Cyclooxygenase (COX) inhibitors: a comparative QSAR study

Synthesis, molecular dynamics simulation, and evaluation of biological activity of novel flurbiprofen and ibuprofen-like compounds

The frequent use of anti-inflammatory drugs and the side effects of existing drugs keep the need for new compounds constant. For this purpose, flurbiprofen and ibuprofen-like compounds, which are frequently used anti-inflammatory compounds in this study, were synthesized and their structures were elucidated. Like ibuprofen and flurbiprofen, the compounds contain a residue of phenylacetic acid. On the other hand, it contains a secondary amine residue. Thus, it is planned to reduce the acidity, which is the biggest side effect of NSAI drugs, even a little bit. The estimated ADME parameters of the compounds were evaluated. Apart from internal use, local use of anti-inflammatory compounds is also very important. For this reason, the skin permeability values of the compounds were also calculated. And it has been found to be compatible with reference drugs. The COX enzyme inhibitory effects of the obtained compounds were tested by in vitro experiments. Compound 2a showed significant activity against COX-1 enzyme with an IC50 = 0.123 + 0.005 μM. The interaction of the compound with the enzyme active site was clarified by molecular dynamics studies.

SERUM DISPOSITION OF A SINGLE DOSE OF ORALLY ADMINISTERED FIROCOXIB IN AFRICAN ELEPHANTS (LOXODONTA AFRICANA)

The time course of serum firocoxib concentrations was described after administration of two single oral doses (0.01 and 0.1 mg/kg) of commercially available firocoxib tablet (n = 4) and paste (n = 2) formulations to six healthy adult female African (Loxodonta africana) elephants. Firocoxib was quantitated by high-performance liquid chromatography. Firocoxib serum concentrations were below detectable levels after administration of 0.01 mg/kg of both formulations. A dose of 0.1 mg/kg (n = 4) of the tablet formulation had the following mean ± SD of pharmacokinetic parameters: area under the curve (AUC) 1,588 ± 362 h × ng/ml, maximum plasma concentration (C_max) 31 ± 6.6 ng/ml at 6.4 ± 1.8 h, and disappearance half-life (T1/2) 66 ± 59 h, Elephant compliance to oral administration of the paste formulation was challenging, with only two elephants accepting administration of the paste at 0.1 mg/kg. Pharmacokinetic parameters determined included AUC of 814 h × ng/ml, C_max of 44 ng/ml at Tmax of 7.0 h, and T1/2 of 36.4 h. Based on mean AUC, the relative bioavailability of paste compared to tablet formulations was 50%. Limitations of this study were the small number of participants and elephant compliance with the paste formulation. This study supports an oral dose of 0.1 mg/kg every 24 h. Multidose and IV trials are indicated to confirm firocoxib dosing requirements for African elephants.

Stability Analysis of the Asiatic Acid-COX-2 Complex Using 100 ns Molecular Dynamic Simulations and Its Selectivity against COX-2 as a Potential Anti-Inflammatory Candidate

Asiatic acid, a triterpenoid compound, has been shown to have anti-inflammatory activity through the inhibition of the formation of cyclooxygenase-2 (COX-2) in vitro and in vivo. This study was conducted to determine the binding stability and the inhibitory potential of asiatic acid as an anti-inflammatory candidate. The study involved in vitro testing utilizing a colorimetric kit as well as in silico testing for the pharmacophore modeling and molecular dynamic (MD) simulation of asiatic acid against COX-2 (PDB ID: 3NT1). The MD simulations showed a stable binding of asiatic acid to COX-2 and an RMSD range of 1-1.5 Å with fluctuations at the residues of Phe41, Leu42, Ile45, Arg44, Asp367, Val550, Glu366, His246, and Gly227. The total binding energy of the asiatic acid-COX-2 complex is -7.371 kcal/mol. The anti-inflammatory activity of the asiatic acid inhibition of COX-2 was detected at IC₅₀ values of 120.17 µM. Based on pharmacophore modeling, we discovered that carboxylate and hydroxyl are the two main functional groups that act as hydrogen bond donors and acceptors interacting with the COX-2 enzyme. From the results, it is evident that asiatic acid is a potential anti-inflammatory candidate with high inhibitory activity in relation to the COX-2 enzyme.

One-pot synthesis of 4-substituted 2-fluoroalkyloxazoles from NH-1,2,3-triazoles and fluoroalkylated acid anhydrides

An efficient one-pot method for the synthesis of 2-fluoroalkyloxazoles from 4-substituted NH-1,2,3-triazoles, fluorinated anhydrides and triethylamine was developed.

Profiling the interaction of 1-phenylbenzimidazoles to cyclooxygenases

In the design of 1-phenylbenzimidazoles as model cyclooxygenase (COX) inhibitors, docking to a series of crystallographic COX structures was performed to evaluate their potential for high-affinity binding and to reproduce the interaction profile of well-known COX inhibitors. The effect of ligand-specific induced fit on the calculations was also studied. To quantitatively compare the pattern of interactions of model compounds to the profile of several cocrystallized COX inhibitors, a geometric parameter, denominated ligand-receptor contact distance (LRCD), was developed. The interaction profile of several model complexes showed similarity to the profile of COX complexes with inhibitors such as iodosuprofen, iodoindomethacin, diclofenac, and flurbiprofen. Shaping of high-affinity binding sites upon ligand-specific induced fit mostly determined both the affinity and the binding mode of the ligands in the docking calculations. The results suggest potential of 1-phenylbenzimidazole derivatives as COX inhibitors on the basis of their predicted affinity and interaction profile to COX enzymes. The analyses also provided insights into the role of induced fit in COX enzymes. While inhibitors produce different local structural changes at the COX ligand binding site, induced fit allows inhibitors in diverse chemical classes to share characteristic interaction patterns that ensure key contacts to be achieved. Different interaction patterns may also be associated with different inhibitory mechanisms.

Nimesulide analogues: From anti-inflammatory to antitumor agents

Nimesulide is a nonsteroidal anti-inflammatory drug possessing analgesic and antipyretic properties. This drug is considered a selective cyclooxygenase-2 (COX-2) inhibitor and, more recently, has been associated to antitumor activity. Thus, numerous works have been developed to modify the nimesulide skeleton aiming to develop new and more potent and selective COX-2 inhibitors as well as potential anticancer agents. This review intends to provide an overview on analogues of nimesulide, including the general synthetic approaches used for their preparation and structural diversification and their main anti-inflammatory and/or antitumor properties.

SAR and QSAR models of cyclooxygenase-1 (COX-1) inhibitors

Cyclooxygenase-1 (COX-1) is one isoform of COX, and it is a main target of nonsteroidal anti-inflammatory drugs (NSAIDs). It is important to develop efficient and selective COX-1 inhibitors. In this work, 12 classification models for 1530 cyclooxygenase-1 (COX-1) inhibitors were built by support vector machine (SVM), decision tree (DT) and random forest (RF) methods. The best classification model (model 1A) was built by SVM with MACCS fingerprints. The classification accuracies for the training and test sets were 99.67% and 97.39%, respectively. The Matthews correlation coefficient (MCC) of the test set was 0.94. We also divided the 1530 COX-1 inhibitors into nine subsets according to their different scaffolds using Kohonen's self-organizing map (SOM). In addition, six quantitative structure-activity relationship (QSAR) models for 181 COX-1 inhibitors whose IC₅₀ were measured by enzyme immunoassay were built by multiple linear regression (MLR) and SVM. The best QSAR model (model 5A) was built by SVM with CORINA Symphony descriptors. The correlation coefficients of the training and test sets are 0.93 and 0.84, respectively. The models built in this study can be obtained from the authors.

Metal-free Chlorothiolation of Alkenes using HCl and Sulfoxides

We report a novel method for the chlorothiolation of alkenes using HCl and sulfoxides to achieve the 1,2-difunctionalization of unactivated alkenes. The combination of our new HCl reagent (HCl/DMPU) with sulfoxides forms a unique chlorothiolation system. Both terminal and internal alkenes are suitable substrates. This method works at gram scale and is applicable in further synthetic elaborations.

Novel 4-methylsulfonylphenyl derivatives as NSAIDS with preferential COX-2 inhibition

Aim: There has been an enormous commercial development following the introduction of selective COX-2 inhibitors. Efforts are continuously done to discover efficient and safe COX-2 inhibitors. Results: A series of 4-methylsulfonylphenyl derivatives was designed, synthesized and screened for preferential inhibition of COX-2 over COX-1 isoforms and in vivo anti-inflammatory activity using the rat paw edema method. The most active ones were investigated via ulcerogenic liability and molecular docking. Physicochemical parameters were calculated for all the newly synthesized compounds. Conclusion: The new compounds showed clear preferential COX-2 over COX-1 inhibition. Selective indices for compounds 4, 6b and 6e were 124, 131 and 119, respectively. Compound 4 reached 71% in vivo anti-inflammatory inhibition. The compounds obeyed ‘Lipinski’s rule of five’.

Low potency toxins reveal dense interaction networks in metabolism

BACKGROUND

The chemicals of metabolism are constructed of a small set of atoms and bonds. This may be because chemical structures outside the chemical space in which life operates are incompatible with biochemistry, or because mechanisms to make or utilize such excluded structures has not evolved. In this paper I address the extent to which biochemistry is restricted to a small fraction of the chemical space of possible chemicals, a restricted subset that I call Biochemical Space. I explore evidence that this restriction is at least in part due to selection again specific structures, and suggest a mechanism by which this occurs.

RESULTS

Chemicals that contain structures that our outside Biochemical Space (UnBiological groups) are more likely to be toxic to a wide range of organisms, even though they have no specifically toxic groups and no obvious mechanism of toxicity. This correlation of UnBiological with toxicity is stronger for low potency (millimolar) toxins. I relate this to the observation that most chemicals interact with many biological structures at low millimolar toxicity. I hypothesise that life has to select its components not only to have a specific set of functions but also to avoid interactions with all the other components of life that might degrade their function.

CONCLUSIONS

The chemistry of life has to form a dense, self-consistent network of chemical structures, and cannot easily be arbitrarily extended. The toxicity of arbitrary chemicals is a reflection of the disruption to that network occasioned by trying to insert a chemical into it without also selecting all the other components to tolerate that chemical. This suggests new ways to test for the toxicity of chemicals, and that engineering organisms to make high concentrations of materials such as chemical precursors or fuels may require more substantial engineering than just of the synthetic pathways involved.

Analogue-based design, synthesis and molecular docking analysis of 2,3-diaryl quinazolinones as non-ulcerogenic anti-inflammatory agents

In our effort to identify potent gastric sparing anti-inflammatory agents, a series of methyl sulfanyl/methyl sulfonyl substituted 2,3-diaryl quinazolinones were designed by analogue-based design strategy and synthesized for biological evaluation. Subsequently, the compounds were evaluated for both cyclooxygenase inhibitions by ovine COX assay and carrageenan-induced rat paw edema assay. All the methyl sulfonyl substituted quinazolinones were exhibited promising anti-inflammatory activity. In particular, 6-bromo-3-(4-methanesulfonyl-phenyl)-2-phenyl-3H-quinazolin-4-one, 7-chloro-3-(4-methanesulfonyl-phenyl)-2-phenyl-3H-quinazolin-4-one, 3-(4-methanesulfonyl-phenyl)-2-(4-methoxy-phenyl)-3H-quinazolin-4-one and 6-bromo-3-(4-methanesulfonyl-phenyl)-2-(4-methoxy-phenyl)-3H-quinazolin-4-one emerged as the most active compounds in the series. The results of ulcerogenic activity assay suggest that these compounds are gastric safe compared to indomethacin. The molecular docking analysis was performed to understand the binding interactions of these compounds to COX-2 enzyme. The results from the present investigation suggests that 2,3-diaryl quinazolinones as a promising template for the design of new gastric safe anti-inflammatory agents, which can be further explored for potential anti-inflammatory activity.

Modeling the binding modes of stilbene analogs to cyclooxygenase-2: a molecular docking study

Stilbene analogs are a new class of anti-inflammatory compounds that effectively inhibit COX-2, which is the major target in the treatment of inflammation and pain. In this study, docking simulations were conducted using AutoDock 4 software that focused on the binding of this class of compounds to COX-2 protein. Our aim was to better understand the structural and chemical features responsible for the recognition mechanism of these compounds, and to explore their binding modes of interaction at the active site by comparing them with COX-2 co-crystallized with SC-558. The docking results allowed us to provide a plausible explanation for the different binding affinities observed experimentally. These results show that important conserved residues, in particular Arg513, Phe518, Trp387, Leu352, Leu531 and Arg120, could be essential for the binding of the ligands to COX-2 protein. The quality of the docking model was estimated based on the binding energies of the studied compounds. A good correlation was obtained between experimental logAr values and the predicted binding energies of the studied compounds.

Histone deacetylase inhibitors (HDACIs). Structure--activity relationships: history and new QSAR perspectives

Histone deacetylase (HDAC) inhibition is a recent, clinically validated therapeutic strategy for cancer treatment. HDAC inhibitors (HDACIs) block angiogenesis, arrest cell growth, and lead to differentiation and apoptosis in tumor cells. In this article, a survey of published quantitative structure-activity relationships (QSARs) studies are presented and discussed in the hope of identifying the structural determinants for anticancer activity. Secondly a two-dimensional QSAR study was carried out on biological results derived from various types of HDACIs and from different assays using the C-QSAR program of Biobyte. The QSAR analysis presented here is an attempt to organize the knowledge on the HDACIs with the purpose of designing new chemical entities with enhanced inhibitory potencies and to study the mechanism of action of the compounds. This study revealed that lipophilicity is one of the most important determinants of activity. Additionally, steric factors such as the overall molar refractivity (CMR), molar volume (MgVol), the substituent's molar refractivity (MR) (linear or parabola), or the sterimol parameters B(1) and L are important. Electronic parameters indicated as σ(p), are found to be present only in one case.

Topological polar surface area: a useful descriptor in 2D-QSAR

Topological polar surface area (TPSA), which makes use of functional group contributions based on a large database of structures, is a convenient measure of the polar surface area that avoids the need to calculate ligand 3D structure or to decide which is the relevant biological conformation or conformations. We demonstrate the utility of TPSA in 2D-QSAR for 14 sets of diverse pharmacological activity data. Even though a large pool of reports showing the importance of the classic 2D descriptors such as calculated logP (ClogP) and calculated molar refractivity (CMR) exists in the 2D-QSAR literature, this is the first report to demonstrate the value of TPSA as a relevant descriptor applicable to a large, structurally and pharmacologically diverse set of classes of compounds. We also address the limitations of applicability of this descriptor for 2D-QSAR analysis. We observed a negative correlation of TPSA with activity data for anticancer alkaloids, MT1 and MT2 agonists, MAO-B and tumor necrosis factor-alpha inhibitors and a positive correlation with inhibitory activity data for telomerase, PDE-5, GSK-3, DNA-PK, aromatase, malaria, trypanosomatids and CB2 agonists.

Lipoxygenase inhibitors: a comparative QSAR study review and evaluation of new QSARs

This paper contains a quantitative structure activity relationship (QSAR) study for lipoxygenase (LO) inhibitors. It reveals that in almost all cases, the clog P parameter plays an important part in the QSARs (linear or bilinear model). In some cases the steric factors such as the overall molar refractivity (CMR) or the substituents molar refractivity (MR) (linear or parabola) are important. Electronic effects are comparatively unimportant. The study shows that log P as calculated from the Clog P program is suitable for this form of QSAR study.

y-Randomization and Its Variants in QSPR/QSAR

y-Randomization is a tool used in validation of QSPR/QSAR models, whereby the performance of the original model in data description (r2) is compared to that of models built for permuted (randomly shuffled) response, based on the original descriptor pool and the original model building procedure. We compared y-randomization and several variants thereof, using original response, permuted response, or random number pseudoresponse and original descriptors or random number pseudodescriptors, in the typical setting of multilinear regression (MLR) with descriptor selection. For each combination of number of observations (compounds), number of descriptors in the final model, and number of descriptors in the pool to select from, computer experiments using the same descriptor selection method result in two different mean highest random r2 values. A lower one is produced by y-randomization or a variant likewise based on the original descriptors, while a higher one is obtained from variants that use random number pseudodescriptors. The difference is due to the intercorrelation of real descriptors in the pool. We propose to compare an original model's r2 to both of these whenever possible. The meaning of the three possible outcomes of such a double test is discussed. Often y-randomization is not available to a potential user of a model, due to the values of all descriptors in the pool for all compounds not being published. In such cases random number experiments as proposed here are still possible. The test was applied to several recently published MLR QSAR equations, and cases of failure were identified. Some progress also is reported toward the aim of obtaining the mean highest r2 of random pseudomodels by calculation rather than by tedious multiple simulations on random number variables.

Molecular modeling of hexakis(areneisonitrile)technetium(I), tricarbonyl eta5 cyclopentadienyl technetium and technetium(V)-oxo complexes: MM3 parameter development and prediction of biological properties

Genetic algorithms (GA) were used to develop specific technetium metal-ligand force field parameters for the MM3 force field. These parameters were developed using automated procedures within the program FFGenerAtor from a combination of crystallographic structures and ab initio calculations. These new parameters produced results in good agreement with experiment when tested against a blind validation set. To illustrate the utility of these new force field parameters, quantitative structure-activity relationship (QSAR) models were developed to predict the P-glycoprotein uptake (log10 VI) of a series of hexakis(areneisonitrile)technetium(I) complexes and to predict their biodistribution. The log10 VI QSAR model, built using a training set of 16 Tc(I) isonitrile complexes, exhibited a correlation between the experimental log10 VI and 5 simple descriptors as follows: r2 = 0.94, q2 = 0.93. When applied to an external test set of six Tc(I) isonitrile complexes, the QSAR preformed with great accuracy q2 = 0.78 based on a leave-one-out cross-validation analysis. Further QSAR models were developed to predict the biodistribution of the same set of Tc(I) isonitrile complexes; a QSAR model to predict hepatic uptake exhibited a correlation between the experimental log10(Blood/Liver) with six simple descriptors as follows: r2 = 0.97, q2 = 0.96. A QSAR model to predict renal uptake exhibited a correlation between the experimental log10(Blood/Kidney) and six simple descriptors as follows: r2 = 0.85, q2 = 0.82. When applied to the external test set the QSAR models preformed with great accuracy, q2 = 0.78 and 0.56, respectively.

Probing the physicochemical and structural requirements for glycogen synthase kinase-3alpha inhibition: 2D-QSAR for 3-anilino-4-phenylmaleimides

Glycogen synthase kinase-3alpha (GSK-3alpha) was recently found to be an attractive target for the treatment of Alzheimer's disease due to its dual action in the formation of both amyloid plaques and neurofibrillary tangles. It is also a viable target for many other diseases, such as type 2 diabetes. Reported herein is a 2D-QSAR exploration of the physicochemical (hydrophobic, electronic, and steric) and structural requirements among 3-anilino-4-phenylmaleimides toward GSK-3alpha binding. Using Fujita-Ban and Hansch QSAR analysis, electronic and steric interactions at the 4-phenyl ring and hydrophobic interactions at the 3-anilino ring are shown to be crucial. Analysis of the 4-phenyl ring of these compounds using common aromatic substituent constants showed electron-withdrawing and bulky ortho substituents as imperative for GSK-3alpha inhibition.

Adaptive Configuring of Radial Basis Function Network by Hybrid Particle Swarm Algorithm for QSAR Studies of Organic Compounds

The configuring of a radial basis function network (RBFN) consists of selecting the network parameters (centers and widths in RBF units and weights between the hidden and output layers) and network architecture. The issues of suboptimum and overfitting, however, often occur in RBFN configuring. This paper presented a hybrid particle swarm optimization (HPSO) algorithm to simultaneously search the optimal network structure and parameters involved in the RBFN (HPSORBFN) with an ellipsoidal Gaussian function as a basis function. The continuous version of PSO was used for parameter training, while the modified discrete PSO was employed to determine the appropriate network topology. The proposed HPSORBFN algorithm was applied to modeling the inhibitory activities of substituted bis[(acridine-4-carboxamide)propyl]methylamines to murine P388 leukemia cells and the bioactivities of COX-2 inhibitors. The results were compared with those obtained from RBFNs with the parameters optimized by continuous PSO and by conventionally RBFN training the algorithm for a fixed network topology, indicating that the HPSO was competent for RBFN configuring in that it converged quickly toward the optimal solution and avoided overfitting.

Inhibitory mode of 2-acetoxyphenyl alkyl sulfides against COX-1 and COX-2: QSAR analyses

Selective inhibition of cyclooxygenase-2 (COX-2) inhibitors is an important strategy in design of potent anti-inflammatory compounds with significantly reduced side effects. Therefore, QSAR studies of 2-acetoxyphenyl alkyl sulfides were performed using Bioloom, CAChe 6.1, and Dragon 3.0 for the COX-2 and COX-1 inhibition. The analyses have produced good predictive and statistically significant QSAR models. These studies suggest that lipophilicity affects both COX-1 and COX-2 inhibition in different manner and indicator variables like presence of aromatic ring and triple bond play an important role in COX-2 selectivity. Branching in the molecule, higher path length 6 rich in polarizability, and lesser number of carbonyl groups would be favorable for COX-2 inhibition. Fourth highest eigenvalue of burden matrix corresponding to atomic mass would be favorable for COX-2 inhibition and sixth lowest eigenvalue of burden matrix corresponding to Sanderson electronegativities is conducive for COX-1 inhibition. Lower path length 3 rich in atomic mass and lesser degree of unsaturation in the molecule would be favorable for COX-1 inhibition.

Support vector machine based training of multilayer feedforward neural networks as optimized by particle swarm algorithm: Application in QSAR studies of bioactivity of organic compounds

Multilayer feedforward neural networks (MLFNNs) are important modeling techniques widely used in QSAR studies for their ability to represent nonlinear relationships between descriptors and activity. However, the problems of overfitting and premature convergence to local optima still pose great challenges in the practice of MLFNNs. To circumvent these problems, a support vector machine (SVM) based training algorithm for MLFNNs has been developed with the incorporation of particle swarm optimization (PSO). The introduction of the SVM based training mechanism imparts the developed algorithm with inherent capacity for combating the overfitting problem. Moreover, with the implementation of PSO for searching the optimal network weights, the SVM based learning algorithm shows relatively high efficiency in converging to the optima. The proposed algorithm has been evaluated using the Hansch data set. Application to QSAR studies of the activity of COX-2 inhibitors is also demonstrated. The results reveal that this technique provides superior performance to backpropagation (BP) and PSO training neural networks.

Comparative study of QSAR/QSPR correlations using support vector machines, radial basis function neural networks, and multiple linear regression

Support vector machines (SVMs) were used to develop QSAR models that correlate molecular structures to their toxicity and bioactivities. The performance and predictive ability of SVM are investigated and compared with other methods such as multiple linear regression and radial basis function neural network methods. In the present study, two different data sets were evaluated. The first one involves an application of SVM to the development of a QSAR model for the prediction of toxicities of 153 phenols, and the second investigation deals with the QSAR model between the structures and the activities of a set of 85 cyclooxygenase 2 (COX-2) inhibitors. For each application, the molecular structures were described using either the physicochemical parameters or molecular descriptors. In both studied cases, the predictive ability of the SVM model is comparable or superior to those obtained by MLR and RBFNN. The results indicate that SVM can be used as an alternative powerful modeling tool for QSAR studies.

Oxidation of Aromatic Lithium Thiolates into Sulfinate Salts: An Attractive Entry to Aryl Sulfones Labeled with Carbon-11

[reaction: see text] Aromatic 11C-sulfones were synthesized by S alkylation of lithium arenesulfinates, which are readily available from the corresponding thiols by an oxaziridine-mediated oxidation reaction with [11C]alkyl iodides in THF/H2O (4:1) at 150 degrees C. The radiosyntheses, including purification by HPLC, were completed in an average of 35 min from the end of the bombardment with 55-76% overall radiochemical yields (decay corrected). The described procedure extends the range of accessible labeling methods.

QSAR studies of copper azamacrocycles and thiosemicarbazones: MM3 parameter development and prediction of biological properties

Genetic algorithms (GA) were used to develop specific copper metal-ligand force field parameters for the MM3 force field, from a combination of crystallographic structures and ab initio calculations. These new parameters produced results in good agreement with experiment and previously reported copper metal-ligand parameters for the AMBER force field. The MM3 parameters were then used to develop several quantitative structure-activity relationship (QSAR) models. A successful QSAR for predicting the lipophilicity (log P(ow)) of several classes of Cu(II)-chelating ligands was built using a training set of 32 Cu(II) radiometal complexes and 6 simple molecular descriptors. The QSAR exhibited a correlation between the predicted and experimental log P(ow) with an r(2) = 0.95, q(2) = 0.92. When applied to an external test set of 11 Cu(II) complexes, the QSAR preformed with great accuracy; r(2) = 0.93 and a q(2) = 0.91 utilizing a leave-one-out cross-validation analysis. Additional QSAR models were developed to predict the biodistribution of a smaller set of Cu(II) bis(thiosemicarbazone) complexes.

Pairwise decomposition of residue interaction energies using semiempirical quantum mechanical methods in studies of protein-ligand interaction

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 protein-ligand complexes as determined by X-ray crystallography.