About this Research Topic
The macromolecules and other molecule interactions rely on covalent and non-covalent interactions. The hydrogen bonding, ionic, and hydrophobic interactions impact are prominent. They play a vital role in the stabilizing three-dimensional and four dimensional structure of macromolecules. Certain macromolecules operate as catalysts for chemical reactions or as enablers of physical processes, such as molecular transport, signal transduction, regulation of gene expression etc. The structural arrangement of chemical groups in an active or binding site creates a high degree of specificity. Dynamic structure of macromolecules involving major and minor structural changes in a wide range of time scale, are crucial for understanding its biological function. Minor alterations can take the form of localised molecular vibrations that promote the small molecules to access the interior portion of macromolecules. Also rapid changes observed in the dynamic structure of the macromolecule affect the homeostasis of molecular and biochemical biological processes. For the majority of biological processes to function, protein dynamics and conformational changes are necessary. Interaction of protein molecules provide the connection between cellular activities like signalling, solute transport, synaptic transmission, enzymatic catalysis and atomic-level structural features.
Molecular Dynamic (MD) simulation promotes to study at molecular and nanoscale level. Biological occurrence are instructed by motion of protein molecules and physical interactions between protein and existing molecules such as nucleic acids, ligands, proteins and peptides. Protein stability, protein-ligand binding, and protein-protein interactions are benefited greatly from MD simulations on a range of protein systems, including single proteins, protein-ligand and protein complexes. When these technologies are integrated into the drug development pipeline, researchers will be able to pinpoint key interactions required for the successful binding of peptides, proteins, and small molecules to binding pockets and protein-protein interfaces. The accuracy of classical potential energy functions, often known as force fields, to characterise the intermolecular and intramolecular interactions between particles in a system of interest underlies the predictive power of dynamic simulations.
Highly complex and dynamic nature of membrane is a crucial determinant of intermolecular protein-binding, signal transduction, molecular mobility etc. Applying molecular modelling with molecular dynamic simulation renders a deeper understanding of the processes involved in biomolecular interactions with membranes. By delineating the dynamics involved in the membrane-protein interaction it is possible to elucidate signalling sequelae and membrane mechanical properties, which governs cell function.
MD simulation has more than 45 years of history. Algorithmic advances and modern force fields used in simulation of biological macromolecules shall be submitted. This call for research articles will pivot around computer calculations of protein-ligand, protein-protein and protein to other biomolecular interaction systems with applications to structure based drug design. Interaction and dynamic simulation studies that examines the pathogenic mechanisms of disease, which is caused by misfolding of protein, intrinsically disordered proteins, investigating drug resistance mechanism etc would be scope for this call for. These problems are difficult to identify by experimental methods. Thus, molecular dynamic simulation will have effective computational power, better sampling techniques and more reliable force fields with efficient analysis methods. The call-for will also focus on highlighting the limitations faced by current simulation tools as well as the improvements that have been made to enhance their efficiency.
Molecular Dynamic (MD) simulation promotes to study at molecular and nanoscale level. Biological occurrence are instructed by motion of protein molecules and physical interactions between protein and existing molecules such as nucleic acids, ligands, proteins and peptides. Protein stability, protein-ligand binding, and protein-protein interactions are benefited greatly from MD simulations on a range of protein systems, including single proteins, protein-ligand and protein complexes. When these technologies are integrated into the drug development pipeline, researchers will be able to pinpoint key interactions required for the successful binding of peptides, proteins, and small molecules to binding pockets and protein-protein interfaces. The accuracy of classical potential energy functions, often known as force fields, to characterise the intermolecular and intramolecular interactions between particles in a system of interest underlies the predictive power of dynamic simulations.
Highly complex and dynamic nature of membrane is a crucial determinant of intermolecular protein-binding, signal transduction, molecular mobility etc. Applying molecular modelling with molecular dynamic simulation renders a deeper understanding of the processes involved in biomolecular interactions with membranes. By delineating the dynamics involved in the membrane-protein interaction it is possible to elucidate signalling sequelae and membrane mechanical properties, which governs cell function.
MD simulation has more than 45 years of history. Algorithmic advances and modern force fields used in simulation of biological macromolecules shall be submitted. This call for research articles will pivot around computer calculations of protein-ligand, protein-protein and protein to other biomolecular interaction systems with applications to structure based drug design. Interaction and dynamic simulation studies that examines the pathogenic mechanisms of disease, which is caused by misfolding of protein, intrinsically disordered proteins, investigating drug resistance mechanism etc would be scope for this call for. These problems are difficult to identify by experimental methods. Thus, molecular dynamic simulation will have effective computational power, better sampling techniques and more reliable force fields with efficient analysis methods. The call-for will also focus on highlighting the limitations faced by current simulation tools as well as the improvements that have been made to enhance their efficiency.
Keywords: biophysics, Molecular Dynamic Simulation
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