By taking advantage of the crystallographic data of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) complexed with statins, a quantum biochemistry study based on the density functional theory is performed to estimate the interaction energy for each statin when one considers binding pockets of different sizes. Assuming a correlation between statin potency and the strength of the total HMGR-statin binding energy, clinical data as well as IC(50) values of these cholesterol-lowering drugs are successfully explained only after stabilization of the calculated total binding energy for a larger size of the ligand-interacting HGMR region, one with a radius of at least 12.0 Å. Actually, the binding pocket radius suggested by classic works, which was based solely on the interpretation of crystallographic data of the HMGR-statin complex, is smaller than that necessary to achieve total binding energy convergence in our simulations. Atorvastatin and rosuvastatin are shown to be the most strongly bound HMGR inhibitors, while simvastatin and fluvastatin are the weakest ones. A binding site, interaction energy between residues and statin atoms, and residues domain (BIRD) panel is constructed, indicating clear quantum biochemistry-based routes for the development of new statin derivatives.

As the dopamine D3R receptor is a promising target for schizophrenia treatment, an improved understanding of the binding of existing antipsychotics to this receptor is crucial for the development of new potent and more selective therapeutic agents. In this work, we have used X-ray cocrystallization data of the antagonist eticlopride bound to D3R as a template to predict, through docking essays, the placement of the typical antipsychotic drug haloperidol at the D3R receptor binding site. Afterward, classical and quantum mechanics/molecular mechanics (QM/MM) computations were employed to improve the quality of the docking calculations, with the QM part of the simulations being accomplished by using the density functional theory (DFT) formalism. After docking, the calculated QM improved total interaction energy EQMDI = -170.1 kcal/mol was larger (in absolute value) than that obtained with classical molecular mechanics improved (ECLDI = -156.3 kcal/mol) and crude docking (ECRDI = -137.6 kcal/mol) procedures. The QM/MM computations reveal the pivotal role of the Asp110 amino acid residue in the D3R haloperidol binding, followed by Tyr365, Phe345, Ile183, Phe346, Tyr373, and Cys114. Besides, it highlights the relevance of the haloperidol hydroxyl group axial orientation, which interacts with the Tyr365 and Thr369 residues, enhancing its binding to dopamine receptors. Finally, our computations indicate that functional substitutions in the 4-clorophenyl and in the 4-hydroxypiperidin-1-yl fragments (such as C3H and C12H hydrogen replacement by OH or COOH) can lead to haloperidol derivatives with distinct dopamine antagonism profiles. The results of our work are a first step using in silico quantum biochemical design as means to impact the discovery of new medicines to treat schizophrenia.

The binding of the nonsteroidal anti-inflammatory drug ibuprofen (IBU) to human serum albumin (HSA) is investigated using density functional theory (DFT) calculations within a fragmentation strategy.Crystallographic data for the IBU-HSA supramolecular complex shows that the ligand is confined to a large cavity at the subdomain IIIA and at the interface between the subdomains IIA and IIB, whose binding sites are FA3/FA4 and FA6, respectively. The interaction energy between the IBU molecule and each amino acid residue of these HSA binding pockets was calculated using the Molecular Fractionation with Conjugate Caps (MFCC) approach employing a dispersion corrected exchange-correlation functional. Our investigation shows that the total interaction energy of IBU bound to HSA at binding sites of the fatty acids FA3/FA4 (FA6) converges only for a pocket radius of at least 8.5Å, mainly due to the action of residues Arg410, Lys414 and Ser489 (Lys351, Ser480 and Leu481) and residues in nonhydrophobic domains, namely Ile388, Phe395, Phe403, Leu407, Leu430, Val433, and Leu453 (Phe206, Ala210, Ala213, and Leu327), which is unusual. Our simulations are valuable for a better understanding of the binding mechanism of IBU to albumin and can lead to the rational design and the development of novel IBU-derived drugs with improved potency.

The resulting noncovalent bonding of the salicylic acid to ovine COX-1 after bromoaspirin and aspirin acetylation by Ser530 is investigated within the scope of density functional theory considering a 6.5 Å radius binding pocket. We have not only took full advantage of published X-ray structural data for the ovine COX-1 cocrystallized with bromoaspirin, but we also have improved that data through computation, finding good estimates for the hydrogen atom positions at the residues of the binding pocket, and repositioning the Ser530Ac[Br;H] lateral chain and salicylic acid by total energy minimization procedures employing LDA and GGA+D exchange-correlation functionals. Using bromoaspirin as a template, we have simulated the positioning of aspirin in the binding pocket, estimating its interaction energy with each of its neighbor COX-1 residues. We demonstrate that the binding energies of bromoaspirin and aspirin to COX-1 are very close when second-order quantum refinements of the structural data are performed, which points to an explanation on why the IC(50) values for the 126 μM COX-1 activity of both bromoaspirin and aspirin are practically the same. Attracting and repelling residues were identified, being shown that Arg120 is the most effective residue attracting the salicylic acid, followed by Ala527, Leu531, Leu359, and Ser353. On the other hand, Glu524 was found the most effective repulsive residue (strength interaction comparable to Arg120).

We employ quantum biochemistry methods based on the Density Functional Theory (DFT) approach to unveil the detailed binding energy features of willardiines co-crystallized with the AMPA receptor. Our computational results demonstrate that the total binding energies of fluorine-willardiine (FW), hydrogen-willardiine (HW), bromine-willardiine (BrW) and iodine-willardiine (IW) to the iGluR2 ligand-pocket correlate with the agonist binding energies, whose experimental sequential data match our computational counterpart, excluding the HW case. We find that the main contributions to the total willardiine-iGluR2 binding energy are due to the amino acid residues in decreasing order Glu705 > Arg485 > Ser654 > Tyr450 > T655. Furthermore, Met708, which is positioned close to the 5-substituent, attracts HW and FW, but repels BrW and IW. Our results contribute significantly to an improved understanding of the willardiine-iGluR2 binding mechanisms.