Combined Covalent-Electrostatic Model of Hydrogen Bonding Improves Structure Prediction with Rosetta

O’Meara, Matthew J.; Leaver‐Fay, Andrew; Tyka, Michael D.; Stein, Amelie; Houlihan, Kevin; DiMaio, Frank; Bradley, Philip; Kortemme, Tanja; Baker, David; Snoeyink, Jack; Kuhlman, Brian

doi:10.1021/ct500864r

Cited by 224 publications

(302 citation statements)

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“…Mutations were defined as improving helical propensity if they were in helical regions and if Rosetta energy calculations showed ΔΔG calc of less than −0.15 Rosetta energy units for the energy term that accounts for the compatibility of the amino acid identity with the local backbone ϕ and ψ dihedral angles (p_aa_pp). Positions were defined as buried if they had >21 and >75 neighboring nonhydrogen atoms within 10 and 12 Å, respectively, according to the Rosetta Features Reporter (31,32).…”

Section: Methodsmentioning

confidence: 99%

One-step design of a stable variant of the malaria invasion protein RH5 for use as a vaccine immunogen

Campeotto

Goldenzweig

Davey

et al. 2017

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

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Many promising vaccine candidates from pathogenic viruses, bacteria, and parasites are unstable and cannot be produced cheaply for clinical use. For instance, Plasmodium falciparum reticulocyte-binding protein homolog 5 (PfRH5) is essential for erythrocyte invasion, is highly conserved among field isolates, and elicits antibodies that neutralize in vitro and protect in an animal model, making it a leading malaria vaccine candidate. However, functional RH5 is only expressible in eukaryotic systems and exhibits moderate temperature tolerance, limiting its usefulness in hot and low-income countries where malaria prevails. Current approaches to immunogen stabilization involve iterative application of rational or semirational design, random mutagenesis, and biochemical characterization. Typically, each round of optimization yields minor improvement in stability, and multiple rounds are required. In contrast, we developed a onestep design strategy using phylogenetic analysis and Rosetta atomistic calculations to design PfRH5 variants with improved packing and surface polarity. To demonstrate the robustness of this approach, we tested three PfRH5 designs, all of which showed improved stability relative to wild type. The best, bearing 18 mutations relative to PfRH5, expressed in a folded form in bacteria at >1 mg of protein per L of culture, and had 10-15°C higher thermal tolerance than wild type, while also retaining ligand binding and immunogenic properties indistinguishable from wild type, proving its value as an immunogen for a future generation of vaccines against the malaria blood stage. We envision that this efficient computational stability design methodology will also be used to enhance the biophysical properties of other recalcitrant vaccine candidates from emerging pathogens.

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Section: Methodsmentioning

confidence: 99%

One-step design of a stable variant of the malaria invasion protein RH5 for use as a vaccine immunogen

Campeotto

Goldenzweig

Davey

et al. 2017

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

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“…This raises the question of how best we should define and measure NCIs, and, of course, how do we model and assess them computationally and quantitatively. For example, recent work on the Rosetta forcefield has demonstrated that simultaneously modeling the electrostatic and covalent properties of hydrogen bonds improves protein-structure prediction, 47 and work on polarizeable, multipolar forcefields such as AMOEBA 48 has challenged the notion of linear hydrogen bonding in a-helices. Further quantification of the contributions from each NCI and how they cooperate should inform the development of more-accurate forcefields for molecular modeling and mechanics, and thus afford a deeper understanding of protein structure and stability.…”

Section: Discussionmentioning

confidence: 99%

On the satisfaction of backbone‐carbonyl lone pairs of electrons in protein structures

Bartlett

Woolfson

2016

Protein Science

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Protein structures are stabilized by a variety of noncovalent interactions (NCIs), including the hydrophobic effect, hydrogen bonds, electrostatic forces and van der Waals' interactions. Our knowledge of the contributions of NCIs, and the interplay between them remains incomplete. This has implications for computational modeling of NCIs, and our ability to understand and predict protein structure, stability, and function. One consideration is the satisfaction of the full potential for NCIs made by backbone atoms. Most commonly, backbone-carbonyl oxygen atoms located within a-helices and b-sheets are depicted as making a single hydrogen bond. However, there are two lone pairs of electrons to be satisfied for each of these atoms. To explore this, we used operational geometric definitions to generate an inventory of NCIs for backbone-carbonyl oxygen atoms from a set of high-resolution protein structures and associated molecular-dynamics simulations in water. We included more-recently appreciated, but weaker NCIs in our analysis, such as nfip* interactions, Ca-H bonds and methyl-H bonds. The data demonstrate balanced, dynamic systems for all proteins, with most backbone-carbonyl oxygen atoms being satisfied by two NCIs most of the time. Combinations of NCIs made may correlate with secondary structure type, though in subtly different ways from traditional models of a-and b-structure. In addition, we find examples of under-and over-satisfied carbonyl-oxygen atoms, and we identify both sequencedependent and sequence-independent secondary-structural motifs in which these reside. Our analysis provides a more-detailed understanding of these contributors to protein structure and stability, which will be of use in protein modeling, engineering and design.

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“…The talaris2013 scoring function was used for Rosetta (65). For the combined Rosetta-TERMs design procedure, we limited the amino acids that Rosetta could use at position r to the smallest set that accounted for at least 80% cumulative probability according to TERM-based self-energy (i.e., fa 1 , .…”

Section: Methodsmentioning

confidence: 99%

“…To this end, we asked whether TERM statistics would predict sequences optimally compatible with native backbones to be close to the corresponding native sequences. This experiment, known as "native sequence recovery," is a common means of evaluating scoring functions in computational protein design (65).…”

Section: A Small Number Of Terms Describe Most Of the Structural Univmentioning

confidence: 99%

Tertiary alphabet for the observable protein structural universe

Mackenzie

Zhou

Grigoryan

2016

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

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Here, we systematically decompose the known protein structural universe into its basic elements, which we dub tertiary structural motifs (TERMs). A TERM is a compact backbone fragment that captures the secondary, tertiary, and quaternary environments around a given residue, comprising one or more disjoint segments (three on average). We seek the set of universal TERMs that capture all structure in the Protein Data Bank (PDB), finding remarkable degeneracy. Only ∼600 TERMs are sufficient to describe 50% of the PDB at sub-Angstrom resolution. However, more rare geometries also exist, and the overall structural coverage grows logarithmically with the number of TERMs. We go on to show that universal TERMs provide an effective mapping between sequence and structure. We demonstrate that TERM-based statistics alone are sufficient to recapitulate close-to-native sequences given either NMR or X-ray backbones. Furthermore, sequence variability predicted from TERM data agrees closely with evolutionary variation. Finally, locations of TERMs in protein chains can be predicted from sequence alone based on sequence signatures emergent from TERM instances in the PDB. For multisegment motifs, this method identifies spatially adjacent fragments that are not contiguous in sequence-a major bottleneck in structure prediction. Although all TERMs recur in diverse proteins, some appear specialized for certain functions, such as interface formation, metal coordination, or even water binding. Structural biology has benefited greatly from previously observed degeneracies in structure. The decomposition of the known structural universe into a finite set of compact TERMs offers exciting opportunities toward better understanding, design, and prediction of protein structure.tertiary motif | structural degeneracy | protein structural universe | sequence-structure relationships | structural modularity I n this work, we aim to decompose the protein structure space into its basic elements as a way of understanding its design principles and describing its limits. Reductionist representations of protein structure have been of long-standing interest (1), with many studies having shown degeneracy at various structural levels (2-5). Features ranging from backbone or side-chain dihedral angles (6, 7) to domains and folds (8, 9) have been classified, and structural basins of attraction have been found in select motifs (10-17), offering a glimpse of a modular space with frequently repeating elements. The reason behind this modularity appears to be a combination of evolutionary history and the fundamental physics of structure. In particular, degeneracy at the level of domains, folds, and functional modules is likely strongly influenced by evolution, whereby such elements recur in different proteins often because of a common ancestor (18,19). On the other hand, statistics of more detailed structural features are better explained from the thermodynamic perspective. For example, observed Ramachandran backbone dihedral angle preferences are largely determined...

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Combined Covalent-Electrostatic Model of Hydrogen Bonding Improves Structure Prediction with Rosetta

Cited by 224 publications

References 76 publications

One-step design of a stable variant of the malaria invasion protein RH5 for use as a vaccine immunogen

One-step design of a stable variant of the malaria invasion protein RH5 for use as a vaccine immunogen

On the satisfaction of backbone‐carbonyl lone pairs of electrons in protein structures

Tertiary alphabet for the observable protein structural universe

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