Creative BioMart provides protein-lipid docking services to predict the structure of protein-lipid complexes and deduce the lipid binding sites of proteins from amino acid sequences, which is of great significance for the design of membrane proteins as drug targets. With years of protein engineering research experience, we can provide you with the best quality and most professional services. If you are interested in our services, please do not hesitate to contact us for more information.
Cell membranes are composed of a complex mixture of lipids and proteins that tightly regulate the flow of energy, information, nutrients and metabolites. These roles are mainly attributed to membrane proteins, and lipid-protein interactions are important determinants of the membrane binding process. In addition, membrane proteins are important drug targets, and the lipid composition of membranes is an important player in understanding the mechanism of action and targeting of many drugs. Structural studies using X-ray crystallography or cryo-electron microscopy often require solubilization of membrane proteins in detergents, a complex and lengthy process. Thus, the advent of molecular dynamics (MD) simulations provides a powerful tool for analyzing protein-lipid interactions. MD simulations have been shown to predict binding sites, allowing analysis of structural aspects of protein-lipid interactions.
Fig 1. Lipid–protein interactions in RTKs and cytokine receptors as detected in MD simulations. (Corradi V, et al., 2019)
Docking of carbohydrate ligands is difficult due to the shallow carbohydrate binding site and the very flexible carbohydrate ligands. Creative BioMart is specifically designed to handle protein to carbohydrate or carbohydrate-like docking. Our designed docking procedure combines an evolutionary docking algorithm for flexible ligands and flexible receptor side chains with carbohydrate-specific scoring and energy functions. Furthermore, it allows the system to explore the orientation and location of carbohydrate ligands into protein cavities and to assess protein-carbohydrate complex structures.
Our designed more accurate membrane models interfaced with in silico to provide detailed insights into lipid-protein interactions and increased overlap with experimental observations to validate and jointly interpret simulations and experiments. Furthermore, our procedure allows for the modulation of the physical properties of the lipid environment, the detailed chemical interactions between lipids and proteins, and the key functional roles of very specific lipids with well-defined binding sites on proteins. We employed MD simulations to study the free energy of specific lipid binding to a given site to understand the affinity of protein-lipid interactions. The calculation methods we use can be roughly divided into two categories:
(1) Using long, unbiased MD simulations to directly estimate interaction probabilities.
(2) Using biased (ie, more targeted) MD simulations to calculate the free energies of interactions of specific lipid molecules with proteins.
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