Matthew K. Howard

PhD Candidate, UCSF | GPCRs | Functional Genomics | Structural Biology | Pharmacology

Last updated: October 2026

About

I develop and apply high-throughput experimental platforms—primarily deep mutational scanning—to understand GPCR function, pharmacology, and evolution at single-residue resolution. I integrate these approaches with structural biology, molecular simulation, and cell biology to reveal how receptors sense their environment and respond to drugs.

I'm currently a PhD candidate at UCSF working in the Coyote-Maestas and Manglik labs where I collaborate broadly across disciplines including statistics, machine learning, and various "-omics" approaches.

Before UCSF, I graduated from Washington University in St. Louis with degrees in chemistry and biology. At WashU, I worked in the Jackrel lab studying protein disaggregases and amyloid biology.

Find me here: email · Bluesky · Twitter/X · GitHub · LinkedIn · Google Scholar · ORCID

Research

Proton-sensing GPCRs

How do cells detect changes in pH? I used deep mutational scanning of GPR68 to map the complete sequence determinants of proton sensing, combining multiphenotypic screening of both expression and function to identify a conserved polar and charged network that acts as a molecular pH sensor. Together with cryo-EM structures, molecular simulation, and pharmacology, this work revealed how evolution has tuned GPCR sensitivity to extracellular acidification—relevant to inflammation, ischemia, and cancer biology. Published in Cell (2025).

Deep Mutational Pharmacology

A longstanding question in pharmacology is how different ligands at the same receptor produce different signaling outputs. Here I use deep mutational scanning to bring a new lens to that question. Using the μ-opioid receptor (μOR) as a model, I make ~400,000 measurements of variant effects across 15 opioid ligands and uncover distinct, efficacy-specific patterns. Weak and strong agonists depend on different regions of the receptor, suggesting they activate it by distinct mechanisms. We also find a mutant that converts antagonists and partial agonists into full agonists, and begin to dissect the allosteric networks used by different ligands. Preprint on bioRxiv (2026); explore the data in the μOR-DMS data browser.

Recent Sidequests

Astera Hidden Science Competition: I love this idea—plenty of solid, complete datasets never get published simply because they don't fit the narrative of a paper. I submitted a proposal to release two such datasets from my PhD: a three-phenotype deep mutational scan of GPR161 and a pooled basal cAMP screen across the human GPCRome, which together map the sequence determinants of constitutive GPCR signaling. Read the proposal (PDF) →

Publications

Google Scholar may be more current. Please Email me if paywalls get in your way.

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PhD work at UCSF

From WUSTL

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