Extension of an Atom-Atom Dispersion Function to Halogen Bonds and Its Use for Rational Design of Drugs and Biocatalysts

A dispersion function Das in the form of a damped atom-atom asymptotic expansion fitted to ab initio dispersion energies from symmetry-adapted perturbation theory was improved and extended to systems containing heavier halogen atoms. To illustrate its performance, the revised Das function was implemented in the multipole first-order electrostatic and second-order dispersion (MED) scoring model. The extension has allowed applications to a much larger set of biocomplexes than it was possible with the original Das. A reasonable correlation between MED and experimentally determined inhibitory activities was achieved in a number of test cases, including structures featuring nonphysically shortened intermonomer distances, which constitute a particular challenge for binding strength predictions. Since the MED model is also computationally efficient, it can be used for reliable and rapid assessment of the ligand affinity or multidimensional scanning of amino acid side-chain conformations in the process of rational design of novel drugs or biocatalysts.

Synthesis, structural characterization, docking simulation and in vitro antiproliferative activity of the new gold(III) complex with 2-pyridineethanol

Gold(III) complex containing 2-pyridineethanol has been synthesized and characterized structurally by single crystal X-ray diffraction, vibrational spectroscopy, ¹H NMR spectroscopy, electrochemical study, and DFT calculations. The Au(III) ion is four coordinated with one N-donor ligand (L) and three Cl anions. The Okuniewski's (τ'₄₌0.018) has been used to estimate the angular distortion from ideal square planar geometry. The vibrational spectroscopy studies, in the solid state and DMSO solution and cyclic voltammetry, have been performed to determine its stability and redox activity, respectively. A complete assignment of the IR and Raman spectra has been made based on the calculated potential energy distribution (PED). The theoretical calculations have been made for two functionals and several basis sets. The compound has been evaluated for its antiproliferative properties in a human lung adenocarcinoma cell line (A549), mouse colon carcinoma (CT26), human breast adenocarcinoma (MCF-7), human prostate carcinoma derived from the metastatic site in the brain (DU-145), and PANC-1 human pancreas/duct carcinoma cell line and non-tumorigenic cell lines: HaCat (human keratinocyte), and HEK293T (human embryonic kidney). Au(III) complex cytotoxicity is significantly against A549 and MCF-7 cells as in the reference drug: cisplatin. Studies of the interactions of Au(III) complex with DNA, HSA (human serum albumin) have been performed. The results from modeling docking simulations indicate that the title complex exerts anticancer effects in vitro based on different mechanisms of action to compare with cisplatin.

Revisiting the halogen bonding between phosphodiesterase type 5 and its inhibitors

Halogenated ligands are nowadays commonly designed in order to increase their potency against protein targets. Although novel computational methods of evaluating the affinity of such halogenated inhibitors have emerged, they still lack the sufficient accuracy, which is especially noticeable in the case of empirical scoring functions, being the method of choice in the drug design process. Here, we evaluated a series of halogenated inhibitors of phosphodiesterase type 5 with ab initio methods, revealing the physical nature of ligand binding and determining the components of interaction energy that are essential for proper inhibitor ranking. In particular, a nonempirical scoring model combining long-range contributions to the interaction energy provided a significant correlation with experimental binding potency, outperforming a number of commonly used empirical scoring functions. Considering the low computational cost associated with remarkable predictive abilities of the aforementioned model, it could be used for rapid assessment of the ligand affinity in the process of rational design of novel halogenated compounds.

Theoretical Model of EphA2-Ephrin A1 Inhibition

This work aims at the theoretical description of EphA2-ephrin A1 inhibition by small molecules. Recently proposed ab initio-based scoring models, comprising long-range components of interaction energy, is tested on lithocholic acid class inhibitors of this protein–protein interaction (PPI) against common empirical descriptors. We show that, although limited to compounds with similar solvation energy, the ab initio model is able to rank the set of selected inhibitors more effectively than empirical scoring functions, aiding the design of novel compounds.

Exploiting the S4-S5 Specificity of Human Neutrophil Proteinase 3 to Improve the Potency of Peptidyl Di(chlorophenyl)-phosphonate Ester Inhibitors: A Kinetic and Molecular Modeling Analysis

The neutrophilic serine protease proteinase 3 (PR3) is involved in inflammation and immune response and thus appears as a therapeutic target for a variety of infectious and inflammatory diseases. Here we combined kinetic and molecular docking studies to increase the potency of peptidyl-diphenyl phosphonate PR3 inhibitors. Occupancy of the S1 subsite of PR3 by a nVal residue and of the S4-S5 subsites by a biotinylated Val residue as obtained in biotin-VYDnV^P(O-C₆H₄-4-Cl)₂ enhanced the second-order inhibition constant k_obs/[I] toward PR3 by more than 10 times ( k_obs/[I] = 73000 ± 5000 M^-1 s^-1) as compared to the best phosphonate PR3 inhibitor previously reported. This inhibitor shows no significant inhibitory activity toward human neutrophil elastase and resists proteolytic degradation in sputa from cystic fibrosis patients. It also inhibits macaque PR3 but not the PR3 from rodents and can thus be used for in vivo assays in a primate model of inflammation.

Theoretical models of inhibitory activity for inhibitors of protein-protein interactions: targeting menin-mixed lineage leukemia with small molecules

A computationally affordable, non-empirical model based on electrostatic multipole and dispersion terms successfully predicts the binding affinity of inhibitors of menin–MLL protein–protein interactions.

Development and binding affinity predictions of inhibitors targeting protein–protein interactions (PPI) still represent a major challenge in drug discovery efforts. This work reports application of a predictive non-empirical model of inhibitory activity for PPI inhibitors, exemplified here for small molecules targeting the menin–mixed lineage leukemia (MLL) interaction. Systematic ab initio analysis of menin–inhibitor complexes was performed, revealing the physical nature of these interactions. Notably, the non-empirical protein–ligand interaction energy comprising electrostatic multipole and approximate dispersion terms (E(10)El,MTP + E_Das) produced a remarkable correlation with experimentally measured inhibitory activities and enabled accurate activity prediction for new menin–MLL inhibitors. Importantly, this relatively simple and computationally affordable non-empirical interaction energy model outperformed binding affinity predictions derived from commonly used empirical scoring functions. This study demonstrates high relevance of the non-empirical model we developed for binding affinity prediction of inhibitors targeting protein–protein interactions that are difficult to predict using empirical scoring functions.

Application of a simple quantum chemical approach to ligand fragment scoring for Trypanosoma brucei pteridine reductase 1 inhibition

There is a need for improved and generally applicable scoring functions for fragment-based approaches to ligand design. Here, we evaluate the performance of a computationally efficient model for inhibitory activity estimation, which is composed only of multipole electrostatic energy and dispersion energy terms that approximate long-range ab initio quantum mechanical interaction energies. We find that computed energies correlate well with inhibitory activity for a compound series with varying substituents targeting two subpockets of the binding site of Trypanosoma brucei pteridine reductase 1. For one subpocket, we find that the model is more predictive for inhibitory activity than the ab initio interaction energy calculated at the MP2 level. Furthermore, the model is found to outperform a commonly used empirical scoring method. Finally, we show that the results for the two subpockets can be combined, which suggests that this simple nonempirical scoring function could be applied in fragment–based drug design.

Rational Design of Orthogonal Multipolar Interactions with Fluorine in Protein-Ligand Complexes

Multipolar interactions involving fluorine and the protein backbone have been frequently observed in protein–ligand complexes. Such fluorine–backbone interactions may substantially contribute to the high affinity of small molecule inhibitors. Here we found that introduction of trifluoromethyl groups into two different sites in the thienopyrimidine class of menin–MLL inhibitors considerably improved their inhibitory activity. In both cases, trifluoromethyl groups are engaged in short interactions with the backbone of menin. In order to understand the effect of fluorine, we synthesized a series of analogues by systematically changing the number of fluorine atoms, and we determined high-resolution crystal structures of the complexes with menin. We found that introduction of fluorine at favorable geometry for interactions with backbone carbonyls may improve the activity of menin–MLL inhibitors as much as 5- to 10-fold. In order to facilitate the design of multipolar fluorine–backbone interactions in protein–ligand complexes, we developed a computational algorithm named FMAP, which calculates fluorophilic sites in proximity to the protein backbone. We demonstrated that FMAP could be used to rationalize improvement in the activity of known protein inhibitors upon introduction of fluorine. Furthermore, FMAP may also represent a valuable tool for designing new fluorine substitutions and support ligand optimization in drug discovery projects. Analysis of the menin–MLL inhibitor complexes revealed that the backbone in secondary structures is particularly accessible to the interactions with fluorine. Considering that secondary structure elements are frequently exposed at protein interfaces, we postulate that multipolar fluorine–backbone interactions may represent a particularly attractive approach to improve inhibitors of protein–protein interactions.

Physical Nature of Fatty Acid Amide Hydrolase Interactions with Its Inhibitors: Testing a Simple Nonempirical Scoring Model

Fatty acid amide hydrolase (FAAH) is an enzyme responsible for the deactivating hydrolysis of fatty acid ethanolamide neuromodulators. FAAH inhibitors have gained considerable interest due to their possible application in the treatment of anxiety, inflammation, and pain. In the context of inhibitor design, the availability of reliable computational tools for predicting binding affinity is still a challenging task, and it is now well understood that empirical scoring functions have several limitations that in principle could be overcome by quantum mechanics. Herein, systematic ab initio analyses of FAAH interactions with a series of inhibitors belonging to the class of the N-alkylcarbamic acid aryl esters have been performed. In contrast to our earlier studies of other classes of enzyme-inhibitor complexes, reasonable correlation with experimental results required us to consider correlation effects along with electrostatic term. Therefore, the simplest comprehensive nonempirical model allowing for qualitative predictions of binding affinities for FAAH ligands consists of electrostatic multipole and second-order dispersion terms. Such a model has been validated against the relative stabilities of the benchmark S66 set of biomolecular complexes. As it does not involve parameters fitted to experimentally derived data, this model offers a unique opportunity for generally applicable inhibitor design and virtual screening.

Non-empirical study of the phosphorylation reaction catalyzed by 4-methyl-5-β-hydroxyethylthiazole kinase: relevance of the theory of intermolecular interactions

The subject of this study was an analysis of the role of active site residues in the phosphoryl transfer reaction catalyzed by 4-methyl-5-beta-hydroxyethylthiazole kinase (ThiK). The ThiK-catalyzed reaction is of special interest due to the lack of a highly conserved aspartate residue serving as a catalytic base. ONIOM(B3LYP:PM3) models of stationary points along the reaction pathway consisted of reactants, two magnesium ions and several highly conserved ThiK active site residues. The results indicate that an S(N)2-like mechanism of ThiK, with gamma-phosphate acting as an alcohol-activating base is reasonable. Geometries of substrates, transition state and products were utilized in the non-empirical analysis of the physical nature of catalytic interactions taking place in the ThiK active site. The role of particular residues was investigated in terms of their ability to preferentially stabilize the transition state relative to substrates (differential transition state stabilization, DTSS) or products (differential product stabilization, DPS). It seems that Mg2, Glu126 and Cys198 play a major catalytic role, whereas Mg1 and the same Cys198 are responsible for product release. It is remarkable that no dominant role of an electrostatic term in the interactions involved in catalytic activity is observed for product release. Determination of catalytic fields expressing differential electrostatic potential of the transition state with respect to substrates revealed the optimal electrostatic features of an ideal catalyst for the studied reaction. The predicted catalytic environment is in agreement with experimental data showing increased catalytic activity of ThiK upon mutation of Cys198 to aspartate.

The molecular basis of urokinase inhibition: from the nonempirical analysis of intermolecular interactions to the prediction of binding affinity

Urokinase-type plasminogen activator (uPA) is a trypsin-like serine protease that plays a crucial role in angiogenesis process. In addition to its physiological role in healthy organisms, angiogenesis is extremely important in cancer growth and metastasis, resulting in numerous attempts to understand its control and to develop new approaches to anticancer therapy. The alpha-aminoalkylphosphonate diphenyl esters are well known as highly efficient serine protease inhibitors. However, their mode of binding has not been verified experimentally in details. For a group of average and potent phosphonic inhibitors of urokinase, flexible docking calculations were performed to gain an insight into the active site interactions responsible for observed enzyme inhibition. The docking results are consistent with the previously suggested mode of inhibitors binding. Subsequently, rigorous ab initio study of binding energy was carried out, followed by its decomposition according to the variation-perturbation procedure to reveal stabilization energy constituents with clear physical meaning. Availability of the experimental inhibitory activities and comparison with theoretical binding energy allows for the validation of theoretical models of inhibition, as well as estimation of the possible potential for binding affinity prediction. Since the docking results accompanied by molecular mechanics optimization suggested that several crucial active site contacts were too short, the optimal distances corresponding to the minimum ab initio interaction energy were also evaluated. Despite the deficiencies of force field-optimized enzyme-inhibitor structures, satisfactory agreement with experimental inhibitory activity was obtained for the electrostatic interaction energy, suggesting its possible application in the binding affinity prediction.