Issue 15, 2021

Troubleshooting unstable molecules in chemical space

Abstract

A key challenge in automated chemical compound space explorations is ensuring veracity in minimum energy geometries—to preserve intended bonding connectivities. We discuss an iterative high-throughput workflow for connectivity preserving geometry optimizations exploiting the nearness between quantum mechanical models. The methodology is benchmarked on the QM9 dataset comprising DFT-level properties of 133 885 small molecules, wherein 3054 have questionable geometric stability. Of these, we successfully troubleshoot 2988 molecules while maintaining a bijective mapping with the Lewis formulae. Our workflow, based on DFT and post-DFT methods, identifies 66 molecules as unstable; 52 contain –NNO–, and the rest are strained due to pyramidal sp2 C. In the curated dataset, we inspect molecules with long C–C bonds and identify ultralong candidates (r > 1.70 Å) supported by topological analysis of electron density. The proposed strategy can aid in minimizing unintended structural rearrangements during quantum chemistry big data generation.

Graphical abstract: Troubleshooting unstable molecules in chemical space

Supplementary files

Article information

Article type
Edge Article
Submitted
09 oct. 2020
Accepted
27 feb. 2021
First published
02 mar. 2021
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2021,12, 5566-5573

Troubleshooting unstable molecules in chemical space

S. Senthil, S. Chakraborty and R. Ramakrishnan, Chem. Sci., 2021, 12, 5566 DOI: 10.1039/D0SC05591C

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