Optimization of Algorithms for Modeling Protein Structural Transitions from Sparse Long-Range Spin-Label Distance Constraints

Protein ensemble modeling and analysis with MMMx

Proteins, especially of eukaryotes, often have disordered domains and may contain multiple folded domains whose relative spatial arrangement is distributed. The MMMx ensemble modeling and analysis toolbox (https://github.com/gjeschke/MMMx) can support the design of experiments to characterize the distributed structure of such proteins, starting from AlphaFold2 predictions or folded domain structures. Weak order can be analyzed with reference to a random coil model or to peptide chains that match the residue-specific Ramachandran angle distribution of the loop regions and are otherwise unrestrained. The deviation of the mean square end-to-end distance of chain sections from their average over sections of the same sequence length reveals localized compaction or expansion of the chain. The shape sampled by disordered chains is visualized by superposition in the principal axes frame of their inertia tensor. Ensembles of different sizes and with weighted conformers can be compared based on a similarity parameter that abstracts from the ensemble width.

Integrative ensemble modeling of proteins and their complexes with distance distribution restraints

Many proteins and protein complexes exhibit regions that are intrinsically disordered. Whereas an arsenal of techniques exists to characterize structured proteins or protein regions, characterization of the vast conformational space occupied by intrinsically disordered regions remains a challenging task due the ensemble-averaging nature of many techniques that provide mean value restraints. More representative information can be gained in the form of distribution restraints, such as EPR-derived distance distributions. Previously we developed the ensemble modeling tool MMM, where we partition the macromolecule into structured and unstructured domains and utilize an integrative structural approach with a focus on EPR-derived distance restraints. Here we present the successor program of MMM: MMMx. All the modeling functionality was ported to MMMx and is now accessed by a uniform script format, allowing to combine the different modules at will to modeling pipelines. During the conception of MMMx many of the tools were improved or updated. We discuss the general functionality of MMMx and its modules, and illustrate some of the modeling tools by application examples.

MMM: A toolbox for integrative structure modeling

Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples.

The Role of ESR Spectroscopy in Advancing Catalytic Science: Some Recent Developments

Recent progress is surveyed in regard to the importance of molecular species containing unpaired electrons in catalytic systems, as revealed using ESR spectroscopy. The review begins with studies of enzymes and their role directly in biological systems, and then discusses investigations of various artificially created catalysts with potential human and environmental significance, including zeolites. Among the specific types of catalytic media considered are those for photocatalysis, water splitting, the degradation of environmental pollutants, hydrocarbon conversions, fuel cells, ionic liquids and sensor devices employing graphene. Studies of muonium-labelled radicals in zeolites are also reviewed, as a means for determining the dynamics of transient radicals in these nanoporous materials.

Unpaired electrons as probes of catalytic systems

An overview is provided of the importance of molecular species containing unpaired electrons in catalytic systems, as revealed using ESR spectroscopy. The review aims to demonstrate the considerable extent of scientific progress that has been made in this broad topic during the past few decades. Studies of catalytically active surfaces, including zeolites, are surveyed, and the detection of radical species, formed as intermediates in their reactions, using matrix isolation and spin-trapping techniques. Radical cation formation in zeolites is discussed, and the employment of muon spin rotation and relaxation techniques to study the mobility of labelled radicals in various porous and catalytic media. Among the specific types of catalytic media considered are those for photocatalysis, water splitting, degradation of environmental pollutants, hydrocarbon conversions, fuel cells and sensor devices employing graphene. The review concludes with recent developments in the study of enzymes and their reactions, using ESR-based methods.