Accurate prediction of the relative potencies of members of a series of kinase inhibitors using molecular docking and MM-GBSA scoring.

By Paul D. Lyne, M. Lamb, J. Saeh. Journal of Medicinal Chemistry, 2006

653 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Organic Chemistry

View Paper: https://www.semanticscholar.org/paper/ca8a3c891850d24c7e9e4b534af115f1f55ddb0f

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. Shengyou Huang
2. Xiaoqin Zou
3. Yumeng Yan
4. Pei-Zhang Zhou
5. Huanyu Tao
6. John Karanicolas
7. David K. Johnson
8. Stefano Moro

In Organic Chemistry

1. Shengyou Huang
2. Xiaoqin Zou
3. John Karanicolas
4. David K. Johnson
5. Stefano Moro
6. Veronica Salmaso

Citations in the corpus

• Advances and Challenges in Protein-Ligand Docking (2010, background): “The Poisson-Boltzmann/surface area (PB/SA) models [89–99] and the generalized-Born/surface area (GB/SA) models [100–111] are typical examples of such implicit solvent models.”