The Current State of Peptide Drug Discovery: Back to the Future?
By Antoine Henninot, J. C. Collins, J. Nuss. Journal of Medicinal Chemistry, 2017
859 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/9dc2d51bfc716a5d55c929a833c83c10c772524f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
- Francesca Grisoni
- Gisbert Schneider
- José Jiménez-Luna
- Nils Weskamp
- Kenneth Atz
- Roderick E. Hubbard
- Markus Hartenfeller
In Molecular Biology
- Francesca Grisoni
- José Jiménez-Luna
- Gisbert Schneider
- Nils Weskamp
- Roderick E. Hubbard
- Markus Hartenfeller
Citations in the corpus
- Artificial intelligence in drug discovery: recent advances and future perspectives (2021, background): “Examples include the modeling of peptides [31], macrocycles, and proteolysis-targeting chimeras (PROTACs) [32].”
- Strategies for Tuning the Selectivity of Chemical Probes that Target Serine Hydrolases (2020, background): “Despite being relatively unexplored in the field of ABPP, the global market for cyclic peptide therapeutics is currently estimated to be over $20 billion (Henninot et al., 2018).”
- Therapeutic peptides: current applications and future directions (2022, background): “ACE inhibition, ACE2 and angiotensin-(1-7) axis in kidney and cardiac inflammation and fibrosis.”