Ligand-based Selectivity Modeling
Ligand-Based Selectivity Modeling is a computational methodology in medicinal chemistry that predicts the selectivity profile of bioactive compounds by analyzing ligand structural and physicochemical features, differentiating it from structure-based approaches through its exclusive reliance on ligand data without requiring target protein structural information.
52
Publications
1.9K
Citations
211
Authors
106
Institutions
Publications per year
2017–2026
14
52
Prediction of Stereochemistry using Q2MM
Eric Hansen, Anthony R. Rosales, Brandon Tutkowski et al. · Accounts of Chemical Research · 2016 · 116 citations
Tahir Ali Chohan, Jiongjiong Chen, Jiongjiong Chen et al. · Molecular BioSystems · 2016 · 78 citations
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University of Utah
Salt Lake City, United States
3 h-index
8 publications
618 citations
Scripps Research Institute
San Diego, United States
2 h-index
2 publications
70 citations

University of Cape Town
Rondebosch, South Africa
2 h-index
7 publications
140 citations
University of Florence
Florence, Italy
2 h-index
7 publications
255 citations

Peking University
Beijing, China
2 h-index
2 publications
127 citations

Universitat Autònoma de Barcelona
Cerdanyola del Vallès, Spain
2 h-index
11 publications
666 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
6 publications
71 citations
Frumkin Institute of Physical Chemistry and Electrochemistry
Moscow, Russia
2 h-index
2 publications
25 citations
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JCIM · 9 publications · 352 citations
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6 publications · 325 citations
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3 publications · 92 citations
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3 publications · 60 citations
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3 publications · 69 citations
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