Computational Enzyme Discovery

Computational Enzyme Discovery is a methodological framework within biocatalyst discovery that employs computational techniques to identify and design enzymatic functions by predicting enzyme-substrate interactions, catalytic mechanisms, and protein structures from sequence or structural data.

121

Publications

9.7K

Citations

586

Authors

239

Institutions

Publications per year

2017–2026

60

Authors

586

  1. DB
    David Baker

    University of Washington, United States

    6 publications · 2.2K citations

    6

    h-index

  2. CD
    Costas D. Maranas

    Pennsylvania State University, United States

    5 publications · 353 citations

    5

    h-index

  3. SC
    Steven C. Almo

    Albert Einstein College of Medicine, United States

    4 publications · 137 citations

    4

    h-index

  4. UT
    Uwe T. Bornscheuer

    Universität Greifswald, Germany

    3 publications · 431 citations

    3

    h-index

  5. DR
    Daniela Röthlisberger

    Howard Hughes Medical Institute, United States

    3 publications · 1.9K citations

    3

    h-index

1–5 of 586

Venues

  1. ACS Catalysis

    9 publications · 987 citations

    9

    h-index

  2. Bioinformatics

    9 publications · 1.4K citations

    9

    h-index

  3. Journal of Chemical Information and Modeling

    JCIM · 8 publications · 276 citations

    8

    h-index

  4. Protein Science

    PS · 5 publications · 699 citations

    5

    h-index

  5. PLoS ONE

    3 publications · 92 citations

    3

    h-index

1–5