FRAGSITEcombM is a ligand virtual screening method that further improves to our previous best methods by combining the Morgan fingerprint (MF) with the originally used PubChem fingerprint and FP2 fingerprint in FINDSITEcomb2.0, FARGSITE and FRAGSITE2 resulting in FINDSITEcomb2.0M, FRAGSITEM, FRAGSITE2M. We then benchmarked FINDSITEcomb2.0M, FRAGSITEM, FRAGSITE2M and the composite meta-approach FRAGSITEcombM. On the 102 target DUD-E set, the 1% enrichment factor (EF1%) and area under the precision-recall curve (AUPR) of the meta-approach FRAGSITEcombM increased from 42.0/0.59 by FINDSITEcomb2.0M to 47.6/0.72. This 0.72 AUPR is significantly better than that of the state-of-the-art deep learning-based method DenseFS’s AUPR of 0.443. An independent test on the 81 targets DEKOIS2.0 set shows that EF1%/AUPR increases from 18.3/0.520 to 23.1/0.683. An ablation investigation shows the MF contributes to most of the improvement of all four approaches.
This web service is freely available to all academic users and not-for-profit institutions.
Commercial users wishing an evaluation copy should contact skolnick@gatech.edu.
Commercial users may license the FRAGSITEcombM software after completing the license agreement and sending it to skolnick@gatech.edu. Download the license agreement license agreement.
If you find this service useful, please cite the following paper: Zhou, H, Skolnick J. 2024. Utility of the Morgan Fingerprint in Structure-Based Virtual Ligand Screening. J. Phys. Chem. B. 2024: 128(22): 5363–5370. https://doi.org/10.1021/acs.jpcb.4c01875. PDF
For virtual ligand screening: screening a protein against library of compounds, click here.
This site is maintained by Dr. H. Zhou: hzhou3@gatech.edu