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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Cloud Computing

I am frequently being asked by our users whether OpenEye's licensing model allows them to run OpenEye software in the cloud. As this appears to be a common concern and a potential legal stumbling block for many groups, I want to make sure that our answer is unambiguous and clarified here.

[business, cloud, licensing]
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