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[ RIDE Setup ]
RIDE is a fast 3D molecular similarity search method based on Atomic Property Fields, developed at MolSoft. RIDE searches databases of compound conformers for molecules that are isosteric to the query, i.e. have similar 3D configurations and distributions of atomic properties. GPU-based implementation is capable of searching ~0.5mln conformers/second on a single GPU card and perform 3D virtual screens of millions of compounds with the level of interactivity comparable to 2D searches. VLS benchmarking on DUDe indicates that RIDE searches produce enrichments on par with much slower standard flexible APF VLS. RIDE applications include:
A simple web-based interface is provided for the ease of use by chemists, or can be used in the ICM-Pro software. In either format, RIDE allows fine-tuning of the queries to generate most desirable hit lists. This includes:
[ RIDE Server Setup | RIDE GPU Benchmark ] Prepare the template to search against:
Download the pre-converted 3D database for screening:
Setup RIDE:
How to set atom weights: You can set weights by changing the Occupancy of each atom from 0-1. By default they are set to 1. To change to 0 or some other value - select the atoms and right click and choose edit Occupancy.
GPU-enabled RIDE server can be installed from Docker container (instructions are contained in download) http://molsoft.com/distrib/docker/RIDE/ After the Docker is installed -paste the URL into URL box, press refresh button next to the database combo to refresh DB list. Other parameters are the same as for local search (see above).
MolSoft has tested RIDE on two GPUs:
Surprisingly, the RIDE performance on RTX was even better ~10%-15% than on the more expensive Tesla. It can be explained because we do not use double precision arithmetic in RIDE superposition, so P100 doesn't give you any advantage and the RTX newer model has higher GPU clock rate. The algorithm performance linearly depends on the size of your template (number of bonds). 0.5 million conformers/sec performance refers the ligand with ~22 bonds. The GPU RAM required for that ligand size is ~200Mb. For multiple templates everything (speed/RAM requirements) is also scaled linearly. The other important requirement for the fast RIDE performance is that conformer DB should be located on SSD drive, otherwise the bottleneck will be just reading data from the disk. In Summary
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