Universal QM features of methyltransferases

Methyltransferases (MTases) are among the most ubiquitous regulatory enzymes in the cell, catalyzing gene signaling, protein repair, neurotransmitter regulation, and natural product biosynthesis. Despite being extensively investigated, competing enzymatic enhancement mechanisms have been suggested, ranging from structural methyl group C–H···X hydrogen bonds (HBs) to electrostatic- and charge-transfer-driven stabilization of the transition state (TS). No broad conclusion can be reached because each study is typically carried out on a single MTase and associated substrate.

WIRES Outlook on the future of ML

As machine learning has matured, it has opened a new frontier in theoretical and computational chemistry by offering the promise of simultaneous paradigm shifts in accuracy and efficiency. Nowhere is this advance more needed, but also more challenging to achieve, than in the discovery of open shell transition metal complexes where localized d or f electrons exhibit variable bonding that is challenging to capture even with the most computationally demanding methods.

Protein-substrate interactions influence catalysis

Biosynthetic enzyme complexes selectively catalyze challenging chemical transformations, including alkane functionalization (e.g., halogenation of threonine, Thr, by the non-heme iron halogenase SyrB2). However, the role of complex formation in enabling reactivity and guiding selectivity is poorly understood, owing to the challenges associated with obtaining detailed structural information of the dynamically associating protein complexes.

Non-empirical corrections to DFT

Density functional theory (DFT) is widely applied to both molecules and materials, but well known energetic delocalization and static correlation errors in practical exchange-correlation approximations limit quantitative accuracy. Common methods that correct energetic delocalization error, such as the Hubbard U correction in DFT+U or Hartree-Fock exchange in global hybrids, do so at the cost of worsening static correlation error.

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About Us

The Kulik group focuses on the development and application of new electronic structure methods and atomistic simulations tools in the broad area of catalysis.

Our Interests

We are interested in transition metal chemistry, with applications from biological systems (i.e. enzymes) to nonbiological applications in surface science and molecular catalysis.

Our Focus

A key focus of our group is to understand mechanistic features of complex catalysts and to facilitate and develop tools for computationally driven design.

Contact Us

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