Accurate computational design of multipass transmembrane proteins

Lu, Pinyan; Min, Duyoung; DiMaio, Frank; Wei, Kathy Y.; Vahey, Michael D.; Boyken, Scott E.; Chen, Zibo; Fallas, Jorge A.; Ueda, George; Sheffler, William; Mulligan, Vikram Khipple; Xu, Wenqing; Bowie, James U.; Baker, David

doi:10.1126/science.aaq1739

Cited by 156 publications

(149 citation statements)

References 40 publications

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“…A popular approach to overcoming the computational cost of solvent electrostatics models is the Lazaridis implicit membrane model (IMM1; (34,35)): a Gaussian solvent-exclusion model that uses experimentally measured transfer energies of side-chain analogues in organic solvents to emulate amino acid preferences in the bilayer (36). IMM1 has been applied to various biomolecular modeling problems including studies of antimicrobial peptides (37), de novo folding (38,39), and de novo design of transmembrane helical bundles (11). However, organic solvent slabs differ from phospholipid bilayers because lipids are thermodynamically constrained to a bilayer configuration, resulting in a unique polarity gradient that influences side chain preferences (40)(41)(42).…”

Section: R a F Tmentioning

confidence: 99%

“…A remaining challenge is to create tools for membrane proteins (3): a class of molecules that constitute over 30% of all proteins (4) and are targets for 60% of pharmaceuticals (5). There have been several achievements in membrane protein design including a zinc-transporting tetramer Rocker (6), an ion-conducting protein based on the Escherichia Coli Wza transporter (7), β-barrel pores with increased selectivity (8), receptors with new ligand-binding properties (9,10), and designed de novo α-helical bundles that insert into the membrane (11). For these advances, design of lipid-facing positions often used a native sequence or restricted the chemistry and/or size of amino acids.…”

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confidence: 99%

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Protein structure prediction and design in a biologically-realistic implicit membrane

Alford

Fleming

et al. 2019

Preprint

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Protein design is a powerful tool for elucidating mechanisms of function and engineering new therapeutics and nanotechnologies. While soluble protein design has advanced, membrane protein design remains challenging due to 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, ∆∆G 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. Further, 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.membrane proteins | lipid composition | energy function | structure prediction | protein design

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Section: R a F Tmentioning

confidence: 99%

mentioning

confidence: 99%

Protein structure prediction and design in a biologically-realistic implicit membrane

Alford

Fleming

et al. 2019

Preprint

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“…Membrane proteins have essential biological roles as receptors, channels, and transporters. Over the past decade, significant progress has been made in membrane-protein design, including the first design of membrane-integral inhibitors 1 , a transporter 2 , and a de novo designed structure based on coiled-coil motifs 3 . Despite this exciting progress, modelling, design, and engineering of membrane proteins lag far behind those of soluble proteins.…”

Section: Introductionmentioning

confidence: 99%

A lipophilicity-based energy function for membrane-protein modelling and design

Weinstein

Elazar

Fleishman

2019

Preprint

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Membrane-protein design is an exciting and increasingly successful research area which has led to landmarks including the design of stable and accurate membrane-integral proteins based on coiled-coil motifs. Design of topologically more complex proteins, such as most receptors, channels, and transporters, however, demands an energy function that balances contributions from intra-protein contacts and protein-membrane interactions. Recent advances in water-soluble all-atom energy functions have increased the accuracy in structure-prediction benchmarks. The plasma membrane, however, imposes different physical constraints on protein solvation. To understand these constraints, we recently developed a high-throughput experimental screen, called dsTβL, and inferred apparent insertion energies for each amino acid at dozens of positions across the bacterial plasma membrane. Here, we express these profiles as lipophilicity energy terms in Rosetta and demonstrate that the new energy function outperforms previous ones in modelling and design benchmarks. Rosetta ab initio simulations starting from an extended chain recapitulate two-thirds of the experimentally determined structures of membrane-spanning homo-oligomers with <2.5Å root-mean-square deviation within the top-predicted five models. Furthermore, in two sequence-design benchmarks, the energy function improves discrimination of stabilizing point mutations and recapitulates natural membrane-protein sequences of known structure, thereby recommending this new energy function for membrane-protein modelling and design.

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“…There are many examples of de novo designed amino acid sequences that fold to a single designed target structure (Huang et al, 2016;Lu et al, 2018) , but designing new amino acid sequences capable of adopting divergent structural conformations is challenging since the free energy difference between the two states must be small enough that a few amino acid changes can shift the global energy minimum from one state to the other, and both states must be stable relative to the unfolded state. Redesigns of natural protein backbones have yielded large conformational changes for systems such as the Zn antennafinger, Zinc-binding/Coiled coil (ZiCo), and designed peptide Sw2, that involve changes in oligomerization state from a homotrimeric 3-helix bundle to a monomeric zinc-finger fold (Ambroggio and Kuhlman, 2006;Cerasoli et al, 2005;Hori and Sugiura, 2004) , and the pHios de novo design also involves a change in oligomerization state (pentamer to hexamer; (Lizatović et al, 2016) ).…”

Section: Introductionmentioning

confidence: 99%

Computational design of a protein family that adopts two well-defined and structurally divergent de novo folds

Wei

Moschidi

Bick

et al. 2019

Preprint

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The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used to de novo design proteins that fold to a single state with a deep free energy minima (Huang et al., 2016) , and to reengineer natural proteins to alter their dynamics (Davey et al., 2017) or fold (Alexander et al., 2009) , the de novo design of closely related sequences which adopt well-defined, but structurally divergent structures remains an outstanding challenge. Here, we design closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations -one short (~66 Å height) and the other long (~100 Å height) -

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Accurate computational design of multipass transmembrane proteins

Cited by 156 publications

References 40 publications

Protein structure prediction and design in a biologically-realistic implicit membrane

Protein structure prediction and design in a biologically-realistic implicit membrane

A lipophilicity-based energy function for membrane-protein modelling and design

Computational design of a protein family that adopts two well-defined and structurally divergent de novo folds

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