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OpenEye Toolkits v2017.Feb Released

OpenEye Toolkits v2017.Feb Released

OpenEye is pleased to announce the release of OpenEye Toolkits v2017.Feb. These libraries include the usual support for C++, Python, C#, and Java.


  • FastROCS TK now allows customization of starting points for shape overlap optimization.
  • Quacpac TK now includes a flexible molecular charging engine.
  • OEMedchem TK now allows MCS similarity scores to be computed for a query molecule compared to a set of indexed target structures.

Alternative Starting Points for Shape Overlap Optimization in FastROCS TK
In this release, the capabilities of FastROCS TK have been extended by the addition of two types of alternative starting points: user-defined starting coordinates accessed via the UserInertialStarts option and heavy atoms starts accessed via the InertialAtHeavyAtoms option. For systems with a large size mismatch between the query molecule and the database molecule, using alternative starting points can lead to more accurate shape scoring as it allows broader sampling of the molecular volume overlap.
In default mode, the shape search in FastROCS starts from four poses of the database molecule aligned around the inertial axes and finds the best possible shape match between the query and the database molecule by optimizing the overlap of their volumes. As shown in the image below, a shape search between, for example, caffeine and a naphthalene derivative using the default inertial starting points results in a poor overlap between the two molecules. However, if the same search is performed with the InertialAtHeavyAtoms option set, the smaller molecule center is translated to each heavy atom of the larger molecule, resulting in a much more favorable overlap.

 Caffeine query and naphthalene derivative
Caffeine query and naphthalene derivative

Best overlap: default (left) vs. InertialAtHeavyAtoms

Best overlap: default (left) vs. InertialAtHeavyAtoms (right)

Overall, the new options provide the ability to fine-tune FastROCS searching based on specific criteria.

Quacpac TK
The 2017.Feb release adds a new molecular charge engine, a container of charging methods used by the new function OEAssignCharges, in Quacpac TK. The charge engine, is a flexible, open-ended options class that defines a charging method. Charge engines are available for all the legacy charging methods.

New Maximum Common Substructure (MCS) Similarity Capability in OEMedchem TK
A new class, OEMCSFragDatabase, has been added to OEMedchem TK. This functionality allows pairwise MCS similarity scores for a query molecule to be compared against a set of indexed target structures. The indexing algorithm uses a fragmentation approach to reduce the computational requirements of traditional NxN structure comparisons. Tanimoto and Tversky similarity scoring functions are provided as well as the ability to implement custom scoring functions.


  • For Python, the new environment variable OE_PIP_ARCH can be set to override the Python package download. OE_ARCH now only applies to application installation. This should mitigate conflicts between Python and application package installation.
  • On Linux, Python single-build distributions are now installed by default when using the meta-installer via pip install openeye-toolkits. If a problem is encountered with the single build packages, users can set the environment variable OE_PIP_ARCH=old before the pip install step.
  • The Java wrappers are now built using Java 1.8 in 1.6 compatibility mode.
  • The 2017.Feb release adds full support for macOS Sierra 10.12.
  • Python 3.4 on Windows is no longer supported.
  • Python 3.6 support will be added in the 2017.Jun release.

Note: OpenEye is planning to phase out Python 2 support by the 2017.Oct release. As this is a substantial change for us and our customers, we are willing to help with code migration. Please contact for more details.

OpenEye Toolkits v2017.Feb are now available for download. Existing licenses will continue to work, but if a new license is required, please contact your account manager or email
See the Release Notes for full and specific details on improvements and fixes. 

About OpenEye Scientific Software
OpenEye Scientific Software Inc. is a privately held company headquartered in Santa Fe, NM, with offices in Boston, Cologne, and Tokyo. It was founded in 1997 to develop large-scale molecular modeling applications and toolkits. Primarily aimed towards drug discovery and design, areas of application include:

The software is designed for scientific rigor, as well as speed, scalability and platform independence. OpenEye makes most of its technology available as toolkits - programming libraries suitable for custom development. OpenEye software typically is distributable across multiple processors and runs on Linux, Windows and Mac OS X.

For additional information
Jeffrey Grandy
VP  Sales