Computational Macrocycle Design
Computational Macrocycle Design is a computational methodology that specializes in the rational design and optimization of macrocyclic compounds for drug discovery by leveraging molecular modeling, conformational sampling, and predictive algorithms to address the unique structural and pharmacological challenges posed by large-ring systems.
51
Publications
2K
Citations
307
Authors
109
Institutions
Publications per year
2017–2026
25
Parents
51
Tools and rules for macrocycles
Christian Heinis · Nature Chemical Biology · 2014 · 120 citations · Full text
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University of California, San Francisco, United States
3 publications · 131 citations
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109
Stanford University
Stanford, United States
4 h-index
10 publications
740 citations
University of California, San Francisco
San Francisco, United States
4 h-index
13 publications
562 citations
University of Washington
Seattle, United States
4 h-index
32 publications
1.9K citations

Uppsala University
Uppsala, Sweden
3 h-index
12 publications
577 citations
University of Southampton
Southampton, United Kingdom
2 h-index
5 publications
145 citations
Flatiron Health (United States)
New York, United States
2 h-index
4 publications
270 citations
Schrodinger (United States)
New York, United States
2 h-index
10 publications
594 citations

Johns Hopkins University
Baltimore, United States
2 h-index
2 publications
114 citations
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JCIM · 5 publications · 122 citations
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JACS · 4 publications · 217 citations
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3 publications · 85 citations
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2 publications · 55 citations
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2 publications · 38 citations
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