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Gigadocking™ in Orion™ Molecular Design Platform Rapidly Identifies Novel Chemical Entities for GPCR Targets

OpenEye Scientific Helps Beacon Discovery Increase Speed and Improve Activity in Virtual Screening

[News, Release]
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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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OpenEye Releases Additional Giga-scale Virtual Screening COVID-19 Data for Public Use

ACE2 with the top four scoring hits from our docking study. The four compounds were selected from the Enamine REAL library of approximately 1.4 billion synthesizable compounds. The top 10,000 hits from this docking study are freely available for download.

Summary: In an effort to help in the search to find potential therapeutics for COVID-19, OpenEye has completed multiple large-scale computational studies. The first dataset was released on April 27 (https://www.eyesopen.com/blog/openeye-deploys-the-orion-molecular-design-platform-to-find-covid-19-therapeutics).  Here we publish a second such set of results and make them freely available to advance research toward a therapy.

[News, large scale virtual screening, COVID-19, Giga docking, ACE2]
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OpenEye deploys the Orion molecular design platform to find COVID-19 therapeutics; makes results freely available

 

SARS-CoV-2 Mpro protease with the top three scoring hits from our docking study. The three compounds were selected from the Enamine REAL library of approximately 1.4 billion synthesizable compounds. The top 10,000 hits from this docking study are freely available for download.

Summary: In an effort to quickly find potential therapeutics for COVID-19, OpenEye has completed multiple large-scale computational studies. Here we publish the first such set of results and make them freely available to advance research toward a therapy.

[News, large scale virtual screening, COVID-19, Giga docking]
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Relative Binding Free Energy with Non-Equilibrium Switching in Orion

By Gaetano Calabro PhD, OpenEye & Christopher Bayly, PhD OpenEye

A variety of free energy simulation methods, such as  FEP, TI, and λ dynamics, make use of atomistic MD or Monte Carlo simulations to determine the relative binding free energy (RBFE) between two ligands along an alchemical path. Non-Equilibrium switching (NES) is a relatively new method to estimate binding affinities based on the calculation of thermodynamic work along fast, non-equilibrium alchemical paths. In Orion, an implementation of De Groot’s RBFE-NES method has been tested on few targets.

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Easier is Better

There was a time when an essential part of most chemistry experiments involved glass blowing, but no longer. Stockrooms full of standardized flasks, condensers, connectors, and tubing have allowed chemists to focus a little more on chemistry and a little less on plumbing. While it's wonderful when scientific breakthroughs allow us to take great strides, we also move forward, inch by inch, when we remove small burdens or simplify some routine task.

[OEChem TK, science]
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Using Apache Maven with OpenEye

Maven is a tool that manages Java projects. In addition to other features, it enforces requirements, manages dependencies, and defines artifact creation. This guide explains how to use Maven with OpenEye jars. To get familiar with Maven, please read the 5 Minute Guide and the Getting Started Guide. The rest of this article assumes that Java and Maven are installed and working. It will be helpful to follow the sample HelloMaven project, available at
https://github.com/oess/HelloMaven, while reading this guide.

[Apache, development, Maven, OpenEye]
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Grapheme: Advancing Protein-Ligand Visualization

How can we more quickly and efficiently extract the rich complexity of information and knowledge embodied in the three-dimensional structure of a protein-ligand complex? In the February 2015 toolkit release OpenEye extends the ability to represent complex, three-dimensional protein-ligand structures in two dimensions with the deployment of Ligand Depiction in Proteins, LDiP 1.0. This will save medicinal chemists and protein biophysicists countless hours staring at lists of complexes in 3D molecule viewers, instead enabling them to focus quickly on key compounds, key interactions or key properties. Example output from LDiP is shown in Figure 1. The emphasis is on clarity and immediacy of representation, without sacrifice of important information.

[application science, Grapheme TK, OEDocking, Python, ROCS]
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Our documentation has moved

We have moved our documentation landing page to a more memorable address http://docs.eyesopen.com. It features a fresh landing page and should deliver our content in double time. Your current bookmarks will still work but we recommend using http://docs.eyesopen.com as your number one resource for our applications and toolkits.

[development, Python, support]
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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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Gigadocking™ in Orion™ Molecular Design Platform Rapidly Identifies Novel Chemical Entities for GPCR Targets

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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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