Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement

Leaver‐Fay, Andrew; O’Meara, Matthew J.; Tyka, Mike; Jacak, Ron; Song, Yifan; Kellogg, Elizabeth H.; Thompson, James; Davis, Ian; Pache, Roland A.; Lyskov, Sergey; Gray, Jeffrey J.; Kortemme, Tanja; Richardson, Jane S.; Havranek, James J.; Snoeyink, Jack; Baker, David; Kuhlman, Brian

doi:10.1016/b978-0-12-394292-0.00006-0

Cited by 234 publications

(307 citation statements)

References 55 publications

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“…Starting from a symmetric array of subunits in a completely extended backbone conformation, the internal, fivefold, and helical DOF were allowed to vary according to the ssNMR restraints and Rosetta energy function. The local backbone and sidechain conformations were sampled using Monte Carlo fragment insertions and rotamer trials that were propagated among the symmetry-related subunits and scored using a physically realistic energy function (52). The selection of candidate backbone fragments from high-resolution structures in the PDB was performed using the ssNMR backbone chemical shifts (53).…”

Section: Methodsmentioning

confidence: 99%

The NMR–Rosetta capsid model of M13 bacteriophage reveals a quadrupled hydrophobic packing epitope

Morag

Sgourakis

Baker

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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115

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Filamentous phage are elongated semiflexible ssDNA viruses that infect bacteria. The M13 phage, belonging to the family inoviridae, has a length of ∼1 μm and a diameter of ∼7 nm. Here we present a structural model for the capsid of intact M13 bacteriophage using Rosetta model building guided by structure restraints obtained from magic-angle spinning solid-state NMR experimental data. The C5 subunit symmetry observed in fiber diffraction studies was enforced during model building. The structure consists of stacked pentamers with largely alpha helical subunits containing an N-terminal type II β-turn; there is a rise of 16.6-16.7 Å and a tilt of 36.1-36.6°between consecutive pentamers. The packing of the subunits is stabilized by a repeating hydrophobic stacking pocket; each subunit participates in four pockets by contributing different hydrophobic residues, which are spread along the subunit sequence. Our study provides, to our knowledge, the first magicangle spinning NMR structure of an intact filamentous virus capsid and further demonstrates the strength of this technique as a method of choice to study noncrystalline, high-molecular-weight molecular assemblies.solid-state NMR | magic-angle spinning | filamentous bacteriophage | structure determination | Rosetta modeling F ilamentous bacteriophage are long, thin, and semiflexible rod viruses that infect bacteria (1, 2). These large assemblies (∼15-35 MDa) contain a circular single-stranded (ss) DNA genome encapsulated in a protein shell. All filamentous phage have a similar life cycle and virion structure despite the relatively high number of strains, with DNA sequence homology varying from almost complete to very little. The unique phage properties make them ideal for a large range of applications such as phage display (3), DNA cloning and sequencing (4, 5), nanomaterial fabrication (6-8), and as drug-carrying nanomachines (9). In addition, filamentous viruses form a variety of liquid crystals driving the development of both theory and practice of softmatter physics (10, 11). Filamentous viruses are also associated with various diseases, e.g., CTXϕ phage in cholera toxin (12) and Pf4 phage in cystic fibrosis (13).Phage belonging to the Ff family (M13, fd, f1) are F-pilusspecific viruses that share almost identical genomes and very similar structures. M13 is a 16-MDa virus having a diameter of ∼7 nm and a length of ∼1 μm. The capsid is composed of several thousand identical copies of a major coat protein subunit arranged in a helical array surrounding a core of a circular ssDNA. The major coat proteins constitute ∼85% of the total virion mass, the ssDNA ∼12%, and all other minor proteins (gp3, gp6, gp7, gp9) that are specific for infection and assembly constitute about 3% of the total virion mass (1, 14).Previous structural models for a small number of phages have been obtained by means of X-ray fiber diffraction (15-19), static solid-state NMR (20, 21), and cryo-EM (22). Structural models for the Ff family have been proposed based on the three methods; however, ...

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Section: Methodsmentioning

confidence: 99%

The NMR–Rosetta capsid model of M13 bacteriophage reveals a quadrupled hydrophobic packing epitope

Morag

Sgourakis

Baker

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

115

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“…Computational design and docking were performed using Rosetta (19)(20)(21). A computationally guided ubiquitin library was displayed on the surface of M13 bacteriophage as previously described (22) and selected against the monobiotinylated catalytic domain of USP14 (residues D91-Q494, C114A active site mutation).…”

Section: Methodsmentioning

confidence: 99%

“…To explore the conformation and dynamics of ubiquitin's β1-β2 loop, we computationally searched for core positions where mutations are predicted to favor the USP-binding state, using both single-state and multistate RosettaDesign (Methods) (19)(20)(21)(22). Both types of design experiments identified a consistent set of positions for mutation ( Fig.…”

Section: Generation Of Ubiquitin Variants With Increased Affinity Formentioning

confidence: 99%

Conformational dynamics control ubiquitin-deubiquitinase interactions and influence in vivo signaling

Phillips¹,

Zhang²,

Cunningham³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Ubiquitin is a highly conserved eukaryotic protein that interacts with a diverse set of partners to act as a cellular signaling hub. Ubiquitin's conformational flexibility has been postulated to underlie its multifaceted recognition. Here we use computational and library-based means to interrogate core mutations that modulate the conformational dynamics of human ubiquitin. These ubiquitin variants exhibit increased affinity for the USP14 deubiquitinase, with concomitantly reduced affinity for other deubiquitinases. Strikingly, the kinetics of conformational motion are dramatically slowed in these variants without a detectable change in either the ground state fold or excited state population. These variants can be ligated into substrate-linked chains in vitro and in vivo but cannot solely support growth in eukaryotic cells. Proteomic analyses reveal nearly identical interaction profiles between WT ubiquitin and the variants but identify a small subset of altered interactions. Taken together, these results show that conformational dynamics are critical for ubiquitin-deubiquitinase interactions and imply that the fine tuning of motion has played a key role in the evolution of ubiquitin as a signaling hub.computational design | phage display | protein dynamics | protein-protein interactions | ubiquitin signaling

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“…Crystal structure processing and design parameters For structural modeling, Rosetta with the Talaris2013 score function was used (Das and Baker, 2008;Kaufmann et al, 2010;Leaver-Fay et al, 2013;Moretti et al, 2013), using the PyRosetta interface (Chaudhury et al, 2010). Native crystal structures were brought to local energy minima through multiple cycles of backbone minimization and rotamer optimization with heavy atom restraints (Bradley et al, 2005).…”

Section: Methodsmentioning

confidence: 99%

A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces

Riley¹,

Ayres²,

Hellman³

et al. 2016

Protein Engineering, Design and Selection

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T-cell receptors (TCRs) have emerged as a new class of therapeutics, most prominently for cancer where they are the key components of new cellular therapies as well as soluble biologics. Many studies have generated high affinity TCRs in order to enhance sensitivity. Recent outcomes, however, have suggested that fine manipulation of TCR binding, with an emphasis on specificity may be more valuable than large affinity increments. Structure-guided design is ideally suited for this role, and here we studied the generality of structure-guided design as applied to TCRs. We found that a previous approach, which successfully optimized the binding of a therapeutic TCR, had poor accuracy when applied to a broader set of TCR interfaces. We thus sought to develop a more general purpose TCR design framework. After assembling a large dataset of experimental data spanning multiple interfaces, we trained a new scoring function that accounted for unique features of each interface. Together with other improvements, such as explicit inclusion of molecular flexibility, this permitted the design new affinity-enhancing mutations in multiple TCRs, including those not used in training. Our approach also captured the impacts of mutations and substitutions in the peptide/MHC ligand, and recapitulated recent findings regarding TCR specificity, indicating utility in more general mutational scanning of TCR-pMHC interfaces.

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Scientific Benchmarks for Guiding Macromolecular Energy Function Improvement

Cited by 234 publications

References 55 publications

The NMR–Rosetta capsid model of M13 bacteriophage reveals a quadrupled hydrophobic packing epitope

The NMR–Rosetta capsid model of M13 bacteriophage reveals a quadrupled hydrophobic packing epitope

Conformational dynamics control ubiquitin-deubiquitinase interactions and influence in vivo signaling

A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces

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