Single molecule force spectroscopy is a useful technique for investigating mechanically induced protein unfolding and refolding under reduced forces by monitoring the end-to-end distance of the protein. The data is often interpreted via a "two-state" model based on the assumption that the end-to-end distance alone is a good reaction coordinate and the thermodynamic behavior is then ascribed to the free energy as a function of this one reaction coordinate. In this paper, we determined the free energy surface (PMF) of GB1 protein from atomistic simulations in explicit solvent under different applied forces as a function of two collective variables (the end-to-end-distance, and the fraction of native contacts ρ). The calculated 2-d free energy surfaces exhibited several distinct states, or basins, mostly visible along the ρ coordinate. Brownian dynamics (BD) simulations on the smoothed free energy surface show that the protein visits a metastable molten globule state and is thus a three state folder, not the two state folder inferred using the end-to-end distance as the sole reaction coordinate. This study lends support to recent experiments that suggest that GB1 is not a two-state folder.

The development of quantitative structure property relationships (QSPRs) with good extrapolation capabilities for high carbon number (n C ) substances in homologous series is considered. Based on the available experimental data, molecular descriptors collinear with a particular property are identified. Among these, the ones whose behavior at the limit n C ! 1 is similar to the properties behavior, are eventually used for prediction. A linear QSPR in terms of the selected descriptor with an optional additional correction term which exponentially decays with n C can be developed. The confidence level in the property prediction can be adjusted to the quantity, precision, and reliability of the available data. The proposed method has been tested by developing QSPRs for predicting T C and P C for several homologous series and T m for the nalkane series. In all cases, the QSPRs developed represent the available experimental data satisfactorily and converge to theoretically accepted values for n C ! 1. V V C 2010 American Institute of Chemical Engineers AIChE J, 57: [423][424][425][426][427][428][429][430][431][432][433] 2011

The international transfer of human biomaterial and data has become a prerequisite for collaborative biomedical research to be successful. However, although a national legal framework for 'biobanking' has already been formulated in many countries, little is known about how an international exchange of data and samples might affect the legal position of national biobanks and their donors. The German Telematics Platform and the Competence Network 'Congenital Heart Defects' jointly instigated a project (BMB-EUCoop) to (i) identify and assess the legal risks ensuing for biobanks and their donors in the context of Europewide research collaborations, (ii) devise practical recommendations to minimize or avoid these risks, and (iii) provide generic informational text, contracts and agreements to facilitate their practical implementation. Four different countries were included in the study; namely, the UK, Netherlands, Austria and Switzerland. The results of the study indicate that the degree of similarity between legal systems in different countries varies according to the respective field of jurisdiction. Although personality and property rights have long been enshrined in virtually identical pieces of law, the applicable medical professional regulations were found to be somewhat heterogeneous. Furthermore, clear-cut differences were often found to be lacking between regulations that reflect either 'soft law' or the nationally binding 'hard law' that has emerged from it. In view of the potential ambiguities, the experts uniformly concluded that the rights and interests of national (in this case, German) biobanks and their donors would be best protected by explicitly addressing any uncertainties in formal contractual agreements.

The use of databases containing thousands of molecular descriptors, including 3-D descriptors, for predicting physical properties is discussed. It is shown that the use of 3-D descriptors for property prediction via quantitative structure property relations (QSPR) limits considerably their applicability, as 3-D structure files must be obtained from the same reliable source for all predictive and target compounds. A modified targeted QSPR (TQSPR) algorithm is presented, which includes a new technique for selecting training sets belonging to the homologous series of the target compound (if such compounds are available in the database). The method is employed for predicting seven properties for five homologous series. It is shown that most properties can be predicted on experimental error level, using training sets of 10 compounds and a maximum of 2 (non 3-D) descriptors. The exclusion of the 3-D descriptors enhances considerably the applicability of the TQSPRs, and the use of a small number of descriptors reduces the probability of "chance correlations".