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Insights into the Stability of Engineered Mini-Proteins from Their Dynamic Electronic Properties
An understanding of protein stability requires capturing dynamic rearrangements and coupled properties over long lengthscales. …
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Insights into the Stability of Engineered Mini-Proteins from Their Dynamic Electronic Properties
Non-Native Anionic Ligand Binding and Reactivity in Engineered Variants of the Fe(II)- and α-Ketoglutarate-Dependent Oxygenase, SadA
Mononuclear non-heme Fe(II)- and alpha-ketoglutarate dependent oxygenases (FeDOs) catalyze site-selective C-H hydroxylation. Variants …
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Non-Native Anionic Ligand Binding and Reactivity in Engineered Variants of the Fe(II)- and α-Ketoglutarate-Dependent Oxygenase, SadA
Endohedrally Functionalized Metal–Organic Cage-Cross-Linked Polymer Gels as Modular Heterogeneous Catalysts
The immobilization of homogeneous catalysts onto supports to improve recyclability while maintaining catalytic efficiency is often a …
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Endohedrally Functionalized Metal–Organic Cage-Cross-Linked Polymer Gels as Modular Heterogeneous Catalysts
Using Computational Chemistry to Reveal Nature's Blueprints for Single-Site Catalysis of C–H Activation
The challenge of activating inert C–H bonds motivates a study of catalysts that draws from what can be accomplished by natural enzymes …
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Using Computational Chemistry to Reveal Nature's Blueprints for Single-Site Catalysis of C–H Activation
Mechanistic Studies of a Skatole-Forming Glycyl Radical Enzyme Suggest Reaction Initiation via Hydrogen Atom Transfer
Gut microbial decarboxylation of amino acid-derived arylacetates is a chemically challenging enzymatic transformation which generates …
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Mechanistic Studies of a Skatole-Forming Glycyl Radical Enzyme Suggest Reaction Initiation via Hydrogen Atom Transfer
Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character Across Known Transition Metal Complex Ligands
Accurate virtual high-throughput screening (VHTS) of transition metal complexes (TMCs) remains challenging due to the possibility of …
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Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character Across Known Transition Metal Complex Ligands
Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis
Virtual high-throughput screening (VHTS) and machine learning (ML) have greatly accelerated the design of single-site transition-metal …
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Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis
Roadmap on Machine Learning in Electronic Structure
In recent years, we have been witnessing a paradigm shift in computational materials science. In fact, traditional methods, mostly …
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Roadmap on Machine Learning in Electronic Structure
Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: The Case of Formate Dehydrogenase
The Mo/W-containing metalloenzyme formate dehydrogenase (FDH) is an efficient and selective natural catalyst that reversibly converts …
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Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: The Case of Formate Dehydrogenase
What's Left for a Computational Chemist To Do in the Age of Machine Learning?
Machine learning (ML) has become a central focus of the computational chemistry community. I will first discuss my personal history in …
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What's Left for a Computational Chemist To Do in the Age of Machine Learning?