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Volume 3, Issue 2
ISSN: 2470-9905
Crystallography 2017
October 16-17, 2017
2
nd
International Conference on
October 16-17, 2017 | Chicago, USA
Applied Crystallography
On the application of molecular simulation tools in studies of organic molecular crystals (i.e., modeling
disorder and other crystalline properties)
Eric J Chan
Bristol Myers Squibb, USA
A
nalysis and prediction of physical properties of crystalline materials is of crucial importance. For example, a pharmaceutical
crystal form must satisfy a target profile with respect to process-ability as well as bioavailability. In the material development
arena, undesirable physical phenomena offer non-trivial challenges. Such phenomena include polymorphism, disorder, solvation/
de-solvation, disproportionation and variation in the crystal particle size shape; because these phenomena impact the physical
structure and related properties of a material, challenges also exist analytical and characterization perspective. Nowadays varieties
of atomistic simulation techniques are useful to support analysis, provide further chemical/physical insight and for risk assessment/
predictive capabilities. The once active laboratory chemical crystallographer may be forced to seek refuge
in silico
. Such computational
activities are facilitated by a plethora of commercial and community software tools and codes. However, in some cases workflows
and tools are not as streamlined and options are limited, the former experimentalist then takes the role of a computer scientist. We
discuss a selection of case studies where such former mentioned novel molecular simulation hackwork is applied to small molecule
crystallography, the majority being pharmaceutically relevant. Example workflows include atomistic simulationmethods (MC or MD)
useful for interpreting supplementary scattering features like diffuse and satellite intensities from single crystal X-ray diffraction. One
study demonstrates insight into de-solvation processes. For understanding the interplay between different solvents within the crystal
structure, a Grand Canonical Monte Carlo (GCMC) model was developed combining crystal structure, molecular mechanics models
and SSNMR data. This was useful to estimate site occupation parameters for solvent bound to a crystal. We argue the supplementary
knowledge of molecular level interactions provides a simple means for prediction of the corresponding thermodynamic properties
such as the solvent activities and temperatures required to remove or replace unwanted lattice solvent. Another example includes
s
ilico
screening for solvent effect on crystal morphology.
Biography
Eric J Chan has completed his graduate studies in Organic Chemistry/Biochemistry, PhD in coordination chemistry of metal-organic complexes and chemical crystallography
and Post-doctoral study in X-ray single crystal diffuse scattering interpretations, molecular models, and Monte Carlo methods for molecular simulation, solid state organic
chemistry and analysis of organic solids. He has expertise in crystallography, solid-state or materials chemistry and molecular simulations. He has interest in computational
physics approaches used in chemistry. Graduate in organic chemistry/biochemistry, PhD: coordination chemistry of metal-organic complexes and chemical crystallography.
Eric.Chan@bms.comEric J Chan, Struct Chem Crystallogr Commun, 3:2
DOI: 10.21767/2470-9905-C1-002