DENOPTIM: Software for Computational de Novo Design of Organic and Inorganic Molecules

A general-purpose software package, termed DE Novo OPTimization of In/organic Molecules (DENOPTIM), for de novo design and virtual screening of functional molecules is described. Molecules of any element and kind, including metastable species and transition states, are handled as chemical objects that go beyond valence-rules representations. Synthetic accessibility of the generated molecules is ensured via detailed control of the kinds of bonds that are allowed to form in the automated molecular building process. DENOPTIM contains a combinatorial explorer for screening and a genetic algorithm for global optimization of user-defined properties. Estimates of these properties may be obtained to form the fitness function (figure of merit or scoring function) from external molecular modeling programs via shell scripts. Examples of a range of different fitness functions and DENOPTIM applications, including an easy-to-do test case, are described. DENOPTIM is available as Open Source from https://github.com/denoptim-project/DENOPTIM.acceptedVersio

Computational Investigations of Organometallic Polymerization Catalyst Reaction Mechanisms

Computational chemistry is a proven tool for creating a better understanding of known chemistry, discovering new mechanisms and chemical reactivity, and systematically improving catalyst and reaction design. The insight that can be gained from computational studies, however, is limited by the accuracy of the models used and often requires an established working knowledge of the chemical system of interest. In addition to this, computational chemistry must be guided and grounded by experiment in order to synergistically approach the goal of achieving a fuller understanding of reaction pathways. The studies herein demonstrate this synergy between computational and experimental chemistry with an emphasis on building realistic computational models for reaction path exploration. Chapter 1 provides a brief overview of computational chemistry fundamentals that are needed to understand reaction landscapes. This introduction describes the reaction path and transition state finding methods that were used in subsequent studies found in this work. These methods and concepts are then demonstrated via studies on metal-catalyzed polymerization reactions that are led by experiment in Chapter 2. This chapter highlights the computational investigations of these systems that were used to support and extend the chemical insights toward catalyst reactivity. Chapter 3 describes the computationally-led elucidation of the transmetalation mechanism of thiophene-based conductive polymer synthesis. This work presents a full mechanistic viewpoint of the transmetalation reaction and establishes the chemical details that are necessary for accurately modeling this reaction including realistic models of reagents, consideration of catalyst spin state, and changing steric interactions as polymerization proceeds. The insights gained from this study should aid catalyst design for polymerization reactions and related cross coupling reactions. Chapter 4 describes conformational effects resulting from the inherent flexibility of organometallic catalysts. This chapter was inspired by the importance of biochemical protein-substrate conformational effects that prompted the investigation of similar effects in the context of organometallic reactions. This study surveys the conformer ensembles of several bisphosphine nickel catalysts and their reductive elimination pathways. The conformational effects shown in this work result in large reductive elimination ground and transition state effects. Additionally, the conformer analysis revealed that reductive elimination barrier height and the degree of distortion of the reactant geometries contained a high-correlation structure-reactivity relationship. This work should inspire more thorough evaluation of conformer effects for transition-metal-catalyzed reactions. Significant efforts are still needed to develop and test chemically insightful and accurate computational methods. This work outlines applications of these modern computational tools toward building better models and a developing a deeper understanding of organometallic chemistry and polymer chemistry.PHDChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149899/1/andvitek_1.pd

Automated Building of Organometallic Complexes from 3D Fragments

A method for the automated construction of three-dimensional (3D) molecular models of organometallic species in design studies is described. Molecular structure fragments derived from crystallographic structures and accurate molecular-level calculations are used as 3D building blocks in the construction of multiple molecular models of analogous compounds. The method allows for precise control of stereochemistry and geometrical features that may otherwise be very challenging, or even impossible, to achieve with commonly available generators of 3D chemical structures. The new method was tested in the construction of three sets of active or metastable organometallic species of catalytic reactions in the homogeneous phase. The performance of the method was compared with those of commonly available methods for automated generation of 3D models, demonstrating higher accuracy of the prepared 3D models in general, and, in particular, a much wider range with respect to the kind of chemical structures that can be built automatically, with capabilities far beyond standard organic and main-group chemistry