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Searching at the Speed of Byte: Accelerating Similarity and Substructure Searches

The number of drug-like molecules that could exist is staggering.  Estimates range as high as 1060, more than the number of atoms in the Universe.

Commercially available collections of synthetically accessible drug-like molecules now number in the billions, and these collections are expanding regularly, while virtual collections of compounds can exceed a trillion molecules.

In order to address the challenges posed by the rapid increase in the size of accessible chemical space, OpenEye Scientific has been focused on accelerating our molecular search algorithms for both the CPU and GPU, specifically similarity search in GraphSim TK and substructure search in OEChem TK. As a result of these recent upgrades, you now are able to search a billion molecules in seconds.  

[GraphSim TK, OEChem TK]
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Recommendation System for Compound Selection

Just recently, Swann et al. of Abbott Labs published "A Unified, Probabilistic Framework for Structure- and Ligand-Based Virtual Screening" in the Journal of Medicinal Chemistry. If you haven’t read it yet, I highly recommend it. The paper is a very interesting extension of previous work done by Muchmore et al., also of Abbott Labs. Muchmore’s paper, "Application of Belief Theory to Similarity Data Fusion for Use in Analog Searching and Lead Hopping," presented a system for calculating a quantitative estimate of the likelihood that any two molecules will exhibit similar biological activity based on ligand similarity. Swann’s paper extends this work to include information obtained from structure-based virtual screening using docking.

[business, FastROCS, FRED, GraphSim TK, ROCS]
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Recent Blog Articles

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Searching at the Speed of Byte: Accelerating Similarity and Substructure Searches

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OpenEye Releases Additional Giga-scale Virtual Screening COVID-19 Data for Public Use

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OpenEye deploys the Orion molecular design platform to find COVID-19 therapeutics; makes results freely available

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