new hybrid exact rotamer optimization (HERO) method that builds on previous dead-end elimination algorithms to yield dramatic performance enhancements. Measured on experimentally validated physical models, these improvements make it possible to perform previously intractable designs of entire protein core, surface, or boundary regions. Computational demonstrations include a full core design of the variable domains of the light and heavy chains of catalytic antibody 48G7 FAB with 74 residues and 10(128) conformations, a full core/boundary design of the beta1 domain of protein G with 25 residues and 10(53) conformations, and a full surface design of the beta1 domain of protein G with 27 residues and 10(60) conformations. In addition, a full sequence design of the beta1 domain of protein G is used to demonstrate the strong dependence of algorithm performance on the exact form of the potential function and the fidelity of the rotamer library. These results emphasize that search algorithm performance for protein design can only be meaningfully evaluated on physical models that have been subjected to experimental scrutiny. The new algorithm greatly facilitates ongoing efforts to engineer increasingly complex protein features.     

A statistical model for the optimization of dsc performance in the evaluation of drugs for preformulation studies

Differential scanning calorimetry (DSC) is a thermal analytical tool for preformulation studies. Extrapolated melting temperature (T_P) and heat of fusion (ΔH_f) can be used as parameters for optimizing the DSC performance. Two model pharmaceuticals acetaminophen and nicotinamide are used in this study. Using a factorial design for the experimental model and matrix analysis the results, the effect of sample mass, heating rate and the nitrogen flow rate were evaluated on the ΔH_f values and T_P values. Two levels for each of the procedural variables were used as a balanced experimental design with two sample sizes, two heating rates and two nitrogen flow rates. It was found that the change in the heating rate caused significant changes in the ΔH_f values but not the T_p values for acetaminophen. However, no significant effect was found for the T_p value but ΔH_f value was affected to a certain extent for nicotinamide.     

微波消解-火焰原子吸收光谱法测定污泥中铅

研究了微波消解-火焰原子吸收光谱法测定污泥中铅。应用正交试验设计法确定了微波消解试样的最佳条件。该法与传统敞口消解法测定结果吻合。样品测定结果的相对标准偏差（n=6）为1.5％～4．7％，加标回收率为93．0%-106．2％。该方法省时省酸，减少环境污染，改善了工作环境。