Christian B. Macdonald

This study uses deep mutational pharmacology to show how different residues in the -opioid receptor determine the efficacy of opioids by shaping distinct activation mechanisms.

Lilace improves variant effect estimation in FACS-based DMS by providing uncertainty quantification and better FDR control.

The paper uses deep mutational scanning to analyze MET kinase domain mutations and their resistance to 11 inhibitors, identifying resistance and sensitizing mutations and improving prediction with a protein language model.

The paper identifies proton-sensing mechanisms in GPCRs using cryo-EM and deep mutational scanning, revealing a network of residues rather than a single site for proton recognition.

The paper introduces cdsFM, a suite of codon-resolution large language models that predict the functional consequences of synonymous codon choices and identify pathogenic variants.

This study performs a deep mutational scan on EccD3 in M. smegmatis to understand its role in the ESX-3 secretion system and its importance for mycobacterial survival.

Rosace improves analysis of deep mutational scanning data by using Bayesian shrinkage and position information, outperforming existing methods in simulations and real data.

The paper introduces DIMPLE, a method for generating indel and missense mutation libraries, and demonstrates its application in studying the impact of mutations on protein function.