Abstract
Lipids play important modulatory and structural roles for membrane proteins. Molecular dynamics simulations are frequently used to provide insights into the nature of these protein–lipid interactions. Systematic comparative analysis requires tools that provide algorithms for objective assessment of such interactions. We introduce PyLipID, a Python package for the identification and characterization of specific lipid interactions and binding sites on membrane proteins from molecular dynamics simulations. PyLipID uses a community analysis approach for binding site detection, calculating lipid residence times for both the individual protein residues and the detected binding sites. To assist structural analysis, PyLipID produces representative bound lipid poses from simulation data, using a density-based scoring function. To estimate residue contacts robustly, PyLipID uses a dual-cutoff scheme to differentiate between lipid conformational rearrangements while bound from full dissociation events. In addition to the characterization of protein–lipid interactions, PyLipID is applicable to analysis of the interactions of membrane proteins with other ligands. By combining automated analysis, efficient algorithms, and open-source distribution, PyLipID facilitates the systematic analysis of lipid interactions from large simulation data sets of multiple species of membrane proteins.
Highlights
Cell membranes typically contain hundreds of different lipid species, asymmetrically distributed between two membrane leaflets.[1,2]. These lipid molecules are locally organized into lateral domains of distinct composition.[3,4]. The combination of these various chemical structures and microdomains results in a diverse lipid landscape that is fully exploited by membrane proteins, especially those involved in cellular signaling.[5,6]
Following recent advances in single-particle cryoEM18 including the use of nanodiscs to preserve a lipid bilayer environment,[19] increasing numbers of membrane proteins structures have been determined at near atomic resolution with bound lipids present in the structures.[20]
Before describing in detail application cases of PyLipID, we provide a brief overview of PyLipID analysis and outputs (Figure 2)
Summary
Cell membranes typically contain hundreds of different lipid species, asymmetrically distributed between two membrane leaflets.[1,2] These lipid molecules are locally organized into lateral domains of distinct composition.[3,4] The combination of these various chemical structures and microdomains results in a diverse lipid landscape that is fully exploited by membrane proteins, especially those involved in cellular signaling.[5,6] The regulatory roles of membrane lipids include ion channel activation[7,8] and allosteric modulation of G-Protein Coupled Receptors (GPCRs) and other receptors.[9−13] Lipid molecules may strengthen domain and/or subunit interactions in more complex membrane proteins.[14,15] It is of importance to characterize protein−lipid interactions in order to reach an understanding of the dynamics and functions of membrane proteins.A number of biophysical techniques can reveal the presence of protein−lipid interactions; e.g., see refs 16 and 17. Following recent advances in single-particle cryoEM18 including the use of nanodiscs to preserve a lipid bilayer environment,[19] increasing numbers of membrane proteins structures have been determined at near atomic resolution with bound lipids present in the structures.[20] These membrane protein structures provide gateways for understanding how lipids may modulate protein function and pose challenges regarding the identification of interacting lipid species
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