Troubleshooting Unstable Molecules in Chemical Space

摘要: A key challenge in automated chemical compound space explorations is ensuring veracity 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 benchmarked on 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 Lewis formulae. Our workflow, based DFT and post-DFT methods, identifies 66 as unstable; 52 contain –NNO–, rest are strained due to pyramidal sp2 C. In curated dataset, inspect long C–C bonds identify ultralong candidates (r > 1.70 A) supported by topological analysis electron density. proposed strategy can aid minimizing unintended structural rearrangements during chemistry big data generation.