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OpenEye Toolkits v2017.Jun released

OpenEye Toolkits v2017.Jun released

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


  • Preliminary API gives users early access to new functionality and technologies.
  • OEShape TK adds Hermite expansion functionality.
  • OEDepict TK and Grapheme TK showcase interactive SVG images.
  • OEGraphSim TK adds fast fingerprint similarity search capabilities.

Preliminary API
The 2017.Jun release introduces the concept of a Preliminary API. This is an API that is still under development and whose improvement is driven primarily by user feedback. Its primary purpose is to provide users with early access to new functionality and technology. A preliminary API will transition to a stable API after 2 release cycles. Preliminary APIs may only be available in C++ and Python.

Hermite Representation in OEShape TK
The 2017.Jun release introduces the OEHermite class, which allows a molecule to be expanded into a Hermite representation. One area of application is the representation of a protein shape. The advantages of representing proteins by Hermites include:
  • smooth representations that capture any level of detail, from the atomistic (many coefficients, see the picture on the right) to the very coarse (few coefficients, as in the middle picture);
  • the ability to store these representations in a compact manner;
  • the ability to transform these representations easily; and
  • very fast overlap calculations between proteins.

Below are examples of low- and high-resolution Hermite representation images of dihydrofolate reductase (DHFR):


OpenEye will explore the potential of Hermite representations; we invite users to do likewise with this exciting new addition to OpenEye toolkits.

Interactive SVG Images
Interactive SVG images are introduced in OEDepict TK and Grapheme TK via a Preliminary API. Low-level functionality that enables users to group together graphical elements in an SVG image is available. In addition, high-level API points allow users to generate self-contained SVG images that show or hide different elements of the image based on mouse events.


Example of interactive SVG image (PDB: 4HWR) showing protein residue–ligand atom interaction.

Fast Fingerprint Similarity Search
High performance similarity search is now available in GraphSim TK through the fast fingerprint similarity search algorithm. Fast fingerprint search is 10 times faster than the current fingerprint search and allows large databases to be searched quickly.

Fast fingerprint search is available in two modes: in-memory and memory-mapped modes. In-memory mode involves pre-loading all fingerprints into memory and performing the search in-memory. This is the fastest search method and is only limited by available memory. Memory-mapped mode does not involve any load time penalty or memory limitation but the search can be slower. A comparison of the performance of the different search methods using 128M 4096-bit long tree fingerprints benchmarked on a m4.10xlarge AWS instance is shown in the figure below.


Performance of fast fingerprint search

  • The 2017.Jun release adds full support for Python 3.6.
  • The 2017.Jun release is the last release to support 32-bit Java.

  • The 2017.Jun release is the last release to support RHEL5. As of March 31, 2017, RHEL5 has reached end-of-production support.
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.Jun 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