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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.com

Eric J Chan, Struct Chem Crystallogr Commun, 3:2

DOI: 10.21767/2470-9905-C1-002