De novo drug design.
By Markus Hartenfeller, Gisbert Schneider. 2010
159 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Molecular Biology, 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 Computational Theory and Mathematics
- Gisbert Schneider
- Markus Hartenfeller
- Alán Aspuru-Guzik
- Yudong Cao
- Jonathan Romero
- Maria Batool
- Sangdun Choi
- Bilal Ahmad
In Molecular Biology
- Markus Hartenfeller
- Alán Aspuru-Guzik
- Gisbert Schneider
- Jonathan Romero
- Yudong Cao
- Maria Batool
- Sangdun Choi
- Bilal Ahmad
In Organic Chemistry
- Alán Aspuru-Guzik
- Jonathan Romero
- Yudong Cao
- Gisbert Schneider
- Markus Hartenfeller
- Maria Batool
- Sangdun Choi
- Bilal Ahmad
Citations in the corpus
- A Structure-Based Drug Discovery Paradigm (2019, background): “The gist of this approach is to develop chemical structures of the small molecules that bind to the target binding cavity with good affinity [39].”
- Machine Learning in Drug Discovery: A Review (2021, methodology): “De novo Drug Architecture progressed unique chemical structures by adjusting or balancing the target interest (Hartenfeller and Schneider 2010).”
- Potential of quantum computing for drug discovery (2018, methodology): “An alternative approach to vHTS for hit search is de novo design of ligands [61, 62].”
- Enabling future drug discovery by de novo design (2011, methodology): “109 Many stochastic optimization algorithms employ heuristics, i.e., they cannot guarantee to find the SCHEME 1 | The software DOGS 80 generates new compounds in a reaction-driven, fragment-based fashion so that the designs mimic a given reference compound (Raloxifene, a modulator of the human…”