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Modeling the Thermodynamics of Conformational Isomerism in Solution via Unsupervised Clustering: The Case of Sildenafil

preprint
submitted on 17.11.2020, 16:03 and posted on 18.11.2020, 12:24 by Veselina Marinova, Laurence Dodd, Song-Jun Lee, Geoffrey P. F. Wood, Ivan Marziano, Matteo Salvalaglio

We present a systematic approach for the identification of statistically relevant conformational macrostates of organic molecules from molecular dynamics trajectories. The approach applies to molecules characterised by an arbitrary number of torsional degrees of freedom and enables the transferability of the macrostates definition across different environments. We formulate a dissimilarity measure between molecular configurations that incorporates information on the characteristic energetic cost associated with transitions along all relevant torsional degrees of freedom. Such metric is employed to perform unsupervised clustering of molecular configurations based on the fast search and find of density peaks algorithm. We apply this method to investigate the equilibrium conformational ensemble of Sildenafil, a conformationally complex pharmaceutical compound, in different environments including the crystal bulk, the gas phase and three different solvents (acetonitrile, 1-butanol, and toluene). We demonstrate that, while Sildenafil can adopt more than one hundred metastable conformational configurations, only 12 are significantly populated across all the environments investigated. Despite the complexity of the conformational space, we find that the most abundant conformers in solution are the closest to the conformers found in the most common Sildenafil crystal phase.

History

Email Address of Submitting Author

m.salvalaglio@ucl.ac.uk

Institution

University College London

Country

United Kingdom

ORCID For Submitting Author

https://orcid.org/0000-0003-3371-2090

Declaration of Conflict of Interest

no conflict of interest

Version Notes

vesrion 1.0

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