Many anticancer drugs are hindered by their bioavailability. To improve a drug’s efficiency, chemists explore novel approaches to engineer solid forms of a drug's active pharmaceutical ingredient (API). Erlotinib, the API of Tarceva, can form a complex with zinc. However, characterizing a specially synthesized crystal is difficult because the resulting nanocrystal powders are often not suitable for single-crystal x-ray analysis and structural information from powder diffraction may not provide sufficient information for patent approval. NMR crystallography, which combines NMR spectroscopy and computational modeling, can be used instead. This study pursued optimizing NMR crystallography parameters to analyze the crystal structure of potential erlotinib-zinc complex. Isolated complexes were constructed and optimized with Gaussian using a 6-31G (d) basis set and PBEPBE functional. Geometry optimizations using lattice including planewave DFT with the RPBE functional and D2* method dispersion corrections with the CASTEP code provided crystalline models for NMR calculations. The impact of refined pseudopotentials and increased basis set cut-off energy on the developed training set and erlotinib molecules was explored, and DFT NMR data was compared to experimental data using root mean square deviation (RMSD) to quantify structural similarities. RMSD findings reveal the impact of each successive optimization on the constructed complexes’ structures. This study’s stepwise approach to NMR crystallography and optimization of computational parameters demonstrate an effective and reliable method for the computational technique. Moreover, these findings support the conclusion that a dichlorodierlotinibzinc(II) complex has been synthesized – possibly one of the first of its kind.

Improving planewave DFT calculations for NMR crystallography of active pharmaceutical ingredients

ACS Spring 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.