Advances in Automated Transition State Theory Calculations: Improvements on the AutoTST Framework

<div>Kinetic modeling of combustion chemistry has made substantial progress in recent years with the development of increasingly detailed models. However, many of the chemical kinetic parameters utilized in detailed models are estimated, often inaccurately. To help replace rate estimates with more accurate calculations, we have developed AutoTST, an automated Transition State Theory rate calculator. This work describes improvements to AutoTST, including: a systematic conformer search to find an ensemble of low energy conformers, vibrational analysis to validate transition state geometries, more accurate symmetry number calculations, and a hindered rotor treatment when deriving kinetics. These improvements resulted in location of transition state geometry for 93% of cases and generation of kinetic parameters for 74% of cases. Newly calculated parameters agree well with benchmark calculations and perform well when used to replace estimated parameters in a detailed kinetic model of methanol combustion.</div>

Advances in Automated Transition State Theory Calculations: Improvements on the AutoTST Framework

<div>Kinetic modeling of combustion chemistry has made substantial progress in recent years with the development of increasingly detailed models. However, many of the chemical kinetic parameters utilized in detailed models are estimated, often inaccurately. To help replace rate estimates with more accurate calculations, we have developed AutoTST, an automated Transition State Theory rate calculator. This work describes improvements to AutoTST, including: a systematic conformer search to find an ensemble of low energy conformers, vibrational analysis to validate transition state geometries, more accurate symmetry number calculations, and a hindered rotor treatment when deriving kinetics. These improvements resulted in location of transition state geometry for 93% of cases and generation of kinetic parameters for 74% of cases. Newly calculated parameters agree well with benchmark calculations and perform well when used to replace estimated parameters in a detailed kinetic model of methanol combustion.</div>

Advances in Automated Transition State Theory Calculations: Improvements on the AutoTST Framework

<div>Kinetic modeling of combustion chemistry has made substantial progress in recent years with the development of increasingly detailed models. However, many of the chemical kinetic parameters utilized in detailed models are estimated, often inaccurately. To help replace rate estimates with more accurate calculations, we have developed AutoTST, an automated Transition State Theory rate calculator. This work describes improvements to AutoTST, including: a systematic conformer search to find an ensemble of low energy conformers, vibrational analysis to validate transition state geometries, more accurate symmetry number calculations, and a hindered rotor treatment when deriving kinetics. These improvements resulted in location of transition state geometry for 93% of cases and generation of kinetic parameters for 74% of cases. Newly calculated parameters agree well with benchmark calculations and perform well when used to replace estimated parameters in a detailed kinetic model of methanol combustion.</div>

High-Affinity Alkynyl Bisubstrate Inhibitors of Nicotinamide N-Methyltransferase (NNMT)

<div> <div> <div> <div> <p>In this work, structure-based rational design led to the development of potent and selective alkynyl bisubstrate inhibitors of NNMT. The reported nicotinamide-SAM conjugate (named <b>NS1</b>) features an alkyne as a key design element that closely mimics the linear, 180° transition state geometry found in the NNMT-catalyzed SAM → NAM (nicotinamide) methyl transfer reaction. NS1 was synthesized as a single enantiomer and diastereomer in 14 steps and found to be a high-affinity, subnanomolar NNMT inhibitor. An X-ray co-crystal structure and structure-activity relationship (SAR) study revealed the unique ability of an alkynyl linker to span the methyl transfer tunnel of NNMT with ideal shape complementarity. The compounds reported in this work represent the most potent and selective NNMT inhibitors reported to date. The rational design principle described herein could potentially be extended to other methyltransferase enzymes. </p> </div> </div> </div> </div>

High-Affinity Alkynyl Bisubstrate Inhibitors of Nicotinamide N-Methyltransferase (NNMT)

<div> <div> <div> <div> <p>In this work, structure-based rational design led to the development of potent and selective alkynyl bisubstrate inhibitors of NNMT. The reported nicotinamide-SAM conjugate (named <b>NS1</b>) features an alkyne as a key design element that closely mimics the linear, 180° transition state geometry found in the NNMT-catalyzed SAM → NAM (nicotinamide) methyl transfer reaction. NS1 was synthesized as a single enantiomer and diastereomer in 14 steps and found to be a high-affinity, subnanomolar NNMT inhibitor. An X-ray co-crystal structure and structure-activity relationship (SAR) study revealed the unique ability of an alkynyl linker to span the methyl transfer tunnel of NNMT with ideal shape complementarity. The compounds reported in this work represent the most potent and selective NNMT inhibitors reported to date. The rational design principle described herein could potentially be extended to other methyltransferase enzymes. </p> </div> </div> </div> </div>

Uncovering the Binding Mode of γ-Secretase Inhibitors

Knowledge of how transition state inhibitors bind to γ-secretase is of major importance for the design of new Alzheimer’s disease therapies. Based on the known structure of γ-secretase in complex with a fragment of the amyloid precursor protein we have generated a structural model of γ-secretase in complex with the effective L-685,458 transition state inhibitor. The predicted binding mode is in excellent agreement with experimental data, mimicking all enzyme-substrate interactions at the active site and forming the relevant transition state geometry with the active site aspartate residues. In addition, we found that the stability of the complex is very likely also sensitive to the pH value. Comparative simulations on the binding of L-685,458 and the epimer L682,679 allowed us to explain the strongly reduced affinity of the epimer for γ-secretase. The structural model could form a valuable basis for the design of new or modified γ-secretase inhibitors.

Transition state geometry of driven chemical reactions on time-dependent double-well potentials

The minimum contour in the forward Lagrangian descriptor overlaps the invariant manifold (in green) dividing reactant and product regions.