Author

J. S. Chang

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Microbiology· 2 Biochemistry· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 3 Organism:mouse· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Approach:genetic perturbation / CRISPR· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:protein folding & dynamics· 1

Frequent Co-Authors

H. Wu· 2 shared S. Li· 2 shared A. A. Lee· 1 shared A. A. Vinogradov· 1 shared A. B. Vogel· 1 shared A. Balesano· 1 shared A. Behzadi· 1 shared A. Ephron· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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Curved chords = mutual co-authorship

2 shared papersMicrobiology

H. Wu

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Discovery of SARS-CoV-2 papain-like protease (PLpro) inhibitors with efficacy in a murine infection model

M. R. Garnsey, M. C. Robinson, L. T. Nguyen, R. Cardin, J. Tillotson, E. Mashalidis, Y. Aijia, L. Aschenbrenner, A. Balesano, A. Behzadi, B. Boras, J. S. Chang, H. Eng, A. Ephron, T. Foley, , A. A. Lee

This study identifies potent SARS-CoV-2 PLpro inhibitors using machine learning, showing efficacy in a mouse model of COVID-19.

bioRxiv · Jan 26, 2024 · PreprintMicrobiology

Preclinical Characterization of the Omicron XBB.1.5-Adapted BNT162b2 COVID-19 Vaccine

K. Modjarrad, Y. Che, W. Chen, H. Wu, C. I. Cadima, A. Muik, M. S. Maddur, K. R. Tompkins, L. T. Martinez, H. Cai, M. Hong, S. Mensah, B. Cumbia, L. Falcao, J. S. Chang, , K. Swanson

The monovalent Omicron XBB.1.5-adapted BNT162b2 mRNA vaccine elicits stronger neutralizing antibody responses against XBB.1.5 and related sublineages than the bivalent Wild Type + Omicron BA.4/5 vaccine.

bioRxiv · Nov 17, 2023Immunology

Accurate models of substrate preferences of post-translational modification enzymes from a combination of mRNA display and deep learning

A. A. Vinogradov, J. S. Chang, H. Onaka, Y. Goto, H. Suga

The paper develops a platform combining mRNA display and deep learning to accurately model substrate preferences of PTM enzymes, showing high accuracy and complexity in enzyme specificity.

bioRxiv · Feb 14, 2022Biochemistry

A chemical-genetic map of the pathways controlling drug potency in Mycobacterium tuberculosis

S. Li, N. C. Poulton, J. S. Chang, Z. A. Azadian, M. A. Dejusus, N. Ruecker, M. D. Zimmerman, K. Eckartt, B. Bosch, C. A. Engelhart, D. Sullivan, M. Gengenbacher, V. A. Dartois, D. Schnappinger, J. M. Rock

This study uses a CRISPR interference platform to map drug resistance pathways in Mtb, identifying new intrinsic and acquired resistance mechanisms and potential drug targets.

bioRxiv · Nov 27, 2021 · PreprintMicrobiology