Kelvin Lau

This study benchmarks DSF across labs, showing variability in thermal stability parameters due to instruments, workflows, and fluorescence readouts, with harmonization and centralized analysis improving consistency.

This paper introduces an AI-based framework for designing responsive protein oligomers that assemble in response to chemical or phosphorylation triggers, validated through experimental testing.

This study introduces a method to engineer hydrophobicity in a bacterial laccase using non-canonical amino acids, resulting in improved catalytic activity.

FragmentScope uses learned protein surface representations to guide fragment placement and small molecule design, achieving accurate placement and promising lead compounds.

The paper introduces TCR specificity profiles to identify key determinants of TCR-epitope recognition and shows their ability to predict cross-reactivity and interpret machine learning models.

This study investigates ADGRG1 activation mechanisms through mechanical and allosteric pathways, showing force direction determines signaling via GAIN domain dynamics and introducing engineered variants with tailored sensitivity.

This paper designs light-regulated dynamic proteins using deep learning, showing precise optogenetic control of cellular processes.

The paper shows that a transposable element-derived domain in KRAB zinc-finger proteins enables new transcription factor functions through trimerization and condensate formation.

This paper applies low-dose cryo-EM and 4D-STEM ptychography to achieve sub-nanometer resolution 3D reconstructions of frozen hydrated proteins.

The paper screens bat samples for coronaviruses, identifies novel strains, and assesses their potential to infect humans.