Despite the continuous advances of the canonical experimental methods for protein structure determination, they all still possess significant limitations, which became more evident when applied to challenge systems. This is the case for large and transient macromolecular complexes, biomolecular machines, very flexible and intrinsically disordered proteins, or domains. The rate of success in obtaining a protein structure is often inversely related to protein size and flexibility. Thus, the predictions and measurements of protein dynamics are essential to the efficient characterization of structural ensembles.
In this sense, experimental structural information (from various sources and resolutions) may be joined through an integrative modeling approach, resulting in a more accurate model - or an ensemble of models. For this, experiments on and predictions of how subunits interact allow one to obtain spatial restraints, which help the determination of the protein molecular architecture. Hence, hybrid simulations guided from experimental data were proven to efficiently sample an ensemble of states relevant to the function.
In this Research Topic, we welcome contributors to submit their original research manuscripts, mini-reviews, and Perspectives on the developments and applications of experimental and computational strategies regarding integrative structural approaches. Including, integrative modeling, hybrid simulations, and experimental techniques such as nuclear magnetic resonance (NMR), small-angle x-ray scattering (SAXS), X-ray crystallography, also cryogenic electron microscopy (cryo-EM). Areas to be covered in this Research Topic may include, but are not limited to:
• Protein structure prediction: bayesian, ab initio and comparative studies.
• Protein interactions: docking, oligomerization, and co-evolution analysis.
• Computational simulations guided from experimental data (SAXS, cryo-EM, NMR, crosslinking, hydrogen-deuterium exchange, atomic force microscopy, and fluorescence resonance energy transfer).
• de novo structural modeling, fitting, and refinement of cryo-EM maps.
• Protein dynamics: allostery, conformational changes, ensembles, and energetics.
• Flexibility and disorder: flexible linkers and intrinsically disordered proteins/domains.
• Roles of water and membranes on the assembly and activity of macromolecules.
Despite the continuous advances of the canonical experimental methods for protein structure determination, they all still possess significant limitations, which became more evident when applied to challenge systems. This is the case for large and transient macromolecular complexes, biomolecular machines, very flexible and intrinsically disordered proteins, or domains. The rate of success in obtaining a protein structure is often inversely related to protein size and flexibility. Thus, the predictions and measurements of protein dynamics are essential to the efficient characterization of structural ensembles.
In this sense, experimental structural information (from various sources and resolutions) may be joined through an integrative modeling approach, resulting in a more accurate model - or an ensemble of models. For this, experiments on and predictions of how subunits interact allow one to obtain spatial restraints, which help the determination of the protein molecular architecture. Hence, hybrid simulations guided from experimental data were proven to efficiently sample an ensemble of states relevant to the function.
In this Research Topic, we welcome contributors to submit their original research manuscripts, mini-reviews, and Perspectives on the developments and applications of experimental and computational strategies regarding integrative structural approaches. Including, integrative modeling, hybrid simulations, and experimental techniques such as nuclear magnetic resonance (NMR), small-angle x-ray scattering (SAXS), X-ray crystallography, also cryogenic electron microscopy (cryo-EM). Areas to be covered in this Research Topic may include, but are not limited to:
• Protein structure prediction: bayesian, ab initio and comparative studies.
• Protein interactions: docking, oligomerization, and co-evolution analysis.
• Computational simulations guided from experimental data (SAXS, cryo-EM, NMR, crosslinking, hydrogen-deuterium exchange, atomic force microscopy, and fluorescence resonance energy transfer).
• de novo structural modeling, fitting, and refinement of cryo-EM maps.
• Protein dynamics: allostery, conformational changes, ensembles, and energetics.
• Flexibility and disorder: flexible linkers and intrinsically disordered proteins/domains.
• Roles of water and membranes on the assembly and activity of macromolecules.