Aubin Ramon

Deep learning assessment of nativeness and pairing likelihood for antibody and nanobody design with AbNatiV2

This paper introduces AbNatiV2 and p-AbNatiV2, deep learning models for assessing nativeness and pairing likelihood in antibodies and nanobodies, showing improved performance on held-out tests.

Engineering armoured in vivo CAR T cells through targeted delivery and transient mRNA gating

This paper develops an in vivo CAR T cell platform using lipid nanoparticles and T-trex strategy to enhance safety, efficacy, and tumor control.

Disulphide and sequence-encoded conformational priors guide nanobody structure prediction

This paper introduces NbForge, a nanobody folding model that improves prediction of HCDR3 blueprint and disulphide bonds, achieving accuracy comparable to large predictors with faster speed.

A direct computational assessment of vinculin-actin unbinding kinetics reveals catch bonding behavior

This study uses molecular dynamics simulations to assess vinculin-actin unbinding kinetics, revealing catch bonding behavior under force and showing how directional forces influence bond states.

Development of potent humanized TNFα inhibitory nanobodies for therapeutic applications in TNFα-mediated diseases

This study develops and characterizes humanized TNFα inhibitory nanobodies with picomolar potency and low immunogenicity for therapeutic use in TNFα-mediated diseases.

NewroBus for the brain: humanized TfR1-targeting nanobodies with high BBB permeability and cargo transport capacity

This paper develops humanized TfR1-targeting nanobodies (NewroBus) that cross the BBB and deliver therapeutic payloads to the CNS.

Highly potent novel multi-armoured IL13Rα2 CAR-T subverts the immunosuppressive microenvironment of Glioblastoma

This paper develops a novel CAR-T cell therapy for glioblastoma that overcomes immunosuppression and improves persistence through a multi-armoured design.

Prediction of protein biophysical traits from limited data: a case study on nanobody thermostability through NanoMelt

NanoMelt, a ridge-stacked ensemble of regressors on four diverse sequence embeddings, predicts nanobody melting temperature from 640 curated sequences, reaching Spearman 0.832 under nested cross-validation.