SCINE-Software for chemical interaction networks.

The software for chemical interaction networks (SCINE) project aims at pushing the frontier of quantum chemical calculations on molecular structures to a new level. While calculations on individual structures as well as on simple relations between them have become routine in chemistry, new developments have pushed the frontier in the field to high-throughput calculations. Chemical relations may be created by a search for specific molecular properties in a molecular design attempt, or they can be defined by a set of elementary reaction steps that form a chemical reaction network. The software modules of SCINE have been designed to facilitate such studies. The features of the modules are (i) general applicability of the applied methodologies ranging from electronic structure (no restriction to specific elements of the periodic table) to microkinetic modeling (with little restrictions on molecularity), full modularity so that SCINE modules can also be applied as stand-alone programs or be exchanged for external software packages that fulfill a similar purpose (to increase options for computational campaigns and to provide alternatives in case of tasks that are hard or impossible to accomplish with certain programs), (ii) high stability and autonomous operations so that control and steering by an operator are as easy as possible, and (iii) easy embedding into complex heterogeneous environments for molecular structures taken individually or in the context of a reaction network. A graphical user interface unites all modules and ensures interoperability. All components of the software have been made available as open source and free of charge.

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.

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, polynuclear 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 the 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.

Stabilization of activated fragments by shell-wise construction of an embedding environment.

An activated fragment which is structurally unstable when considered isolated can be stabilized through binding to a suitable molecular environment; for instance, to a transition-metal fragment. The metal fragment may be designed in a shell-wise build-up of a surrounding molecular environment. However, adding more and more atoms in a consecutive fashion soon leads to a combinatorial explosion of structures, which is unfeasible to handle without automation. Here, we present a fully automated and parallelized framework that constructs such an embedding environment atom-wise. Molecular realizations of such an environment are constructed based on simple heuristic rules intended to screen a sufficiently large portion of the possible compound space and are then subsequently optimized by electronic structure methods. (Constrained-optimized) structures are then evaluated with respect to a scoring function, for which we choose here the concept of gradient-driven molecule construction. This concept searches for structure modifications that reduce the forces on all atoms. We develop and analyze our approach at the example of CO2 activation by reproducing a known compound and mapping out possible alternative structures and their effect on the stabilization of a (bent) CO2 ligand. For all generated structures, the nuclear gradient on the activated fragment and its coordination energy are evaluated to steer the design process. © 2017 Wiley Periodicals, Inc.