Visualizing chemical space networks with RDKit and NetworkX.

This article demonstrates how to create Chemical Space Networks (CSNs) using a Python RDKit and NetworkX workflow. CSNs are a type of network visualization that depict compounds as nodes connected by edges, defined as a pairwise relationship such as a 2D fingerprint similarity value. A step by step approach is presented for creating two different CSNs in this manuscript, one based on RDKit 2D fingerprint Tanimoto similarity values, and another based on maximum common substructure similarity values. Several different CSN visualization features are included in the tutorial including methods to represent nodes with color based on bioactivity attribute value, edges with different line styles based on similarity value, as well as replacing the circle nodes with 2D structure depictions. Finally, some common network property and analysis calculations are presented including the clustering coefficient, degree assortativity, and modularity. All code is provided in the form of Jupyter Notebooks and is available on GitHub with a permissive BSD-3 open-source license: https://github.com/vfscalfani/CSN_tutorial.

Programmatic conversion of crystal structures into 3D printable files using Jmol.

BACKGROUND: Three-dimensional (3D) printed crystal structures are useful for chemistry teaching and research. Current manual methods of converting crystal structures into 3D printable files are time-consuming and tedious. To overcome this limitation, we developed a programmatic method that allows for facile conversion of thousands of crystal structures directly into 3D printable files. RESULTS: A collection of over 30,000 crystal structures in crystallographic information file (CIF) format from the Crystallography Open Database (COD) were programmatically converted into 3D printable files (VRML format) using Jmol scripting. The resulting data file conversion of the 30,000 CIFs proceeded as expected, however some inconsistencies and unintended results were observed with co-crystallized structures, racemic mixtures, and structures with large counterions that led to 3D printable files not containing the desired chemical structure. Potential solutions to these challenges are considered and discussed. Further, a searchable Jmol 3D Print website was created that allows users to both discover the 3D file dataset created in this work and create custom 3D printable files for any structure in the COD. CONCLUSIONS: Over 30,000 crystal structures were programmatically converted into 3D printable files, allowing users to have quick access to a sizable collection of 3D printable crystal structures. Further, any crystal structure (>350,000) in the COD can now be conveniently converted into 3D printable file formats using the Jmol 3D Print website created in this work. The 3D Print website also allows users to convert their own CIFs into 3D printable files. 3D file data, scripts, and the Jmol 3D Print website are provided openly to the community in an effort to promote discovery and use of 3D printable crystal structures. The 3D file dataset and Jmol 3D Print website will find wide use with researchers and educators seeking to 3D print chemical structures, while the scripts will be useful for programmatically converting large database collections of crystal structures into 3D printable files.

Network Formation in an Orthogonally Self-Assembling System.

Many supramolecular motifs self-assemble into nanorods, forming the basis of the mechanical properties of supramolecular polymers. When integrated as end-caps in a bifunctional telechelic polymer, the motifs can phase segregate into the same or into another nanorod. In the latter case, a functional cross-link is formed by the bridging chain that strengthens the polymer network. This study introduces a supramolecular polymeric system that consists of two different nanorod forming supramolecular motifs. When end-capped to monofunctional polymers, these supramolecular motifs self-assemble in an orthogonal fashion in two separate types of noncross-linked nanorods, resulting in a viscous liquid lacking macroscopic properties. The addition of 15 mol % of an α,ω-telechelic polymer containing both supramolecular motifs, each on one end, transforms this viscous sticky liquid to a solid material with elastomeric properties due to network formation between the two types of nanorods.