Protein Structure Prediction and Design in a Biologically Realistic Implicit Membrane

Abstract

Protein design is a powerful tool for elucidating mechanisms of function and engineering new therapeutics and nanotechnologies. Although soluble protein design has advanced, membrane protein design remains challenging because of difficulties in modeling the lipid bilayer. In this work, we developed an implicit approach that captures the anisotropic structure, shape of water-filled pores, and nanoscale dimensions of membranes with different lipid compositions. The model improves performance in computational benchmarks against experimental targets, including prediction of protein orientations in the bilayer, DDG calculations, native structure discrimination, and native sequence recovery. When applied to de novo protein design, this approach designs sequences with an amino acid distribution near the native amino acid distribution in membrane proteins, overcoming a critical flaw in previous membrane models that were prone to generating leucine-rich designs. Furthermore, the proteins designed in the new membrane model exhibit native-like features including interfacial aromatic side chains, hydrophobic lengths compatible with bilayer thickness, and polar pores. Our method advances high-resolution membrane protein structure prediction and design toward tackling key biological questions and engineering challenges.

Integrative modeling of membrane-associated protein assemblies

“…This would require extra effort to develop a scoring function that accounts for protein–lipid interactions. Such membrane-specific scoring functions have been already shown appropriate for membrane protein structure prediction and design purposes 45 and might also represent a significant advance for membrane-associated protein docking protocols. Looking ahead, a larger benchmark set will enable broader energy function development and optimization, which should eventually cover protein–lipid interactions too.…”

Local Bilayer Hydrophobicity Modulates Membrane Protein Stability

“…Our results should improve the speed and accuracy of membrane protein structure prediction and design algorithms. [43][44][45] As membrane proteins account for over half of all therapeutic drug targets, 46 having accurate force fields to describe membrane protein energetics is essential. This simple, linear function / 01 (=) could be adapted to implicit membrane models or could alternatively be applied explicitly in systems such that a local value of / 01 to be calculated over water concentrations ranging from millimolar to 30 molar.…”

Evolution of the SARS-CoV-2 proteome in three dimensions (3D) during the first six months of the COVID-19 pandemic

“…Computed structural model optimizations were performed with three different combinations of scoring functions based on previous work (Kellogg, Leaver-Fay, & Baker, 2011), including "hard-hard", indicating that both side chain optimization and structure minimization were performed with default van der Waals repulsion term in the Rosetta scorefunction, "soft-soft" indicating that for both steps, a different scorefunction was used that has dampened van der Waals repulsion (in this case, the backbone was entirely prevented from moving during minimization), and "soft-hard" indicating that the soft-repulsive score function was used for side chain rotamer optimization, while the hard-repulsive scorefunction was used for energy minimization. The scorefunctions used were REF2015 (Alford et al, 2017) and REF2015_soft (Kellogg et al, 2011) for soluble proteins, and franklin2019 (Alford, Fleming, Fleming, & Gray, 2020) for integral membrane proteins (with a dampened van der Waals repulsion weight in the case of soft repulsion).…”