Assessment of semiempirical enthalpy of formation in solution as an effective energy function to discriminate native‐like structures in protein decoy sets

Abstract

In this work, we tested the PM6, PM6-DH1, PM6-D3, and PM7 enthalpies of formation in aqueous solution as scoring functions across 33 decoy sets to discriminate native structures or good models in a decoy set. In each set these semiempirical quantum chemistry methods were compared according to enthalpic and geometric criteria. Enthalpically, we compared the methods according to how much lower was the enthalpy of each native, when compared with the mean enthalpy of its set. Geometrically, we compared the methods according to the fraction of native contacts (Q), which is a measure of geometric closeness between an arbitrary structure and the native. For each set and method, the Q of the best decoy was compared with the Q 0 , which is the Q of the decoy closest to the native in the set. It was shown that the PM7 method is able to assign larger energy differences between the native structure and the decoys in a set, arguably because of a better description of dispersion interactions, however PM6-DH1 was slightly better than the rest at selecting geometrically good models in the absence of a native structure in the set.

Semiempirical Quantum-Chemical Methods with Orthogonalization and Dispersion Corrections

“…in calculations of very large systems, e.g. of fullerenes, − nanotubes, , long polyynes, proteins, ,− and others, ,, in real-time quantum chemistry studies, − and in simulations requiring a very large number of electronic structure calculations. The latter applications include high-throughput screening in drug ,− and materials , design, high-throughput p K a calculations, , ground-state molecular dynamics (MD) simulations, , excited-state nonadiabatic MD simulations, quantum mechanics/molecular mechanics (QM/MM) MD and Monte Carlo studies, ,− , and mass spectra simulations. − …”

Target–ligand binding affinity from single point enthalpy calculation and elemental composition

“…This combination of the semi-empirical QM approaches with COSMO implicit solvent model for the calculation of DH b has been a choice in various studies with PM3, 28,30 PM6 48 and PM7 33,49 parametrizations among which PM7 may be considered as the most robust one. 50 In a comparative study, PM7 outperformed PM6, PM6-DH+, and PM6-D3 methods in differentiating between decoy versus native docked poses based on single-point complex formation enthalpies, 51 and similar results were obtained with PM7/COSMO. 52 While the above studies (Table 1) hint that application of the COSMO solvent model is useful in QM-based DH b calculations, there are many situations in drug design 25 where the use of explicit water molecules would be advantageous.…”

The Advances and Limitations of the Determination and Applications of Water Structure in Molecular Engineering

“…There is also a universal solvation model based on solute electron density (SMD, [133]), which is usually implemented for more computationally demanding levels of QM. At the semi-empirical level, the combination of PM6s [134][135][136][137] and PM7 [137][138][139] parametrizations, combined with the implicit model of COSMO, is a popular choice for estimating the binding affinities of ligands to targets.…”