Identifying Conformational Isomers of Organic Molecules in Solution via Unsupervised Clustering.

Veselina Marinova,Laurence Dodd,Song-Jun Lee,Geoffrey P F Wood,Ivan Marziano,Matteo Salvalaglio

doi:10.1021/acs.jcim.0c01387

Abstract

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 characterized 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 100 metastable conformational configurations, only 12 are significantly populated across all of 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.

Highlights

Conformational isomerism in organic molecules is an important characteristic that bears significance in a variety of problems
With the use of a data clustering approach, we demonstrate how characteristic conformational configurations can be identified a priori for a molecule in the gas phase to extract quantitative information on conformational states from enhanced sampling molecular dynamics simulations performed in solution under experimentally relevant conditions
The approach is based on the development of a distance metric between configurations that incorporates qualitative information on the energetic cost associated with transitions along each degree of freedom, and the subsequent application of unsupervised clustering

Summary

Introduction

Conformational isomerism in organic molecules is an important characteristic that bears significance in a variety of problems. Binding properties of proteins in protein−ligand complexes are controlled by their conformational configuration by affecting association/dissociation rates and by entropic contributions to the process.[1,2] Understanding the details and mechanisms of conformational changes that proteins undergo is an important part of modern drug discovery methodologies.[3] For small organic molecules, the ability to adopt different conformational configurations can open the possibility for the formation of multiple crystal forms known as conformational polymorphs[4,5] crystal structures of components with the same chemical formula but different molecular shapes. State-to-state transitions of a molecule along its path of incorporation into the crystal from solution may be limited by conformational rearrangements

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