Imaging protein crystal growth behaviour in batch cooling crystallisation

The temporal and spatial growth behaviour of protein crystals, subject to different cooling strategies in protein crystallisation was investigated. Although the impact of temperature and cooling rate on crystal growth of small molecules was well documented, much less has been reported on their impact on the crystallisation of proteins. In this paper, an experimental set-up is configured to carry out such a study which involves an automatic temperature controlled hot-stage crystalliser fitted with a real-time imaging system. Linbro parallel crystallisation experiments(24-well plate) were also conducted to find the suitable initial conditions to be used in the hot-stage crystallisation experiments, including the initial concentration of HEW lysozyme solutions, precipitate concentration and pH value. It was observed that fast cooling rates at the early stage led to precipitates while slow cooling rates produced crystal nuclei, and very slow cooling rates, much smaller than for small molecules are critical to the growth of the nuclei and the crystals to a desired shape. The interesting results provide valuable insight as well as experimental proof of the feasibility and effectiveness of cooling as a means for achieving controlled protein crystallisation, compared with the evaporation approach which was widely used to grow single large crystals for X-ray diffraction study. Since cooling rate control can be easily achieved and has good repeatability, it suggests that large-scale production of protein crystals can be effectively achieved by manipulating cooling rates.

(Q)SAR modelling of nanomaterial toxicity:A critical review

There is increasing recognition that some nanomaterials may pose a risk to human health and the environment. Moreover, the industrial use of the novel engineered nanomaterials （ENMs） increases at a higher rate than data generation for hazard assessment; consequently, many of them remain untested. The large number of nanomaterials and their variants （e.g., different sizes and coatings） requiring testing and the ethical pressure towards nonanimal testing means that in a first instance, expensive animal bioassays are precluded, and the use of（quantitative） structure-activity relationships （（Q）SARs） models as an alter- native source of （screening） hazard information should be explored. （Q）SAR modelling can be applied to contribute towards filling important knowledge gaps by making best use of existing data, prioritizing the physicochemical parameters driving toxicity, and providing practical solutions for the risk assessment problems caused by the diversity of ENMs. This paper covers the core components required for successful application of （Q）SAR methods to ENM toxicity prediction, summarizes the published nano-（Q）SAR studies, and outlines the challenges ahead for nano-（Q）SAR modelling. It provides a critical review of （1） the present availability of ENM characterization/toxicity data, （2） the characterization of nanostructures that meet the requirements for （Q）SAR analysis, （3） published nano-（Q）SAR studies and their limitations, （4） in silico tools for （Q）SAR screening of nanotoxicity, and （5） prospective directions for the development of nano-（Q）SAR models.