Cátia S. D. Lopes, Manuel E. Minas da Piedade and Carlos E. S. Bernardes
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An all-atom force field for MD simulations on organosulfur and organohalogen active pharmaceutical ingredients developed from experimental sublimation enthalpies and single crystal X-ray diffraction data†
An all-atom force field for MD simulations on crystalline Active Pharmaceutical Ingredients (API) containing sulfur and halogens was developed and tested. Validation was performed by comparing the MD results with enthalpies of sublimation experimentally determined by Calvet microcalorimetry and reported single crystal X-ray diffraction data. The test set consisted of sulfanilamide, sulfapyridine, chlorzoxazone, clioquinol, and triclosan. The development was incremental. The OPLS-AA model was taken as the starting point. Then dihedral parameters missing in the OPLS-AA database were obtained from PES data computed at the MP2/aug-cc-pVDZ level of theory. Finally, several methods to determine atomic point charges were tested and a procedure based on the ChelpG methodology, with the inclusion of X-sites mimicking the σ-hole in the case of iodine, was found to provide the best overall accuracy in terms of unit cell dimensions and enthalpy of sublimation predictions.
期刊介绍:
Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions.
The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.