P. Sormanni

Targeted protein editing with an antibody-based system

This paper introduces an antibody-based system for post-translational modification of endogenous proteins in complex environments, demonstrating its use on green fluorescent protein and beta-2 microglobulin.

AbNatiV: VQ-VAE-based assessment of antibody and nanobody nativeness for hit selection, humanisation, and engineering

AbNatiV assesses antibody and nanobody nativeness using a VQ-VAE model, enabling hit selection, humanisation, and engineering with improved performance over conventional methods.

Sequence-based prediction of the solubility of peptides containing non-natural amino acids

The paper presents CamSol-PTM, a computational method to predict solubility of peptides with non-natural amino acids, validated through experimental testing of 30 variants.

Multi-dimensional protein solubility optimization with an ultra-high-throughput microfluidic platform

This paper introduces a high-throughput microfluidic platform for protein solubility screening, enabling rapid and efficient optimization of formulation additives and mutations.

Automated optimisation of solubility and conformational stability of antibodies and proteins

This study introduces an automated computational method to co-optimize solubility and conformational stability of antibodies, validated on six antibodies with improved developability without affecting antigen-binding.

Sequence-based pH-dependent prediction of protein solubility using CamSol

The paper extends the CamSol method to predict protein solubility at different pH levels and validates it on antibodies and other proteins.

Discovery of Potent Inhibitors of α-Synuclein Aggregation Using Structure-Based Iterative Learning

This paper uses structure-based machine learning to identify potent small molecule inhibitors of α-synuclein aggregation, achieving compounds two orders of magnitude more potent than previous reports.