Benchmarking density functional tight binding models for barrier heights and reaction energetics of organic molecules

Abstract

Density Functional Tight Binding (DFTB) models are two to three orders of magnitude faster than ab initio and Density Functional Theory (DFT) methods and therefore are particularly attractive in applications to large molecules and condensed phase systems. To establish the applicability of DFTB models to general chemical reactions, we conduct benchmark calculations for barrier heights and reaction energetics of organic molecules using existing databases and several new ones compiled in this study. Structures for the transition states and stable species have been fully optimized at the DFTB level, making it possible to characterize the reliability of DFTB models in a more thorough fashion compared to conducting single point energy calculations as done in previous benchmark studies. The encouraging results for the diverse sets of reactions studied here suggest that DFTB models, especially the most recent third-order version (DFTB3/3OB augmented with dispersion correction), in most cases provide satisfactory description of organic chemical reactions with accuracy almost comparable to popular DFT methods with large basis sets, although larger errors are also seen for certain cases. Therefore, DFTB models can be effective for mechanistic analysis (e.g., transition state search) of large (bio)molecules, especially when coupled with single point energy calculations at higher levels of theory.

L718Q mutant EGFR escapes covalent inhibition by stabilizing a non-reactive conformation of the lung cancer drug osimertinib

“…Hybrid QM/MM potentials derived from the SCC-DFTB theory have been widely applied to enzyme-catalyzed reactions and often give reasonable descriptions of reaction geometries and energetics. 46 In the EGFR–osimertinib complexes, side chain atoms of Cys797, Asp800 and the acrylamide portion of the inhibitor were treated with the SCC-DFTB method with dispersion correction. The resulting QM system was composed of 23 atoms, including three link atoms placed along the C–C bond connecting Cβ of the amino acids to their backbone Cα and along the C–N bond connecting the acrylamide nitrogen to the phenyl ring of osimertinib.…”

QM/MM simulations identify the determinants of catalytic activity differences between type II dehydroquinase enzymes

“…S3 † ); such limitations are typical of this efficient but approximate density-functional theory method (with the recent third-order parametrization showing promising improvement). 32 To overcome this issue, several high-level QM methods ( ab initio MP2, and DFT: B3LYP and MPW1K) were employed to correct the free energy profile of this 2 nd step, using energy calculations on SCC-DFTB/MM potential energy profiles. All showed the same trends, so only the ab initio MP2 results are discussed here (Fig.…”

Density-functional tight-binding: basic concepts and applications to molecules and clusters

“…In the early DFTB2 versions, the average performances for a set of small organic molecules [204] were found to be 0.017 Å for bond lengths, 2 degrees for bond angles, 5 kcal/mol for dissociation energies and relative errors in the range 6-7 percent on harmonic vibrational frequencies. Recent studies focused on the barrier heights and energetics of reactions with organic molecules [205,206]. The description of the isomers (epimers) of glucose at the DFTB level has also been compared with DFT and wavefunction results: the agreement between structural parameters was shown to be good except when hydrogen bonds are present [207].…”

“…The accuracy of the DFTB approach to model bare metal systems, inorganic particles [295][296][297] as well as organic molecules [205,209] combined with the transferability of the DFTB potentiel over different chemical systems, makes it a valuable tool to describe functionalized clusters and hybrid organic-inorganic systems. Hence, over the last 15 years, this strength of the DFTB approach has led to a number of studies devoted to functionalized clusters.…”