Ultra Large Library Virtual Screening in MolSoft ICM |
Method | Approach | Target Structure(s) Required | High Affinity Lead(s) | Speed | Notes |
---|---|---|---|---|---|
RIDE | Ligand-Based | No | Yes | ~1.5M confs/sec on latest GPU RTX 4090 | Ligand-based screening approach using MolSoft's 3D Pharmacophore method Atomic Property Fields Any prepared giga size library in molt format can be screened. |
RIDE-Dock | Ligand- and Structure-based hybrid | Yes | Yes | Speed optimized by RIDE | Ligand-based RIDE screen followed by Structure-based virtual ligand screening of top scoring chemicals. |
Method | Approach | Target Structure(s) Required | High Affinity Lead(s) | Speed | Notes |
---|---|---|---|---|---|
V-SYNTHES + ICM-VLS | Fragment-based and enumeration | Yes | No | ~2 weeks with a 250 VLS Cluster License | Efficiently screen the 21B Enamine Real Space Set using an initial fragment-based filter followed by enumeration and structure-based docking. |
RIDGE BETA | Structure-based | Yes | No | 100 chemicals/sec on latest GPU RTX 4090 | Rapid structure-based GPU docking engine. Any prepared giga sized library in molt format can be screened. |
Giga Screen | Deep Learning | Yes | No | Speed optimized by RIDGE | The GigaScreen method combines machine learning and deep learning tools to tackle the computational intensity of screening very large chemical databases. Any prepared giga sized library in molt format can be screened. |
Available databases include the following which are available as a free download here.