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Your search keyword '"Erasmus, M. Frank"' showing total 22 results
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22 results on '"Erasmus, M. Frank"'

1. AIntibody: an experimentally validated in silico antibody discovery design challenge

Author

Erasmus, M. Frank, Spector, Laura, Ferrara, Fortunato, DiNiro, Roberto, Pohl, Thomas J., Perea-Schmittle, Katheryn, Wang, Wei, Tessier, Peter M., Richardson, Crystal, Turner, Laure, Kumar, Sumit, Bedinger, Daniel, Sormanni, Pietro, Fernández-Quintero, Monica L., Ward, Andrew B., Loeffler, Johannes R., Swanson, Olivia M., Deane, Charlotte M., Raybould, Matthew I. J., Evers, Andreas, Sellmann, Carolin, Bachas, Sharrol, Ruffolo, Jeff, Nastri, Horacio G., Ramesh, Karthik, Sørensen, Jesper, Croasdale-Wood, Rebecca, Hijano, Oliver, Leal-Lopes, Camila, Shahsavarian, Melody, Qiu, Yu, Marcatili, Paolo, Vernet, Erik, Akbar, Rahmad, Friedensohn, Simon, Wagner, Rick, Kurella, Vinodh babu, Malhotra, Shipra, Kumar, Satyendra, Kidger, Patrick, Almagro, Juan C., Furfine, Eric, Stanton, Marty, Graff, Christilyn P., Villalba, Santiago David, Tomszak, Florian, Teixeira, Andre A. R., Hopkins, Elizabeth, Dovner, Molly, D’Angelo, Sara, and Bradbury, Andrew R. M.

Published
2024
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9. A next-generation Fab library platform directly yielding drug-like antibodies with high affinity, diversity, and developability.

Author

Ferrara, Fortunato, Fanni, Adeline, Teixeira, Andre A. R., Molina, Esteban, Leal-Lopes, Camila, DeAguero, Ashley, D'Angelo, Sara, Erasmus, M. Frank, Spector, Laura, Rodriguez Carnero, Luis Antonio, Li, Jianquan, Pohl, Thomas J., Suslov, Nikolai, Desrumeaux, Klervi, McMahon, Conor, Kathuria, Sagar, and Bradbury, Andrew R. M.

Published
2024
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11. Pandemic’s silver lining

Author

Ferrara, Fortunato, primary, D’Angelo, Sara, additional, Erasmus, M. Frank, additional, Teixeira, André A., additional, Leal-Lopes, Camila, additional, Spector, Laura P., additional, Pohl, Tom, additional, Fanni, Adeline, additional, Cocklin, Simon, additional, and Bradbury, Andrew R. M., additional

Published
2022
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12. Simultaneous affinity maturation and developability enhancement using natural liability-free CDRs

Author

Teixeira, Andre A. R., primary, D’Angelo, Sara, additional, Erasmus, M. Frank, additional, Leal-Lopes, Camila, additional, Ferrara, Fortunato, additional, Spector, Laura P., additional, Naranjo, Leslie, additional, Molina, Esteban, additional, Max, Tamara, additional, DeAguero, Ashley, additional, Perea, Katherine, additional, Stewart, Shaun, additional, Buonpane, Rebecca A., additional, Nastri, Horacio G., additional, and Bradbury, Andrew R. M., additional

Published
2022
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15. Spatial Stochastic Model of the Pre-B Cell Receptor

Author

Kerketta, Romica, Erasmus, M. Frank, Wilson, Bridget S., Halasz, Adam M., and Edwards, Jeremy S.

Abstract

Survival and proliferation of immature B lymphocytes requires expression and tonic signaling of the pre-B cell receptor (pre-BCR). This low level, ligand-independent signaling is likely achieved through frequent, but short-lived, homo interactions. Tonic signaling is also central in the pathology of precursor B acute lymphoblastic leukemia (B-ALL). In order to understand how repeated, transient events can lead to sustained signaling and to assess the impact of receptor accumulation induced by the membrane landscape, we developed a spatial stochastic model of receptor aggregation and downstream signaling events. Our rule- and agent-based model builds on previous mature BCR signaling models and incorporates novel parameters derived from single particle tracking of pre-BCR on surfaces of two different B-ALL cell lines, 697 and Nalm6. Live cell tracking of receptors on the two cell lines revealed characteristic differences in their dimer dissociation rates and diffusion coefficients. We report here that these differences affect pre-BCR aggregation and consequent signal initiation events. Receptors on Nalm6 cells, which have a lower off-rate and lower diffusion coefficient, more frequently form higher order oligomers than pre-BCR on 697 cells, resulting in higher levels of downstream phosphorylation in the Nalm6 cell line.

Published
2023
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18. Recombinant Antibodies against Mycolactone

Author

Naranjo, Leslie, primary, Ferrara, Fortunato, additional, Blanchard, Nicolas, additional, Demangel, Caroline, additional, D’Angelo, Sara, additional, Erasmus, M. Frank, additional, Teixera, Andre A., additional, and Bradbury, Andrew R.M., additional

Published
2019
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20. Allergen Valency, Dose, and FcεRI Occupancy Set Thresholds for Secretory Responses to Pen a 1 and Motivate Design of Hypoallergens

Author

Mahajan, Avanika, primary, Youssef, Lama A., additional, Cleyrat, Cédric, additional, Grattan, Rachel, additional, Lucero, Shayna R., additional, Mattison, Christopher P., additional, Erasmus, M. Frank, additional, Jacobson, Bruna, additional, Tapia, Lydia, additional, Hlavacek, William S., additional, Schuyler, Mark, additional, and Wilson, Bridget S., additional

Published
2017
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22. Many Routes to an Antibody Heavy-Chain CDR3: Necessary, Yet Insufficient, for Specific Binding.

Author

D'Angelo S, Ferrara F, Naranjo L, Erasmus MF, Hraber P, and Bradbury ARM

Subjects
Amino Acid Sequence, Antigens immunology, Clonal Selection, Antigen-Mediated, Cyclin-Dependent Kinase 2 immunology, Datasets as Topic, Gene Rearrangement, Humans, Immunoglobulin Heavy Chains genetics, Peptide Library, Protein Binding, Structure-Activity Relationship, Antibody Diversity, Complementarity Determining Regions genetics, Immunoglobulin Heavy Chains chemistry, Single-Chain Antibodies genetics
Abstract

Because of its great potential for diversity, the immunoglobulin heavy-chain complementarity-determining region 3 (HCDR3) is taken as an antibody molecule's most important component in conferring binding activity and specificity. For this reason, HCDR3s have been used as unique identifiers to investigate adaptive immune responses in vivo and to characterize in vitro selection outputs where display systems were employed. Here, we show that many different HCDR3s can be identified within a target-specific antibody population after in vitro selection. For each identified HCDR3, a number of different antibodies bearing differences elsewhere can be found. In such selected populations, all antibodies with the same HCDR3 recognize the target, albeit at different affinities. In contrast, within unselected populations, the majority of antibodies with the same HCDR3 sequence do not bind the target. In one HCDR3 examined in depth, all target-specific antibodies were derived from the same VDJ rearrangement, while non-binding antibodies with the same HCDR3 were derived from many different V and D gene rearrangements. Careful examination of previously published in vivo datasets reveals that HCDR3s shared between, and within, different individuals can also originate from rearrangements of different V and D genes, with up to 26 different rearrangements yielding the same identical HCDR3 sequence. On the basis of these observations, we conclude that the same HCDR3 can be generated by many different rearrangements, but that specific target binding is an outcome of unique rearrangements and VL pairing: the HCDR3 is necessary, albeit insufficient, for specific antibody binding.

Published
2018
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