CovalentDock: Automated covalent docking with parameterized covalent linkage energy estimation and molecular geometry constraints

By Xuchang Ouyang, Shuo Zhou, C. Su, Z. Ge, Runtao Li, Chee Keong Kwoh. 2013

129 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Computational Chemistry & Drug Discovery

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

1. Stefano Forli
2. David S. Goodsell
3. Arthur J. Olson
4. Abdo A. Elfiky
5. Michel F. Sanner
6. Garrett M. Morris
7. John Karanicolas
8. Daniel Seeliger

In Molecular Biology

1. Stefano Forli
2. David S. Goodsell
3. Arthur J. Olson
4. Abdo A. Elfiky
5. Garrett M. Morris
6. Shengyou Huang
7. B. L. de Groot
8. Daniel Seeliger

In Organic Chemistry

1. Arthur J. Olson

In Computational Chemistry & Drug Discovery

1. Stefano Forli
2. David S. Goodsell
3. Arthur J. Olson
4. Abdo A. Elfiky
5. C. Hetényi
6. D. van der Spoel
7. Diane Joseph-McCarthy
8. Stefano Moro

Citations in the corpus

• Structure-Based Virtual Screening for Drug Discovery: Principles, Applications and Recent Advances (2014, unknown): “CovalentDock [128] Covalent docking http://docking.”
• Covalent docking using autodock: Two‐point attractor and flexible side chain methods (2016, background): “With the recent increased interest in covalent inhibitors, a variety of methods have been reported for using computational docking to predict the binding of covalently bound compounds (see, for instance, Refs 4–7).”
• The design and development of covalent protein-protein interaction inhibitors for cancer treatment (2020, background): “The latter involves sampling the space around a single flexible side chain in order to assess the interaction between the protein attachment point and the covalent ligand [75].”