Abstract: Herein we will focus on the use of quantum mechanics (QM) in drug design (DD) to solve disparate problems from scoring protein–ligand poses to building QM QSAR models. Through the variational principle of QM we know that we can obtain a more accurate representation of molecular systems than classical models, and while this is not a matter of debate, it still has not been shown that the expense of QM approaches is offset by improved accuracy in DD applications. Objectively validating the improved applicability and performance of QM over classical-based models in DD will be the focus of research in the coming years along with research on the conformational sampling problem as it relates to protein–ligand complexes.

Authors: Kaushik Raha, Martin B. Peters, Bing Wang, Ning Yu, Andrew M. Wollacott, Lance M. Westerhoff, and Kenneth M. Merz Jr.

Reference: Drug Discovery Today. 2007, 12:17-18, 725-731. (see link for full paper).

Abstract: A scheme to decompose the intermolecular interaction energy of a series of complexes at the semiempirical (SE) level has been developed and validated. The comparative binding energy analysis (COMBINE) (Ortiz, A. R.; Pisabarro, M. T.; Gago, F.; Wade, R. C. J. Med. Chem. 1995, 38, 2681-2691) and the semiempirical quantum mechanical method pairwise energy decomposition (PWD) (Raha, K.; van der Vaart, A. J.; Riley, K. E.; Peters, M. B.; Westerhoff, L. M. Kim, H.; Merz, K. M., Jr. J. Am. Chem. Soc. 2005, 127, 6583-6594) were coupled together to form SE-COMBINE. This approach calculates the residue pairwise electrostatic interaction energies, and QSAR models were built with the energies as descriptors using partial least squares (PLS). The application of SE-COMBINE was used as an investigation of the intermolecular interactions between 88 benzamidine inhibitors and trypsin and to test the ability of this new method to predict binding free energies. The predictive capability of SECOMBINE is shown to be comparable to those of other QSAR methods, and using graphical intermolecular interaction maps (IMMs) enhances the interpretability of receptor-based QSARs.

Authors: Martin B. Peters and Kenneth M. Merz, Jr.

Reference: J. Chem. Theory Comput. 2006, 2, 383-399. (see link for full paper).

Abstract: Pairwise decomposition of the interaction energy between molecules is shown to be a powerful tool that can increase our understanding of macromolecular recognition processes. Herein we calculate the pairwise decomposition of the interaction energy between the protein human carbonic anhydrase II (HCAII) and the fluorine-substituted ligand N-(4-sulfamylbenzoyl)benzylamine (SBB) using semiempirical quantum mechanics based methods. We dissect the interaction between the ligand and the protein by dividing the ligand and the protein into subsystems to understand the structure-activity relationships as a result of fluorine substitution. In particular, the off-diagonal elements of the Fock matrix that is composed of the interaction between the ionic core and the valence electrons and the exchange energy between the subsystems or atoms of interest is examined in detail. Our analysis reveals that the fluorine-substituted benzylamine group of SBB does not directly affect the binding energy. Rather, we find that the strength of the interaction between Thr199 of HCAII and the sulfamylbenzoyl group of SBB affects the binding affinity between the protein and the ligand. These observations underline the importance of the sulfonamide group in binding affinity as shown by previous experiments (Maren, T. H.; Wiley: C. E. J. Med. Chem. 1968, 11, 228-232). Moreover, our calculations qualitatively agree with the structural aspects of these proteinligand complexes as determined by X-ray crystallography.

Authors: Kaushik Raha, Arjan J. van der Vaart, Kevin E. Riley, Martin B. Peters, Lance M. Westerhoff, Hwanho Kim, and Kenneth M. Merz, Jr.

Reference: J. Am. Chem. Soc. 2005, 127, 6583-6594. (see link for full paper).