Combinatorial Lead Generation

Combinatorial Lead Generation is a methodological approach in drug discovery that systematically combines chemical building blocks to create diverse compound libraries for high-throughput screening against biological targets to identify novel lead molecules.

100

Publications

5.1K

Citations

508

Authors

129

Institutions

Publications per year

2017–2026

5

Authors

508

  1. MJ
    Mark J. Kurth

    University of California, Davis, United States

    4 publications · 367 citations

    4

    h-index

  2. GS
    Gisbert Schneider

    ETH Zurich, Switzerland

    3 publications · 215 citations

    3

    h-index

  3. LJ
    Luis J. V. Galietta

    Istituto Giannina Gaslini, Italy

    2 publications · 269 citations

    2

    h-index

  4. MP
    Maurizio Pellecchia

    Sanford Burnham Prebys Medical Discovery Institute, United States

    2 publications · 110 citations

    2

    h-index

  5. AS
    A. S. Verkman

    University of California, San Francisco, United States

    2 publications · 269 citations

    2

    h-index

1–5 of 508

Venues

  1. Journal of Medicinal Chemistry

    9 publications · 571 citations

    8

    h-index

  2. PubMed

    Repository · 7 publications · 133 citations

    7

    h-index

  3. Bioorganic & Medicinal Chemistry Letters

    7 publications · 424 citations

    7

    h-index

  4. Journal of Chemical Information and Modeling

    JCIM · 5 publications · 258 citations

    5

    h-index

  5. Molecular Diversity

    4 publications · 100 citations

    4

    h-index

1–5