William Gerwick

About

William Gerwick, Ph.D., is a Distinguished Professor at the Skaggs School of Pharmacy and Pharmaceutical Sciences at UC San Diego. His research focuses on exploring the unique natural products of marine algae and cyanobacteria for biomedical applications. His group has been involved in discovering and evaluating these organisms' highly unusual metabolites for their potential in cancer, inflammation, infectious diseases including tropical diseases such as malaria, Chagas’ disease, and leishmaniasis, as well as neurochemical pathways, antiviral activity against SARS-CoV-2, and agricultural uses. Dr. Gerwick's team uses SCUBA to collect marine samples worldwide and grows many of these organisms in the laboratory, testing extracts for bioactivity, and isolating active compounds using NMR and MS. They have developed new methods of structure analysis, such as the Deep Learning-based SMART technology, and collaborate with academic and industrial partners to develop lead molecules through synthetic chemistry and molecular modeling, especially targeting parasitic diseases.

Research topics

• Biology
• Chemistry
• Computational biology
• Artificial Intelligence
• Genetics
• Computer Science
• Bioinformatics
• Biochemistry
• Chromatography
• Biological system

Selected publications

• Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra

  Nature Biotechnology · 2020 · 794 citations

  DOI

• NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products

  Journal of Natural Products · 2021-10-18 · 485 citations

  articleOpen accessCorresponding

  Computational approaches such as genome and metabolome mining are becoming essential to natural products (NPs) research. Consequently, a need exists for an automated structure-type classification system to handle the massive amounts of data appearing for NP structures. An ideal semantic ontology for the classification of NPs should go beyond the simple presence/absence of chemical substructures, but also include the taxonomy of the producing organism, the nature of the biosynthetic pathway, and/…

  PublisherOA PDFDOI

• microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data

  Nature Microbiology · 2024 · 109 citations

  microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding o…

  PublisherOA PDFDOI

• Potent Anti-SARS-CoV-2 Activity by the Natural Product Gallinamide A and Analogues via Inhibition of Cathepsin L

  Journal of Medicinal Chemistry · 2021 · 84 citations

  values in the nanomolar range. Reduced antiviral activity was observed in cells overexpressing transmembrane protease, serine 2 (TMPRSS2); however, a synergistic improvement in antiviral activity was achieved when combined with a TMPRSS2 inhibitor. These data highlight the potential of cathepsin L as a COVID-19 drug target as well as the likely need to inhibit multiple routes of viral entry to achieve efficacy.

  PublisherOA PDFDOI

• A universal language for finding mass spectrometry data patterns

  Nature Methods · 2025-05-12 · 44 citations

  articleOpen access

  Despite being information rich, the vast majority of untargeted mass spectrometry data are underutilized; most analytes are not used for downstream interpretation or reanalysis after publication. The inability to dive into these rich raw mass spectrometry datasets is due to the limited flexibility and scalability of existing software tools. Here we introduce a new language, the Mass Spectrometry Query Language (MassQL), and an accompanying software ecosystem that addresses these issues by enabli…

  PublisherDOI

Recent grants

• NIH Grant R23CA042850

  NIH · $141k · 1990

• NIH Grant U01TW006634

  NIH · $7.8M · 2015

• Unified Computation Tools for Natural Products research

  NIH · $547k · 2013–2025

Frequent coauthors

• Lena Gerwick

  Scripps Institution of Oceanography

  285 shared

• Pieter C. Dorrestein

  University of California, San Diego

  247 shared

• Evgenia Glukhov

  Scripps Institution of Oceanography

  187 shared

• Kerry L. McPhail

  Oregon State University

  167 shared

• Jehad Almaliti

  University of California, San Diego

  160 shared

• Niclas Engene

  Florida International University

  148 shared

• Albán R. Pereira

  143 shared

• Thomas F. Murray

  126 shared

Awards & honors

• Fellow, American Society of Pharmacognosy (2008)
• UC San Diego Chancellor's Associates Faculty Excellence Awar…
• American Society of Pharmacognosy Norman Farnsworth Research…
• Fellow of the American Association for the Advancement of Sc…
• Paul Scheuer Award, Gordon Conference on Marine Natural Prod…

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