Journal of Chemical Information and ModelingBioinformaticsPeer-reviewed journal article
COFFEE-PRESC: A fast pre-screening method using compound retrieval by pairwise positional relationship of representative fragments
Masayoshi ShimizuiD, Satoshi Yoneyama, Keisuke YanagisawaiD, Yutaka AkiyamaiD
Abstract
Protein-ligand docking is one of the most widely used methods in structure-based virtual screening in the early stages of drug discovery. Its calculations require approximately one minute per compound, making exhaustive evaluation of ultra-large libraries containing billions of molecules computationally impractical. In this study, we propose COFFEE-PRESC (COmpound Filtering by Fragment pair-based Efficient Evaluation for PRE-SCreening), a fast, fragment-based pre-screening method. COFFEE-PRESC first docks fragments in a pre-constructed fragment set to the target protein and enumerates multiple favorable protein-fragment docking poses and then pairs them to consider pairwise positional relationship. The fragment set is composed of a small number of representative fragments that exhibit high similarity to many other fragments, enabling coverage of a large and diverse chemical space. Compounds that contain stuructures similar to fragment pairs are then retrieved through similarity-based searches. This retrieval methodology guarantees that the mutual positional relationship of the two matched fragments does not spatially collide. Finally, the retrieved compounds are evaluated using docking scores of the representative fragments and similarity values between the representative and individual fragments matched in the compound retrieval process. COFFEE-PRESC was 32-fold faster while higher accuracy than Spresso, a existing pre-screening tool, highlighting its potential for application to ultra-large compound library screening. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/692874v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@c9a5eborg.highwire.dtl.DTLVardef@abeddcorg.highwire.dtl.DTLVardef@18d0bfdorg.highwire.dtl.DTLVardef@10e1e33_HPS_FORMAT_FIGEXP M_FIG TOC Graphic C_FIG
- research focus: drug response / drug discovery
- research focus: benchmarking
- approach: experimental assay
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 4th percentile
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- G-screen: Scalable Protein-Aware Virtual Screening through Flexible Ligand Alignment
Nuri Jung, Hahnbeom Park, … Chaok Seok·Journal of CheminformaticsPeer-reviewed·Sep 16, 2026
- Simpatico: accurate and ultra-fast virtual drug screening with atomic embeddings
Jeremiah Gaiser, Travis J. Wheeler·bioRxiv·Jun 8, 2025
- ReverseScreen.ai: Pharmacophore-Guided Reverse Screening Across the Growing Co-Complex Proteome
Steven M. Muskal, George Nicola·bioRxiv·Sep 15, 2026
- FlexAutoDock: A Flexible Platform for Automated Molecular Docking and Virtual Screening of Natural and Synthetic Compounds
Feroj Ahmed, Fahim Faysal, … Nurul Haque Mollah·bioRxiv·Aug 19, 2026
- FlashBind: Towards Accurate and Efficient Structure-based Virtual Screening
Songlin Jiang, Yifan Chen, … Wengong Jin·bioRxiv·Aug 21, 2026
- Learning a PRECISE language for small-molecule binding
Mert Erden, Xuting Zhang, … Lenore Cowen·bioRxiv·Jan 5, 2026