The new FLYA automated resonance assignment algorithm determines NMR chemical shift assignments on the basis of peak lists from any combination of multidimensional through-bond or through-space NMR experiments for proteins. Backbone and side-chain assignments can be determined. All experimental data are used simultaneously, thereby exploiting optimally the redundancy present in the input peak lists and circumventing potential pitfalls of assignment strategies in which results obtained in a given step remain fixed input data for subsequent steps. Instead of prescribing a specific assignment strategy, the FLYA resonance assignment algorithm requires only experimental peak lists and the primary structure of the protein, from which the peaks expected in a given spectrum can be generated by applying a set of rules, defined in a straightforward way by specifying through-bond or through-space magnetization transfer pathways. The algorithm determines the resonance assignment by finding an optimal mapping between the set of expected peaks that are assigned by definition but have unknown positions and the set of measured peaks in the input peak lists that are initially unassigned but have a known position in the spectrum. Using peak lists obtained by purely automated peak picking from the experimental spectra of three proteins, FLYA assigned correctly 96-99% of the backbone and 90-91% of all resonances that could be assigned manually. Systematic studies quantified the impact of various factors on the assignment accuracy, namely the extent of missing real peaks and the amount of additional artifact peaks in the input peak lists, as well as the accuracy of the peak positions. Comparing the resonance assignments from FLYA with those obtained from two other existing algorithms showed that using identical experimental input data these other algorithms yielded significantly (40-142%) more erroneous assignments than FLYA. The FLYA resonance assignment algorithm thus has the reliability and flexibility to replace most manual and semi-automatic assignment procedures for NMR studies of proteins.

Aggregation of organic dyes often has consequences on their spectroscopic properties in materials. Here, we study a new sterically hindered boron-dipyrromethene (BODIPY), with adamantyl moieties grafted for the first time on the BODIPY core. Its aggregation behavior was investigated in poly(methyl methacrylate) (PMMA) and on drop-casted films by monitoring absorption, fluorescence emission, relative quantum yield (ΦFluo,Rel), lifetime and time-resolved anisotropy. Aggregates only appear from 0.067 mol·L–1. A multicomponent analysis demonstrated that the aggregation process can be described by three distinguishable components which correspond to a monomer species (M) and J and H aggregates. The results also indicated a concentration frontier: when the dye concentration increased up to 0.29 mol·L–1, the concentration of M decreased in favor of the aggregates. ΦFluo,Rel is yet only divided by 5 compared to the dye in solution. Above 0.29 mol·L–1, an equilibrium between M and the J aggregates is established, showing meanwhile a steady ΦFluo,Rel. The J aggregates are found to be dimers, whereas the aggregation number is varying for the H aggregates. Analysis of fluorescence and anisotropy decays showed that the excitation energy was transferred from M to the J dimers, and very probably trapped by H aggregates.

Understanding flexibility and rigidity characteristics of biomolecules is a prerequisite for understanding biomolecular structural stability and function. Computational methods have been implemented that directly characterize biomolecular flexibility and rigidity by constraint network analysis. For deriving maximal advantage from these analyses, their results need to be linked to biologically relevant characteristics of a structure. Such links are provided by global and local measures ("indices") of biomolecular flexibility and rigidity. To date, more than 14 indices are available with sometimes overlapping or only vague definitions. We present concise definitions of these indices, analyze the relation between, and the scope and limitations of them, and compare their informative value. For this, we probe the structural stability of the calcium binding protein α-lactalbumin as a showcase, both in the "ground state" and after perturbing the system by changing the network topology. In addition, we introduce three indices for the first time that extend the application domain of flexibility and rigidity analyses. The results allow us to provide guidelines for future studies suggesting which of these indices could best be used for analyzing, understanding, and quantifying structural features that are important for biomolecular stability and function. Finally, we make suggestions for proper index notations in future studies to prevent the misinterpretation and to facilitate the comparison of results obtained from flexibility and rigidity analyses.