Molassembler: Molecular graph construction, modification and conformer generation for inorganic and organic molecules

We present the graph-based molecule software Molassembler for building organic and inorganic molecules. Molassembler provides algorithms for the construction of molecules built from any set of elements from the periodic table. In particular, poly-nuclear transition metal complexes and clusters can be considered. Structural information is encoded as a graph. Stereocenter configurations are interpretable from Cartesian coordinates into an abstract index of permutation for an extensible set of polyhedral shapes. Substituents are distinguished through a ranking algorithm. Graph and stereocenter representations are freely modifiable and chiral state is propagated where possible through incurred ranking changes. Conformers are generated with full stereoisomer control by four spatial dimension Distance Geometry with a refinement error function including dihedral terms. Molecules are comparable by an extended graph isomorphism and their representation is canonicalizeable. Molassembler is written in C++ and provides Python bindings.Comment: 81 pages, 26 figures, 3 table

Formal Representation and Exploration of Inorganic Molecules with Graph-Theoretical Means

We present the graph-based software Molassembler for organic and inorganic molecules. Molassembler provides algorithms for the construction of molecules built from any set of elements from the periodic table. In particular, poly-nuclear transition metal complexes and clusters can be considered. We motivate a molecular model in which structural information is encoded as a graph, and stereocenter configurations are represented as an abstract index of permutation for an arbitrary and freely extensible set of polyhedral shapes. A variety of shape classification methods are presented, devised and evaluated, yielding a reliable approach. The arrangements represented by abstract stereoconfiguration indices are filtered by three-dimensional feasibility, leading to practical stereodescriptors. An algorithm is presented to interpret stereocenter configurations from Cartesian coordinates. An extension of organic substituent ranking rules with the derived stereodescriptors expands its applicability to inorganic chemical space. The modification of the joint model composed of a graph and its stereocenter representations is discussed and an algorithm presented to prevent avoidable losses of chiral state through incurred shape, stereodescriptor, and ranking changes. Algorithms to compare molecules and canonicalize their representation are introduced. We show an approach to generate conformers with full stereoisomer control by four spatial dimension Distance Geometry. After discussing the model’s weaknesses, we demonstrate its strengths at some sample complexes. Finally, Molassembler is applied in the context of automated chemical reaction network exploration and the molecular design of a CO2-fixating complex

The (not so) simple prediction of enantioselectivity – a pipeline for high-fidelity computations

The computation of reaction selectivity represents an appealing complementary route to experimental studies and a powerful means to refine catalyst design strategies. Accurately establishing the selectivity of reactions facilitated by molecular catalysts, however, remains a challenging task for computational chemistry. The small free energy differences that lead to large variations in the enantiomeric ratio (er) represent particularly tricky quantities to predict with sufficient accuracy to be helpful for prioritizing experiments. Further complicating this problem is the fact that standard approaches typically consider only one or a handful of conformers identified through human intuition as pars pro toto of the conformational space. Obviously, this assumption can potentially lead to dramatic failures should key energetic low-lying structures be missed. Here, we introduce a multi-level computational pipeline leveraging the graph-based Molassembler library to construct an ensemble of molecular catalysts. The manipulation and interpretation of molecules as graphs provides a powerful and direct route to tailored functionalization and conformer generation that facilitates high-throughput mechanistic investigations of chemical reactions. The capabilities of this approach are validated by examining a Rh(iii) catalyzed asymmetric C-H activation reaction and assessing the limitations associated with the underlying ligand design model. Specifically, the presence of remarkably flexible chiral Cp ligands, which induce the experimentally observed high level of selectivity, present a rich configurational landscape where multiple unexpected conformations contribute to the reported enantiomeric ratios (er). Using Molassembler, we show that considering about 20 transition state conformations per catalysts, which are generated with little human intervention and are not tied to "back-of-the-envelope" models, accurately reproduces experimental er values with limited computational expense.ISSN:2041-6520ISSN:2041-653