PRODIGY: a web server for predicting the binding affinity of protein-protein complexes

By Li C. Xue, João P. G. L. M. Rodrigues, Panagiotis L. Kastritis, Alexandre M. J. J. Bonvin, Anna Vangone. Bioinform., 2016

1,281 citations recorded by the source corpus.

Subfields: Cell Biology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/00bf2efae289b26fec4366d1193466fa82dfe907

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Alexandre M. J. J. Bonvin
2. João P. G. L. M. Rodrigues
3. Zeynep Kurkcuoglu
4. Panagiotis I. Koukos
5. Rodrigo Vargas Honorato
6. Li C. Xue
7. Jorge Roel‐Touris
8. Adrien S. J. Melquiond

Citations in the corpus

• Structural Biology in the Clouds: The WeNMR-EOSC Ecosystem (2021, background): “, 2020) Prodigy Local No No (Xue et al., 2016; Vangone et al., 2018; Jiménez-García et al., 2019) SpotON Local Yes No (Moreira et al.”
• Performance of HADDOCK and a simple contact-based protein–ligand binding affinity predictor in the D3R Grand Challenge 2 (2017, methodology): “Recently, we have introduced a residue–residue contact-based method for the prediction of the binding affinity in Target R M S D ( Å ) protein–protein complexes [40], implemented in the web-server PRODIGY (PROtein binDIng enerGY prediction) [41, 42].”