The structurally disordered nature of intrinsically disordered proteins and intrinsically disordered regions in large proteins (IDPRs) makes them unique among biomolecules and provides them with distinct advantages, especially in interactions with their binding/interaction partners. Our current knowledge conveys that IDPRs interact with their partners via numerous different modes and mechanisms (including combinations). The selectivity and specificity in the intermolecular interactions of IDPRs are key to the activation and regulation of nucleation and growth of different types of supramolecular assemblies that are key to various functions (and dysfunctions in disease conditions) of IDPRs.
The research field observing the physical phenomena where IDPs play key roles has exploded on many fronts in recent years with relatively limited mechanistic understanding of the driving forces and druggable interactions. With ever-growing advances in computing hardware, computational molecular science holds a great promise in advancing our thermodynamic, kinetic, and structural understanding of biomolecular assemblies of IDPRs. Especially with the rise of machine learning algorithms, a breadth of new (or improved) models, sampling, and analysis techniques have become readily available to be tested systematically.
The aim of this Research Topic is to cover novel promising computational developments aiming to interrogate IDPRs and their assemblies. In this collection, we welcome original research articles that feature including (but are not limited to)
• applications/developments of multiscale modeling and advanced sampling techniques for IDPR assemblies including liquid-like condensates of IDPRs, disease-related aggregates, complex coacervates of IDPRs with nucleic acids, mesoscopic clusters of IDPRs, and so on,
• applications/developments of novel analysis techniques to detect the role of intrinsic disorder and/or novel interaction modes of IDPRs in their assemblies,
• combined experiment/simulation/theory studies of IDPR assemblies.
We also welcome review articles that focus on including (but are not limited to) recent developments in machine learning methodologies, multiscaling frameworks, and systematic database analyses.
Please note that all studies with a specific focus on bioinformatics approaches should be submitted through Frontiers in Bioinformatics.
The structurally disordered nature of intrinsically disordered proteins and intrinsically disordered regions in large proteins (IDPRs) makes them unique among biomolecules and provides them with distinct advantages, especially in interactions with their binding/interaction partners. Our current knowledge conveys that IDPRs interact with their partners via numerous different modes and mechanisms (including combinations). The selectivity and specificity in the intermolecular interactions of IDPRs are key to the activation and regulation of nucleation and growth of different types of supramolecular assemblies that are key to various functions (and dysfunctions in disease conditions) of IDPRs.
The research field observing the physical phenomena where IDPs play key roles has exploded on many fronts in recent years with relatively limited mechanistic understanding of the driving forces and druggable interactions. With ever-growing advances in computing hardware, computational molecular science holds a great promise in advancing our thermodynamic, kinetic, and structural understanding of biomolecular assemblies of IDPRs. Especially with the rise of machine learning algorithms, a breadth of new (or improved) models, sampling, and analysis techniques have become readily available to be tested systematically.
The aim of this Research Topic is to cover novel promising computational developments aiming to interrogate IDPRs and their assemblies. In this collection, we welcome original research articles that feature including (but are not limited to)
• applications/developments of multiscale modeling and advanced sampling techniques for IDPR assemblies including liquid-like condensates of IDPRs, disease-related aggregates, complex coacervates of IDPRs with nucleic acids, mesoscopic clusters of IDPRs, and so on,
• applications/developments of novel analysis techniques to detect the role of intrinsic disorder and/or novel interaction modes of IDPRs in their assemblies,
• combined experiment/simulation/theory studies of IDPR assemblies.
We also welcome review articles that focus on including (but are not limited to) recent developments in machine learning methodologies, multiscaling frameworks, and systematic database analyses.
Please note that all studies with a specific focus on bioinformatics approaches should be submitted through Frontiers in Bioinformatics.
