Publication:Crystal Growth Design
Authors:Mingjun Yang, Eric Dybeck, Guangxu Sun, Chunwang Peng, Brian Samas, Virginia M. Burger, Qun Zeng, Yingdi Jin, Michael A. Bellucci, Yang Liu, Peiyu Zhang, Jian Ma, Yide Alan Jiang, Bruno C. Hancock, Shuhao Wen*, and Geoffrey P. F. Wood
Date:Sept. 2, 2020

Prediction of the Relative Free Energies of Drug Polymorphs above Zero Kelvin

Cryst. Growth Des. 2020, 20, 8, 5211–5224

Crystal structure prediction (CSP) calculations can reduce risk and improve efficiency during drug development. Traditionally, CSP calculations use lattice energies computed through density functional theory. While this approach is often successful in predicting the low energy structures, it neglects the crucial role of thermal effects on polymorph stabilities. In the present study, we develop a robust and efficient protocol for predicting the relative stability of polymorphs at different temperatures. The protocol is executed on a highly parallel cloud computing infrastructure to produce results at time scales useful for drug development timelines. We demonstrate this protocol on molecule XXIII from the sixth crystal structure prediction blind test. Our results predict that Form D is the most stable experimentally observed polymorph at ambient temperature and Form C is the most stable at low temperature consistent with experiments also conducted in the present study.

Publication:Crystal Growth Design
Authors:Dr. Yuriy Abramov, Dr. Peiyu Zhang et al.
Date:Jan. 30, 2020

Computational Insights into Kinetic Hindrance Affecting Crystallization of Stable Forms of Active Pharmaceutical Ingredients

Cryst. Growth Des. 2020, 20, 3, 1512-1525

A computational investigation of the potential source of kinetic hindrance for the late appearance of pharmaceutically relevant stable forms of ritonavir, rotigotine, ranitidine hydrochloride, and pharmaceutical compound A was performed along the crystallization coordinates of the relative rates of conformational interconversion, crystal nucleation, and growth.

Publication:molecular pharmaceutics
Authors:Dr. Yuriy Abramov, Dr. Guangxu Sun et al.
Date:Jan. 13, 2020

Guiding Lead Optimization for Solubility Improvement with Physics-Based Modeling

Mol. Pharmaceutics 2020, 17, 2, 666-673

Although there are a number of computational approaches available for the aqueous solubility prediction, a majority of those models rely on the existence of a training set of thermodynamic solubility measurements or/and fail to accurately account for the lattice packing contribution to the solubility. The main focus of this study is the validation of the application of a physics-based aqueous solubility approach…

Publication:Journal of Computational Chemistry
Authors:Dr. Shuai Liu, Dr. Mingjun Yang et al.
Date:Nov. 13, 2019

Optimal Designs for Pairwise Calculation: an Application to Free Energy Perturbation in Minimizing Prediction Variability

J. Comput. Chem. 2019, 9999, 1–11

Pairwise‐based methods such as the free energy perturbation (FEP) method have been widely deployed to compute the binding free energy differences between two similar host–guest complexes. The calculated pairwise free energy difference is either directly adopted or transformed to absolute…

Publication:Crystal Growth Design
Authors:Dr. Yuriy Abramov, Dr. Guangxu Sun
Date:Oct. 17, 2019

Solid-form Transition Temperature Prediction from a Virtual Polymorph Screening:A Reality Check

Cryst. Growth Des. 2019, 19, 7132−7137

The focus of this study is an estimation of uncertainty of solid-form transition temperature (Ttr) prediction based on modern virtual polymorph screening calculations. That was done through error propagation, utilizing estimated uncertainties of the relative free energy predictions at 0 K as well as of finite-temperature contribution to the polymorphic relative free energy…

Publication:The Journal of Chemical Physics
Authors:Dr. M. A. Bellucci et al.
Date:March 5, 2019

Solubility of Paracetamol in Ethanol by Molecular Dynamics Using the Extended Einstein Crystal Method and Experiments

J. Chem. Phys. 150, 094107 (2019)

Li and co-workers [Li et al., J. Chem. Phys. 146, 214110 (2017)] have recently proposed a methodology to compute the solubility of molecular compounds from first principles, using molecular dynamics simulations. We revise and further explore their methodology that was originally applied to nap…