Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
November 7, 2022Journal of Chemical Information and Modeling

MILCDock: Machine Learning Enhanced Consensus Docking for Virtual Screening in Drug Discovery

View Full Paper
Ask AI
Bookmark
Share

Authors

CMConnor J. MorrisJSJacob SternBSBrenden Stark

Discussion

Loading...

Member takes

Overview

Key Points

Key points are not available for this paper at this time.

Cite This Study

Morris et al. (2022) studied this question.

synapsesocial.com/papers/69d9a5417f18ff2fefa3c232https://doi.org/10.1021/acs.jcim.2c00705
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Improving scoring-docking-screening powers of protein-ligand scoring functions using random forest2016 · 349 citations
  2. 2Benchmarking Sets for Molecular Docking2006 · 1,342 citations
  3. 3Comprehensive evaluation of ten docking programs on a diverse set of protein–ligand complexes: the prediction accuracy of sampling power and scoring power2016 · 992 citations
  4. 4Maximum Unbiased Validation (MUV) Data Sets for Virtual Screening Based on PubChem Bioactivity Data2009 · 428 citations
  5. 5Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking2012 · 2,505 citations