Knowledge of the three-dimensional structure of macromolecules is an incredible source for understanding biological processes. It would allows us, for example, to apprehend an enzymatic reaction, even to be able to define how to modify it and propose approaches for drug design, etc. Nonetheless, experimentally determined structures of specific macromolecules or their biologically relevant complex forms are often not available. Hence, computational approaches have been developed to generate atomic models of macromolecules, complexes with other macromolecules, and complexes with small ligands. Some models also use experimental data as restraints in their simulations. These modeling approaches have limitations, but are also of impressive interest ranging from basic research to applied biotechnology, biomedicine and drug design.
With the increasing amount of structural information (coming from X-ray crystallography, Nuclear Magnetic Resonance or cryogenic electron microscopy), the computational approaches such as molecular modelling, molecular dynamics, docking and chemoinformatics, are often required for better interpretation of data. All these in silico methodologies are complex, have limitations and must be used with appropriate statistical and quality measures. The objective of this Research Topic is to bring together work using robust and recent computational methodologies, which relates to the computational analysis of structures and complexes. We are also interested in work exploring new developments and applications that integrate docking approaches and complex experimental data such as cryo-EM.
For this Research Topic, we welcome contributions of research articles and reviews covering recent computational methodological developments in the following areas of Structural Bioinformatics, Cheminformatics and Computational Biology:
• Analysis of macromolecular structure-function relationships, especially protein structures that are ordered or disordered
• Molecular dynamics simulations to comprehend protein flexibility, dynamics and folding. These MDs can be classical all atoms, coarse-grained, or using enhanced sampling approaches such as Replica-Exchange Molecular Dynamics or metadynamics
• Docking approaches to predict binding of natural or non-natural ligands and answering biological or biotechnological questions such as drug design
• Integration of experimental data restraints in macromolecular structure modeling
Knowledge of the three-dimensional structure of macromolecules is an incredible source for understanding biological processes. It would allows us, for example, to apprehend an enzymatic reaction, even to be able to define how to modify it and propose approaches for drug design, etc. Nonetheless, experimentally determined structures of specific macromolecules or their biologically relevant complex forms are often not available. Hence, computational approaches have been developed to generate atomic models of macromolecules, complexes with other macromolecules, and complexes with small ligands. Some models also use experimental data as restraints in their simulations. These modeling approaches have limitations, but are also of impressive interest ranging from basic research to applied biotechnology, biomedicine and drug design.
With the increasing amount of structural information (coming from X-ray crystallography, Nuclear Magnetic Resonance or cryogenic electron microscopy), the computational approaches such as molecular modelling, molecular dynamics, docking and chemoinformatics, are often required for better interpretation of data. All these in silico methodologies are complex, have limitations and must be used with appropriate statistical and quality measures. The objective of this Research Topic is to bring together work using robust and recent computational methodologies, which relates to the computational analysis of structures and complexes. We are also interested in work exploring new developments and applications that integrate docking approaches and complex experimental data such as cryo-EM.
For this Research Topic, we welcome contributions of research articles and reviews covering recent computational methodological developments in the following areas of Structural Bioinformatics, Cheminformatics and Computational Biology:
• Analysis of macromolecular structure-function relationships, especially protein structures that are ordered or disordered
• Molecular dynamics simulations to comprehend protein flexibility, dynamics and folding. These MDs can be classical all atoms, coarse-grained, or using enhanced sampling approaches such as Replica-Exchange Molecular Dynamics or metadynamics
• Docking approaches to predict binding of natural or non-natural ligands and answering biological or biotechnological questions such as drug design
• Integration of experimental data restraints in macromolecular structure modeling
