Virtual Screening
Virtual Screening is a computational method in drug discovery that systematically evaluates large libraries of chemical compounds through molecular modeling techniques to prioritize those with the highest predicted affinity for a target biomolecule, distinguishing it from experimental screening by enabling in silico prioritization of potential drug candidates based on structural and physicochemical complementarity.
9.5K
Publications
538.5K
Citations
36.2K
Authors
5.8K
Institutions
Publications per year
2017–2026
5.2K
Variants
In Silico Screening
9.5K
1–5 of 9.5K
36.2K
35
h-index
33
h-index
University of North Carolina at Chapel Hill, United States
40 publications · 5.1K citations
32
h-index
32
h-index
30
h-index
1–5 of 36.2K
5.8K

Centre National de la Recherche Scientifique
Paris, France
57 h-index
184 publications
12.6K citations
University of California, San Francisco
San Francisco, United States
50 h-index
84 publications
17.1K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
49 h-index
89 publications
11.7K citations

Chinese Academy of Sciences
Beijing, China
46 h-index
181 publications
8.6K citations
Scripps Research Institute
San Diego, United States
41 h-index
60 publications
50.6K citations
Inserm
Paris, France
41 h-index
96 publications
6.7K citations
University of Cambridge
Cambridge, United Kingdom
41 h-index
69 publications
5.6K citations
Shanghai Institute of Materia Medica
Pudong, China
40 h-index
110 publications
5.2K citations
1–8 of 5.8K
JCIM · 873 publications · 63.7K citations
111
h-index
365 publications · 40.8K citations
94
h-index
144 publications · 10.7K citations
54
h-index
207 publications · 21.2K citations
52
h-index
283 publications · 9K citations
49
h-index
1–5