Pitfalls in Computational Modeling of Chemical Reactions and How To Avoid Them

Abstract

Quantum chemical molecular modeling has become a standard tool in organometallic chemistry. In particular, density functional theory calculations are now indispensable for investigating the mechanism of even complex reactions and deliver precise energies of intermediates and transition states. Because software packages have become user-friendly and are widely available, even nonexperts can now produce highquality computer models. In this tutorial, we highlight nontrivial mistakes, misconceptions, and misinterpretations often encountered when producing models of a chemical reaction that can lead to wrong conclusions. The reasons for these errors are conceptually explained in simple terms, and remedies are offered.

The mechanism of monochloramine disproportionation under acidic conditions

“…We found the second step as rate determining with an activation barrier of 14.9 ± 1.0 kcal mol −1 which is fully in accord with the reaction times observed experimentally. 62 The mechanistic picture derived from computations is consistent with the pre-equilibrium kinetic approach, from which the k app fitting curves can be derived. Agreement between kinetic model and experiment can be further improved if both the deprotonation constant of MCA and the rate constant were varied.…”

Readily Available Primary Aminoboranes as Powerful Reagents for Aldimine Synthesis

“…To gain insight into the reaction mechanism, we performed calculations at the M062X 6‐31G** level of theory to compare the reaction of anilino‐pinacolborane (methyl groups on pinacol were replaced by hydrogens) with isobutyraldehyde and benzaldehyde in benzene (Figure ) . We found that the concerted addition of the aminoborane across the carbonyl bond, leading to the hemi‐aminal I , is exergonic with an energy barrier of 28–29 kcal mol −1 ( TS1 ).…”

How Many O‐Donor Groups in Enterobactin Does It Take to Bind a Metal Cation?

“…A similar analysis of the modified enterobactin derivatives with reduced number of oxygen donors leads to similar conclusions regarding the entropy penalties, and shows that triseryl tethering lowers the free energy of binding by around 20 kcal mol −1 . This is easy to understand, given that the contribution of the translational entropy to the free energy at room temperature is approximately 10 kcal mol −1 for any molecule, and the tethering reduces the number of independent entities on the reactant side by two, forming a single chelating ligand by combining three units. Interestingly, the structural distortion energies increase significantly for the ligands with reduced number of oxygen donors, as illustrated in Figure b.…”