Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Schoeder, Clara T.; Schmitz, Samuel; Adolf-Bryfogle, Jared; Sevy, Alexander M.; Finn, Jessica A.; Sauer, Marion F.; Bozhanova, Nina G.; Mueller, Benjamin K.; Sangha, Amandeep K.; Bonet, Jaume; Sheehan, Jonathan H.; Kuenze, Georg; Marlow, Brennica; Smith, Shannon Toney; Woods, H. J.; Bender, Brian J.; Martina, Cristina Elisa; Alamo, Diego del; Kodali, Pranav; Gulsevin, Alican; Schief, William R.; Correia, Bruno E.; Crowe, James E.; Meiler, Jens; Moretti, Rocco

doi:10.1021/acs.biochem.0c00912

Cited by 36 publications

(32 citation statements)

References 154 publications

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“…The Rosetta software suite contains different methods for epitope-focused immunogen design, including sidechain and backbone grafting, and a protocol called FoldFromLoops, which is now succeeded by FunFolDes [ 16 , 18 , 20 , 29 , 30 ]. In the work presented here, these grafting protocols were used to transplant the BDBV-HR2-MPER epitope, as observed in the crystal structure PDB: 6N7J, onto smaller scaffold proteins [ 21 ].…”

Section: Resultsmentioning

confidence: 99%

Epitope-focused immunogen design based on the ebolavirus glycoprotein HR2-MPER region

et al. 2022

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The three human pathogenic ebolaviruses: Zaire (EBOV), Bundibugyo (BDBV), and Sudan (SUDV) viruses, cause severe disease with high fatality rates. Epitopes of ebolavirus glycoprotein (GP) recognized by antibodies with binding breadth for all three ebolaviruses are of major interest for rational vaccine design. In particular, the heptad repeat 2 –membrane-proximal external region (HR2-MPER) epitope is relatively conserved between EBOV, BDBV, and SUDV GP and targeted by human broadly-neutralizing antibodies. To study whether this epitope can serve as an immunogen for the elicitation of broadly-reactive antibody responses, protein design in Rosetta was employed to transplant the HR2-MPER epitope identified from a co-crystal structure with the known broadly-reactive monoclonal antibody (mAb) BDBV223 onto smaller scaffold proteins. From computational analysis, selected immunogen designs were produced as recombinant proteins and functionally validated, leading to the identification of a sterile alpha motif (SAM) domain displaying the BDBV-HR2-MPER epitope near its C terminus as a promising candidate. The immunogen was fused to one component of a self-assembling, two-component nanoparticle and tested for immunogenicity in rabbits. Robust titers of cross-reactive serum antibodies to BDBV and EBOV GPs and moderate titers to SUDV GP were induced following immunization. To confirm the structural composition of the immunogens, solution NMR studies were conducted and revealed structural flexibility in the C-terminal residues of the epitope. Overall, our study represents the first report on an epitope-focused immunogen design based on the structurally challenging BDBV-HR2-MPER epitope.

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Section: Resultsmentioning

confidence: 99%

Epitope-focused immunogen design based on the ebolavirus glycoprotein HR2-MPER region

et al. 2022

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“…This tool is available online and can be used through Rosie ( , last accessed date: 10 February 2022). The protocol consists of three steps for a given antibody sequence [ 21 , 207 , 208 ]: In the initial step, the CDRs are identified using the Kabat CDR definition, and the residues are renumbered using the Chothia scheme. The template selection is then carried out for all the frameworks, and five of the six CDRs (CDRH1 and CDRH2 and CDRL1–CDR3), From the selected templates, a preliminary model is created using homology modelling, as it was shown to be more accurate than a completely de novo approach.…”

Section: V H H Modellingmentioning

confidence: 99%

“…AbPredict has been benchmarked using the AMA-II antibody set and compared to the methods presented therein. It performed in the upper third of all the compared methods [ 208 ]. It was recently compared to RosettaAntibody and RosettaCM, a generic version, in the case of long CDRH3.…”

Section: V H H Modellingmentioning

confidence: 99%

VHH Structural Modelling Approaches: A Critical Review

Vishwakarma

Vattekatte

Shinada³

et al. 2022

IJMS

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VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. The number of experimentally solved VHH structures has significantly improved recently, which is of great help, because it offers the ability to directly work on 3D structures to humanise or improve them. Unfortunately, most VHHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural information. The methods of structure prediction from the primary amino acid sequence appear essential to bypass this limitation. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given VHH sequence (a total of 21). Besides the historical overview, it aims at showing how model software programs have been shaping the structural predictions of VHHs. A brief explanation of each methodology is supplied, and pertinent examples of their usage are provided. Finally, we present a structure prediction case study of a recently solved VHH structure. According to some recent studies and the present analysis, AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of VHH from its sequence.

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“…All tools are available as components for RosettaScripts and PyRosetta. In addition, the use of all components are covered in publicly accessible tutorials 63 and detailed protocol captures 64 . Results of this study are continuously benchmarked using the Rosetta automated scientific testing framework 65 .…”

Section: Availability and Documentationmentioning

confidence: 99%

Growing Glycans in Rosetta: Accuratede novoglycan modeling, density fitting, and rational sequon design

Adolf-Bryfogle

Labonte

Kraft

et al. 2021

Preprint

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Carbohydrates and glycoproteins modulate key biological functions. Computational approaches inform function to aid in carbohydrate structure prediction, structure determination, and design. However, experimental structure determination of sugar polymers is notoriously difficult as glycans can sample a wide range of low energy conformations, thus limiting the study of glycan-mediated molecular interactions. In this work, we expanded the RosettaCarbohydrate framework, developed and benchmarked effective tools for glycan modeling and design, and extended the Rosetta software suite to better aid in structural analysis and benchmarking tasks through the SimpleMetrics framework. We developed a glycan-modeling algorithm, GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. After a rigorous optimization of kinematic and energetic considerations to improve near-native sampling enrichment and decoy discrimination, GlycanTreeModeler was benchmarked on a test set of diverse glycan structures, or "trees". Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. GlycanTreeModeler algorithms and associated tools were employed to design de novo glycan trees into a protein nanoparticle vaccine that are able to direct the immune response by shielding regions of the scaffold from antibody recognition. This work will inform glycoprotein model prediction, aid in both X-ray and electron microscopy density solutions and refinement, and help lead the way towards a new era of computational glycobiology.

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Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Cited by 36 publications

References 154 publications

Epitope-focused immunogen design based on the ebolavirus glycoprotein HR2-MPER region

Epitope-focused immunogen design based on the ebolavirus glycoprotein HR2-MPER region

VHH Structural Modelling Approaches: A Critical Review

Growing Glycans in Rosetta: Accuratede novoglycan modeling, density fitting, and rational sequon design

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