Cytosolic lipid droplets (LDs) are the main storage organelles for metabolic energy in most cells. They are unusual organelles that are bounded by a phospholipid monolayer and specific surface proteins, including key enzymes of lipid and energy metabolism. Proteins targeting LDs from the cytoplasm often contain amphipathic helices, but how they bind to LDs is not well understood. Combining computer simulations with experimental studies in vitro and in cells, we uncover a general mechanism for targeting of cytosolic proteins to LDs: large hydrophobic residues of amphipathic helices detect and bind to large, persistent membrane packing defects that are unique to the LD surface. Surprisingly, amphipathic helices with large hydrophobic residues from many different proteins are capable of binding to LDs. This suggests that LD protein composition is additionally determined by mechanisms that selectively prevent proteins from binding LDs, such as macromolecular crowding at the LD surface.

Highlights d Specific membrane-embedded ER proteins target and accumulate on LDs d Minimal targeting motifs use Trp and positive-charged residues for LD accumulation d Distribution of these residues within motifs correlates with LD accumulation

Standard low resolution coarse-grained modeling techniques have difficulty capturing multiple configurations of protein systems. Here, we present a method for creating accurate coarse-grained (CG) models with multiple configurations using a linear combination of functions or “states”. Individual CG models are created to capture the individual states, and the approximate coupling between the two states is determined from an all-atom potential of mean force. We show that the resulting multiconfiguration coarse-graining (MCCG) method accurately captures the transition state as well as the free energy between the two states. We have tested this method on the folding of dodecaalanine, as well as the amphipathic helix of endophilin.