Protein Structure Prediction and Design in a Biologically-Realistic Implicit Membrane
bioRxiv preprint doi: https://doi.org/10.1101/630715; this version posted May 8, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Protein structure prediction and design in a biologically-realistic implicit membrane Rebecca F. Alforda, Patrick J. Flemingb,c, Karen G. Flemingb,c, and Jeffrey J. Graya,c aDepartment of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218; bT.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218; cProgram in Molecular Biophysics, Johns Hopkins University, Baltimore, MD 21218 This manuscript was compiled on May 8, 2019 ABSTRACT. Protein design is a powerful tool for elucidating mecha- MOS (16), and the protein-lipid interactions are scored with nisms of function and engineering new therapeutics and nanotech- a molecular mechanics energy function. All-atom models are nologies. While soluble protein design has advanced, membrane attractive because they can feature hundreds of lipid types to- protein design remains challenging due to difficulties in modeling ward approximating the composition of biological membranes the lipid bilayer. In this work, we developed an implicit approach (17). With current technology, detailed all-atom models can be that captures the anisotropic structure, shape of water-filled pores, used to explore membrane dynamics for hundreds of nanosec- and nanoscale dimensions of membranes with different lipid compo- onds (18): the time scale required to achieve equilibrated sitions. The model improves performance in computational bench- properties on a bilayer with approximately 250 lipids (19). marks against experimental targets including prediction of protein Coarse-grained representations such as MARTINI (20), ELBA orientations in the bilayer, ∆∆G calculations, native structure dis- (21), and SIRAH (22) reduce computation time by mapping crimination, and native sequence recovery.
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