Daniel Herschlag

This paper introduces SPARKfold, a microfluidic platform to measure protein unfolding rates for thousands of variants, validating its accuracy and demonstrating its utility in studying kinetic stability.

This paper introduces Rho analysis to study RNA folding pathways using mutations and isolated contacts, revealing multiple folding pathways and their modulation.

This study uses high-throughput biochemical assays to analyze SHP2 variants, revealing that dysregulated autoinhibition drives disease and that allosteric inhibitors stabilize a partially active conformation.

The paper identifies proteolytic activation mechanisms in prokaryotic antiviral defense modules and shows their functional diversity and convergence with stress responses.

SEISMICgraph is a web-based tool for visualizing RNA structure data from chemical probing experiments, enabling comparison across sequences and conditions.

This paper evaluates current biomolecular structure prediction models using physics-based criteria, revealing widespread errors in capturing atomic interactions and conformational preferences.

Ensemble-function analyses provide a quantitative model for serine protease catalysis, reveal previously unknown conformational features that contribute to their catalysis, and identify a structural motif that underlie these features and has evolved in >100 different enzymes from 32 protein folds.

This study uses high-throughput thermodynamic measurements to explore how sequence changes affect the binding properties of RNA tetraloop receptor motifs, revealing complex sequence-fitness landscapes.

The paper introduces uPIC-M, a method to efficiently create clonal single mutant libraries for high-throughput protein biochemistry, achieving high recovery rates and cost-effectiveness.