Orion® Formulations Suite — Crystal Structure Prediction

Orion® Formulations Suite

The Orion® Formulations Suite* includes robust crystal structure prediction (CSP) workflows and intrinsic solubility calculations that lets researchers uncover promising candidates for formulation early in the drug development process. With the Orion CSP methodology, researchers get:

  • Robust science in easy-to-use workflows:  Walk through a series of steps that use crystal-specific force fields and Quantum Mechanics (QM)-energy models. Eliminate high-energy packings that are more likely to be unstable and identify tightly packed, low-energy crystal structures that are more likely to be stable and suitable candidates for formulation.

  • Fewer late-stage hurdles: Reduce the likelihood of discovering polymorphs during later stages of development, or even after approval, thereby minimizing the chances of unexpected safety concerns, drug recalls, and financial losses. The computational CSP method in Orion let researchers explore the polymorph landscape more thoroughly than possible with time-consuming and costly experimental methods.

  • Fast and accurate results, even with large datasets: Break free from hardware and compute-time constraints by leveraging the massive scaling made possible when running Orion on Amazon Web Services (AWS). From geometry optimization to entropy calculation, Orion employs novel parallelization methods that return results quickly and accurately, even for large datasets. What used to take days now takes only hours.

   How to Speed Up Your Drug Development with Crystal Structure Prediction

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The Crystal Structure Prediction Workflow

The Orion CSP method was validated in collaboration with researchers at GlaxoSmithKline using several drug-like molecules from pharmaceutical settings. It includes four key stages.

CSP Funnel Nov 2021

Orion CSP stages: (1) conformer ensemble generation, (2) random packing and intermolecular energy force field (IEFF) optimization, (3) QM optimization of selected crystal structures using dimer-expansion approach as shown in (3b), and (4) finite temperature corrections.

  1. 3D Conformer Generation from the 2D Structure: Predict the potential 3D conformations of a molecule that might be observed in experimental conditions. This step uses a QM energy model to perform automated torsion scanning of all rotatable bonds and lets users keep only the tautomers that are predicted to be accessible in a defined energy range.

  2. Random Packing and Intermolecular Energy Force field (IEFF) Optimization:  Eliminate high-energy packings that are more likely to be unstable and identify tightly packed, low-energy crystal structures that are more likely to be stable and suitable candidates for formulation. This step leverages OpenEye’s proprietary multipole-based intermolecular energy force field (IEFF) for fast and accurate energy calculations.

  3. QM Optimization using a Dimer-Expansion Approach:  Narrow down the list of crystal candidates by examining differences between long-range, mid-range and short-range interactions and how important they are to a crystal’s stability. This step uses a unique, highly parallelizable dimer-expansion approach that allows for QM optimization of crystal packings in unprecedented time.

  4. Finite Temperature Corrections:  Predict how temperature will impact the stability of promising crystal structures. OpenEye’s dimer-expansion approach makes crystal entropy calculations highly parallelizable which means estimating the stability of crystals at room temperature can be done prospectively on structures.


Results for tight-optimized acetaminophen crystal structures predicted with the Orion CSP workflow. The graph shows the relative QM energy (in kcal/mol) vs crystal RMSD20 (in Å) compared to a polymorph discovered experimentally. Each point is colored by space group. The 3D overlay shows the experimental polymorph (gray) compared to the predicted crystal structure with the lowest RMSD20 (purple).

Additional Resources:

  1. Recorded Presentation on Multi-component CSP: Update on multi-component CSP (Crystal Structure Prediction) at OpenEye, Presented by Caitlin Bannan, PhD, Scientific Software Developer at OpenEye Scientific (July 2021)
  2. Recorded Presentation on Single-component CSP: Ab initio prediction of small-molecule crystal structures: A blind challenge study, Presented by Hari Muddana, Senior Scientific Software Developer at OpenEye Scientific (October 2020)


* Crystal Structure Prediction (CSP) are available as a set of guided workflows available for purchase and use on the Orion cloud-native platform, or as a service performed by OpenEye’s consulting team.

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