A practical guide to large-scale docking

By Brian Joseph Bender, Stefan Gahbauer, Andreas Luttens, Jiankun Lyu, Chase M. Webb, Reed M. Stein, Elissa A. Fink, Trent E. Balius, Jens Carlsson, John J. Irwin and 1 more. Nature Protocols, 2021

431 citations recorded by the source corpus.

How researchers see this paper

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

Computational approaches streamlining drug discovery (2023, background): “%) hit rates in experimental testing 60 , yielding novel hits for many targets with potencies in the 0.1–10-μM range (for those that are published, at least).”
Benchmarking AlphaFold‐enabled molecular docking predictions for antibiotic discovery (2022, methodology): “In view of these observations, it is important to note that docking has been widely used in “one target, many compounds” approaches to enrich for screening hits (Lyu et al , 2019; Bender et al , 2021).”
Artificial intelligence–enabled virtual screening of ultra-large chemical libraries with deep docking (2022, positive): “Very recently, Bender et al. developed a guide for ultra-large docking campaigns, highlighting that computing clusters of 500 – 1,000 CPU cores are required to perform billion-scale virtual screening in a timely manner 46 .”