Efficient drug lead discovery and optimization.
By W. L. Jorgensen. 2009
616 citations recorded by the source corpus.
Subfields: Cellular and Molecular Neuroscience, Immunology, Organic Chemistry
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- Robert E. W. Hancock
- Gisbert Schneider
- Alexander D. MacKerell
- Christopher D. Fjell
- Jan A. Hiss
- Wenbo Yu
In Immunology
- Robert E. W. Hancock
- Gisbert Schneider
- Alexander D. MacKerell
- Christopher D. Fjell
- Jan A. Hiss
- Wenbo Yu
In Organic Chemistry
- Wenbo Yu
- Alexander D. MacKerell
- Christopher D. Fjell
- Robert E. W. Hancock
- Jan A. Hiss
- Gisbert Schneider
- Hualiang Jiang
- Xiangqian Kong
Citations in the corpus
- Computer-Aided Drug Design Methods (2017, methodology): “Database screening methods are often used for hit identification (59) while a number of methods may be used for hit optimization (4, 24, 60).”
- Designing antimicrobial peptides: form follows function (2011, methodology): “Such computationally demanding exercises have been successfully applied to drug design and optimizatio”
- Computational drug discovery (2012, background): “The efficiency, accuracy and speed of these computational methods largely depend on several technical aspects, including conformation generation and sampling, scoring functions, optimization algorithms, and molecular similarity calculations [7, 11, 15] .”
- An estimated 5% of new protein structures solved today represent a new Pfam family (2013, background): “This information can give important insights into, for example, the effect of mutations such as those caused by some nonsynonymous single-nucleotide polymorphisms or can impact significantly on our ability to design new drugs (Jorgensen, 2009).”