Crystal Structure Prediction
The crystal form of a drug plays an important role in its solid-state formulation. Finding novel and more stable crystal forms of a drug molecule, after the drug has been approved, can pose significant risks for pharmaceutical companies.
As all stable crystal forms of a drug cannot be obtained readily through experiment, computational predictions can assist with identifying the potential risk of polymorph, as well as finding crystal forms that are better suited for formulation with regards to physico-chemical properties.
Crystal structure prediction (CSP) of drug-like molecules poses a variety of challenges, including unknown tautomer state, novel chemical motifs, high degree of flexibility, intricate hydrogen bonding networks, and others.
- Perform CSP on drug-like molecules within a few days – instead of months – using the Orion® cloud-native platform
- Apply various force fields and Quantum Mechanics (QM) energy models for a broader range of results
- Assess the polymorph risk of a drug early in the development process to save time and effort down the pipeline
To meet the challenges of CSP, OpenEye offers a custom CSP solution that is built on our cloud-native platform Orion. At each stage of the study, we have developed novel methods for parallelizing the problem, enabling us to exploit the massive scaling afforded by Amazon Web Services. In addition to ranking crystal structures by energy, we can calculate the entropic contribution to crystal stability at the QM level of theory, and thereby rank the crystal structures at finite temperature. Furthermore, we can apply a variety of force field and QM energy models within the study for varying levels of accuracy and scope.
Traditional approaches to CSP of a drug molecule can take weeks to months. A major bottleneck in these approaches is the use of periodic QM lattice calculations (e.g. plane-wave density-functional theory), which are not very parallelizable and scale poorly.
OpenEye’s novel approach for optimizing crystal structures using QM energy models is highly parallelizable and scalable to hundreds of thousands of processors. Utilizing this approach, we are able to perform CSP on drug-like molecules within the wall clock time of a few days, enabling the exploration of a variety of ideas for optimizing drug molecule formulation within a reasonable amount of time. Assessing the polymorph risk of a drug early in the drug development process can save time and effort down the pipeline.
In an effort to evaluate our methodology, we have performed several successful blind challenges in collaboration with GSK on drug-like molecules in various stages of clinical trials.
To find out how a collaboration with OpenEye could help with your CSP and drug formulation needs and to explore completing a CSP project with OpenEye, contact us at email@example.com