Scoring Function Optimization

Scoring Function Optimization is a computational methodology within protein-ligand docking that systematically refines the mathematical model used to predict binding affinity in order to enhance the accuracy of identifying optimal ligand conformations.

337

Publications

71.3K

Citations

1.2K

Authors

466

Institutions

Publications per year

2017–2026

101

Authors

1.2K

  1. AŠ
    Andrej Šali

    University of California, San Francisco, United States

    6 publications · 934 citations

    6

    h-index

  2. TL
    Thomas Lengauer

    Max Planck Institute for Informatics, Germany

    5 publications · 190 citations

    5

    h-index

  3. WF
    Walter Filgueira de Azevedo

    Pontifícia Universidade Católica do Rio Grande do Sul, Brazil

    5 publications · 288 citations

    5

    h-index

  4. SL
    Shide Liang

    University of Nebraska–Lincoln, United States

    5 publications · 274 citations

    5

    h-index

  5. HJ
    Hualiang Jiang

    Shanghai Institute of Materia Medica, China

    5 publications · 183 citations

    5

    h-index

1–5 of 1.2K

Venues

  1. Journal of Chemical Information and Modeling

    JCIM · 47 publications · 5.6K citations

    28

    h-index

  2. Proteins Structure Function and Bioinformatics

    26 publications · 2.9K citations

    19

    h-index

  3. Bioinformatics

    17 publications · 1.1K citations

    15

    h-index

  4. Journal of Computational Chemistry

    10 publications · 37.8K citations

    10

    h-index

  5. Journal of Computer-Aided Molecular Design

    10 publications · 3.1K citations

    10

    h-index

1–5