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Bioscience / Engineering / synthetic biology

Protein engineering

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Displaying 1 - 5 of 5

Functional Profiling of Thousands of Sequence-Diverse Protease Homologs with GROQ-seq

May 5, 2026
Author(s)
James McLellan, Svetlana Ikonomova, Shwetha Sreenivasan, Alan Amin, Catherine Baranowski, Amanda Reider Apel, Peter Kelly, David Ross, Aviv Spinner
High-quality datasets that span broad sequence diversity are essential for understanding protein sequence–function relationships beyond local mutational landscapes. Here, we applied Growth-based Quantitative Sequencing (GROQ-seq) to measure function across

GROQ-seq Datasets Across Transcription Factors (LacI, RamR, VanR), T7 RNA Polymerase and TEV Protease

April 19, 2026
Author(s)
Aviv Spinner, Shwetha Sreenivasan, James McLellan, Svetlana Ikonomova, Dana Cortade, Simon d'Oelsnitz, Kristen Sheldon, Olga Vasilyeva, Nina Alperovich, Anjali Chadha, Lily Nematollahi, Andi Dhroso, Zach Sisson, Corey Hudson, Erika DeBenedictis, Peter Kelly, Amanda Reider Apel, David Ross, Catherine Baranowski
Predicting any protein's function from its sequence alone would be a significant breakthrough in molecular biology. Although machine learning approaches have sought to tackle this, their limited generalizability reflects the absence of sufficiently large

GROQ-seq Enables Cross-site Reproducibility for High-Throughput Measurement of Protein Function

April 9, 2026
Author(s)
Aviv Spinner, Amanda Reider Apel, David Ross, Svetlana Ikonomova, Dana Cortade, Catherine Baranowski, Andi Dhroso, Kristen Sheldon, Courtney Tretheway, Erika DeBenedictis, Corey Hudson
High-throughput functional assays are increasingly used to generate large-scale protein function datasets for protein engineering and machine learning applications. However, the utility of such datasets depends on the reproducibility of the underlying

Mapping the phenotypic landscape of a transcriptional repressor using Deep Mutational Scanning and Growth-based Quantitative Sequencing

December 2, 2025
Author(s)
Zachary Jansen, Xuan Le, Qiyao Wei, Devon Kulhanek, Nina Alperovich, Olga Vasilyeva, Andrew Gilmour, David Ross, Ross Thyer
CymR is a TetR-family transcriptional repressor that recognizes a well-defined operator sequence in the promoter PcymRC. The native ligand cuminic acid and a series of structurally related aromatic acids can bind at an allosteric site and induce a

Experimental Evaluation of AI-Driven Protein Design Risks Using Safe Biological Proxies

June 20, 2025
Author(s)
Svetlana Ikonomova, Bruce Wittmann, Fernanda Piorino Macruz de Oliveira, David Ross, Samuel Schaffter, Olga Vasilyeva, Elizabeth Strychalski, Eric Horvitz, James Diggans, Sheng Lin-Gibson, Geoffrey Taghon
Advances in machine learning are providing new abilities for engineering biology, promising leaps forward with beneficial applications. At the same time, these advances raise concerns about biosecurity. Recently, Wittmann et al. described an in silico
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