Combining QM/MM Calculations with Classical Mining Minima to Predict Protein-Ligand Binding Free Energy

We developed an effective binding free energy prediction protocol which incorporates quantum mechanical/molecular mechanical (QM/MM) calculations to substitute the specified atomic charges of force fields with quantum-mechanically recalculated ones at a proposed pose using a mining minima approach with the VeraChem mining minima engine. We tested this protocol using seven well-known targets with 147 different ligands and compared it with classical mining minima and the most popular binding free energy (BFE) methods using different metrics. Our new protocol, dubbed Qcharge-VM2, yielded an overall Pearson correlation of 0.86, which was better than all the methods examined. Qcharge-VM2 performed significantly better than implicit solvent-based methods, such as MM-GBSA and MM-PBSA, but not as good as explicit water-based free energy perturbation methods, such as FEP+, in terms of root-mean-square error, RMSE (1.75 kcal/mol) and mean unsigned error, MUE (1.39 kcal/mol) on a limited set of targets. However, our protocol is substantially less computationally demanding compared with FEP+. The combined accuracy and efficiency of our method can be valuable in drug discovery campaigns.

Sensory Perception of Non-Deuterated and Deuterated Organic Compounds

The chemical background of olfactory perception has been subject of intensive research, but no available model can fully explain the sense of smell. There are also inconsistent results on the role of the isotopology of molecules. In experiments with human subjects it was found that the isotope effect is weak with acetone and D6 -acetone. In contrast, clear differences were observed in the perception of octanoic acid and D15 -octanoic acid. Furthermore, a trained sniffer dog was initially able to distinguish between these isotopologues of octanoic acid. In chromatographic measurements, the respective deuterated molecule showed weaker interaction with a non-polar liquid phase. Quantum chemical calculations give evidence that deuterated octanoic acid binds more strongly to a model receptor than non-deuterated. In contrast, the binding of the non-deuterated molecule is stronger with acetone. The isotope effect is calculated in the framework of statistical mechanics. It results from a complicated interplay between various thermostatistical contributions to the non-covalent free binding energies and it turns out to be very molecule-specific. The vibrational terms including non-classical zero-point energies play about the same role as rotational/translational contributions and are larger than bond length effects for the differential isotope perception of odor for which general rules cannot be derived.

Novel Acetylcholinesterase Inhibitors Based on Uracil Moiety for Possible Treatment of Alzheimer Disease

In this study, novel derivatives based on 6-methyluracil and condensed uracil were synthesized, namely, 2,4-quinazoline-2,4-dione with ω-(ortho-nitrilebenzylethylamino) alkyl chains at the N atoms of the pyrimidine ring. In this series of synthesized compounds, the polymethylene chains were varied from having tetra- to hexamethylene chains, and secondary NH, tertiary ethylamino, and quaternary ammonium groups were introduced into the chains. The molecular modeling of the compounds indicated that they could function as dual binding site acetylcholinesterase inhibitors, binding to both the peripheral anionic site and active site. The data from in vitro experiments show that the most active compounds exhibit affinity toward acetylcholinesterase within a nanomolar range, with selectivity for acetylcholinesterase over butyrylcholinesterase reaching four orders of magnitude. In vivo biological assays demonstrated the potency of these compounds in the treatment of memory impairment using an animal model of Alzheimer disease.

Hierarchical-Clustering, Scaffold-Mining Exercises and Dynamics Simulations for Effectual Inhibitors Against Lipid-A Biosynthesis of Helicobacter pylori

Introduction

Treatment failures of standard regimens and new strains egression are due to the augmented drug resistance conundrum. These confounding factors now became the drug designers spotlight to implement therapeutics against Helicobacter pylori strains and to safeguard infected victims with devoid of adverse drug reactions. Thereby, to navigate the chemical space for medicine, paramount vital drug target opting considerations should be imperative. The study is therefore aimed to develop potent therapeutic variants against an insightful extrapolative, common target LpxC as a follow-up to previous studies.

Methods

We explored the relationships between existing inhibitors and novel leads at the scaffold level in an appropriate conformational plasticity for lead-optimization campaign. Hierarchical-clustering and shape-based screening against an in-house library of > 21 million compounds resulted in panel of 11,000 compounds. Rigid-receptor docking through virtual screening cascade, quantum-polarized-ligand, induced-fit dockings, post-docking processes and system stability assessments were performed.

Results

After docking experiments, an enrichment performance unveiled seven ranked actives better binding efficiencies with Zinc-binding potency than substrate and in-actives (decoy-set) with ROC (1.0) and area under accumulation curve (0.90) metrics. Physics-based membrane permeability accompanied ADME/T predictions and long-range dynamic simulations of 250 ns chemical time have depicted good passive diffusion with no toxicity of leads and sustained consistency of lead1-LpxC in the physiological milieu respectively.

Conclusions

In the study, as these static outcomes obtained from this approach competed with the substrate and existing ligands in binding affinity estimations as well as positively correlated from different aspects of predictions, which could facilitate promiscuous new chemical entities against H. pylori.

The evaluation of QM/MM-driven molecular docking combined with MM/GBSA calculations as a halogen-bond scoring strategy

The combination of quantum mechanics/molecular mechanics-driven (QM/MM) molecular docking with binding free-energy calculations was successfully used to reproduce the X-ray geometries of protein–ligand complexes with halogen bonding. The procedure involves quantum-polarized ligand docking (QPLD) to obtain the QM-derived ligand atomic charges in the protein environment at the B3PW91/cc-pVTZ level and the MM/GBSA (generalized-Born/surface area) algorithm to calculate the binding free energies of resultant complexes. The performance was validated using a set of 106 X-ray complexes and compared with the Glide and AutoDock VinaXB scoring functions in terms of RMSD and the reconstruction of halogen-bond geometry (distance and σ-hole angle). The results revealed that docking and scoring using the QPLD–GBSA procedure outperformed the remaining scoring functions in the majority of instances. Additionally, a comparison of the orientation of the top ranked binding poses calculated using the fixed atomic charges of ligands obtained from force-field parameterization and by QM calculations in the protein environment provides strong evidence that the use of QM-derived charges is significant.

Activity prediction of substrates in NADH-dependent carbonyl reductase by docking requires catalytic constraints and charge parameterization of catalytic zinc environment

Molecular docking of substrates is more challenging compared to inhibitors as the reaction mechanism has to be considered. This becomes more pronounced for zinc-dependent enzymes since the coordination state of the catalytic zinc ion is of greater importance. In order to develop a predictive substrate docking protocol, we have performed molecular docking studies of diketone substrates using the catalytic state of carbonyl reductase 2 from Candida parapsilosis (CPCR2). Different docking protocols using two docking methods (AutoDock Vina and AutoDock4.2) with two different sets of atomic charges (AM1-BCC and HF-RESP) for catalytic zinc environment and substrates as well as two sets of vdW parameters for zinc ion were examined. We have selected the catalytic binding pose of each substrate by applying mechanism based distance criteria. To compare the performance of the docking protocols, the correlation plots for the binding energies of these catalytic poses were obtained against experimental Vmax values of the 11 diketone substrates for CPCR2. The best correlation of 0.73 was achieved with AutoDock4.2 while treating catalytic zinc ion in optimized non-bonded (NBopt) state with +1.01 charge on the zinc ion, compared to 0.36 in non-bonded (+2.00 charge on the zinc ion) state. These results indicate the importance of catalytic constraints and charge parameterization of catalytic zinc environment for the prediction of substrate activity in zinc-dependent enzymes by molecular docking. The developed predictive docking protocol described here is in principle generally applicable for the efficient in silico substrate spectra characterization of zinc-dependent ADH.