Combined 2D and 3D-QSAR,molecular modelling and docking studies of pyrazolodiazepinones as novel phosphodiesterase 2 inhibitors

Selective inhibition of phosphodiesterase 2 (PDE2) in cells where it is located elevates cyclic guanosine monophosphate (cGMP) and acts as novel analgesic with antinociceptive activity. Three-dimensional quantitative structure–activity relationship (QSAR) studies for pyrazolodiazepinone inhibitors exhibiting PDE2 inhibition were performed using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and Topomer CoMFA, and two-dimensional QSAR study was performed using a Hologram QSAR (HQSAR) method. QSAR models were generated using training set of 23 compounds and were validated using test set of nine compounds. The optimum partial least squares (PLS) for CoMFA-Focusing, CoMSIA-SDH, Topomer CoMFA and HQSAR models exhibited good ‘leave-one-out’ cross validated correlation coefficient (q²) of 0.790, 0.769, 0.840 and 0.787, coefficient of determination (r²) of 0.999, 0.964, 0.979 and 0.980, and high predictive power (r²_pred) of 0.796, 0.833, 0.820 and 0.803 respectively. Docking studies revealed that those inhibitors able to bind to amino acid Gln859 by cGMP binding orientation called ‘glutamine-switch’, and also bind to the hydrophobic clamp of PDE2 isoform, could possess high selectivity for PDE2. From the results of all the studies, structure–activity relationships and structural requirements for binding to active site of PDE2 were established which provide useful guidance for the design and future synthesis of potent PDE2 inhibitors.     

Insight into the structural requirements of pyrimidine-based phosphodiesterase 10A (PDE10A) inhibitors by multiple validated 3D QSAR approaches

Schizophrenia is a complex disorder of thinking and behaviour (0.3?0.7% of the population is affected). The over-expression of phosphodiesterase 10A (PDE10A) enzyme may be a potential target for schizophrenia and Huntington’s disease. Because 3D QSAR analysis is one of the most frequently used modelling techniques, in the present study, five different 3D QSAR tools, namely CoMFA, CoMSIA, kNN-MFA, Open3DQSAR and topomer CoMFA methods, were used on a dataset of pyrimidine-based PDE10A inhibitors. All developed models were validated internally and externally. The non-commercial Open3DQSAR produced the best statistical results amongst 3D QSAR tools. The structural interpretations obtained from different methods were thoroughly analysed and were justified on the basis of information obtained from the crystal structure. Information from one method was mostly validated by the results of other methods and vice versa. In the current work, the use of multiple tools in the same analysis revealed more complete information about the structural requirements of these compounds. On the basis of the observations of the 3D QSAR studies, 12 new compounds were designed for better PDE10A inhibitory activity. The current investigation may help in further designing new PDE10A inhibitors with promising activity.     

High-throughput catch-and-release synthesis of oxazoline hydroxamates. Structure-activity relationships in novel inhibitors of Escherichia coli LpxC: in vitro enzyme inhibition and antibacterial properties

LpxC is a zinc amidase that catalyses the second step of lipid A biosynthesis in Gram-negative bacteria. Oxazolines incorporating a hydroxamic acid, which is believed to coordinate to the single essential zinc ion, at the 4-position are known inhibitors of this enzyme. Some of these enzyme inhibitors exhibit antibacterial activity through their inhibition of LpxC. We recently developed a method for the synthesis of oxazolines using resin capture and ring-forming release that eliminates traditional purification steps and can be used in high-throughput synthesis. Using our method, oxazoline hydroxamates with diverse 2-substituents were prepared in library form as candidate inhibitors for LpxC. Two conventional methods for oxazoline synthesis were also applied to generate more than 70 compounds. The groups at the 2-position included a wide variety of substituted aromatic rings and a limited selection of alkyl groups. These compounds were screened against wild-type and LpxC inhibitor-sensitive strains of Escherichia coli, as well as wild-type Pseudomonas aeruginosa. Inhibition of the E. coli LpxC enzyme was also investigated. A broad correlation between enzyme inhibitory and antibacterial activity was observed, and novel compounds were discovered that exhibit antibacterial activity but fall outside earlier-known structural classes.     

Theoretical studies on QSAR and mechanism of 2‐indolinone derivatives as tubulin inhibitors

The theoretical studies on three‐dimensional quantitative structure activity relationship (3D‐QSAR) and action mechanism of a series of 2‐indolinone derivatives as tubulin inhibitors against human breast cancer cell line MDA‐MB‐231 have been carried out. The established 3D‐QSAR model from the comparative molecular field analysis (CoMFA) shows not only significant statistical quality but also predictive ability, with high correlation coefficient (R² = 0.986) and cross‐validation coefficient (q² = 0.683). In particular, the appropriate binding orientations and conformations of these 2‐indolinone derivatives interacting with tubulin are located by docking study, and it is very interesting to find that the plot of the energy scores of these compounds in DOCK versus the corresponding experimental pIC₅₀ values exhibits a considerable linear correlation. Therefore, the inhibition mechanism that 2‐indolinone derivatives were regarded as tubulin inhibitors can be theoretically confirmed. Based on such an inhibition mechanism along with 3D‐QSAR results, some important factors improving the activities of these compounds were discussed in detail. These factors can be summarized as follows: the H atom adopted as substituent R₁, the substituent R₂ with higher electropositivity and smaller bulk, the substituents R₄–R₆ (on the phenyl ring) with higher electropositivity and larger bulk, and so on. These results can offer useful theoretical references for understanding the action mechanism, designing more potent inhibitors, and predicting their activities prior to synthesis. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2009     

Synthesis and structure-activity relationship of N-arylrolipram derivatives as inhibitors of PDE4 isozymes

Structure activity studies of N-phenylrolipram derivatives have led to the identification of highly potent PDE4 inhibitors. The potential of these inhibitors for cellular activity was routinely assessed in an assay of fMLP induced oxidative burst in human eosinophils. Since first generation PDE4 inhibitors have been plagued with a number of unwanted side effects, parallel structure activity studies for competition with the [3H]-rolipram binding site in rat brain were performed. In this fashion 5-[4-(3-cyclopentyloxy-4-methoxyphenyl)-2-oxo-pyrrolidin-1-yl]-3-(3-methoxybenzyloxy)benzoic acid N',N'-dimethylhydrazide (22) was identified as a potent inhibitor of PDE4 which exhibits >1000 fold selectivity versus PDE3, and is a nanomolar inhibitor in all the cellular assays tested. Studies on the stereoselectivity of PDE4 inhibition of this class of rolipram based compounds revealed, that for example (S)-11 is a more potent inhibitor than (R)-11. This effect can also be observed in primary human cells where the (S)-enantiomer is about 10 fold more potent than the corresponding (R)-enantiomer.     

Quantitative structure-activity relationship study of N-(3-oxo-3,4-dihydro-2H-benzo[1,4]thiazine-6-carbonyl)guanidines as potent Na/H exchange inhibitors

We have previously reported that N-(4-isopropyl-2,2-dimethyl-3-oxo-3,4-dihydro-2H-benzo[1,4]oxazine-6-car bonyl)guanidine (4b) methanesulfonate salt (KB-R9032) is a potent and highly water-soluble Na/H exchange inhibitor. In a series of studies on Na/H exchange inhibitors, we designed and synthesized N-(3-oxo-3,4-dihydro-2H-benzo[1,4]thiazine-6-carbonyl)guanidines (5) as more potent inhibitors with high water-solubility. The design strategy for 5 was based on a quantitative structure-activity relationship (QSAR) study, involving the proportional relationship between the biological activity and hydrophobicity of the ring structure of compounds 4. As expected, compounds 5 showed more potent activity than 4. It was found by using the QSAR analysis that 5 were about five-fold more potent than 4. The increase in potency of compounds 5 well agreed with our previous QSAR analysis result. The most potent derivative was the methanesulfonate salt 5d of the 4-isopropyl derivative (IC50=0.0091 microM). And in addition to the in vitro study, 5d showed significant protective activity against a rat acute myocardial infraction model.     

CoMFA and CoMSIA 3D-quantitative structure-activity relationship model on benzodiazepine derivatives, inhibitors of phosphodiesterase IV

Recently, we reported structurally novel PDE4 inhibitors based on 1,4-benzodiazepine derivatives. The main interest in developing bezodiazepine-based PDE4 inhibitors is in their lack of adverse effects of emesis with respect to rolipram-like compounds. A large effort has thus been made toward the structural optimization of this series. In the absence of structural information on the inhibitor binding mode into the PDE4 active site, 2D-QSAR (H-QSAR) and two 3D-QSAR (CoMFA and CoMSIA) methods were applied to improve our understanding of the molecular mechanism controlling the PDE4 affinity of the benzodiazepine derivatives. As expected, the CoMSIA 3D contour maps have provided more information on the benzodiazepine interaction mode with the PDE4 active site whereas CoMFA has built the best tool for activity prediction. The 2D pharmacophoric model derived from CoMSIA fields is consistent with the crystal structure of the PDE4 active site reported recently. The combination of the 2D and 3D-QSAR models was used not only to predict new compounds from the structural optimization process, but also to screen a large library of bezodiazepine derivatives.     

Species-specific and inhibitor-dependent conformations of LpxC: implications for antibiotic design

LpxC is an essential enzyme in the lipid A biosynthetic pathway in gram-negative bacteria. Several promising antimicrobial lead compounds targeting LpxC have been reported, though they typically display a large variation in potency against different gram-negative pathogens. We report that inhibitors with a diacetylene scaffold effectively overcome the resistance caused by sequence variation in the LpxC substrate-binding passage. Compound binding is captured in complex with representative LpxC orthologs, and structural analysis reveals large conformational differences that mostly reflect inherent molecular features of distinct LpxC orthologs, whereas ligand-induced structural adaptations occur at a smaller scale. These observations highlight the need for a molecular understanding of inherent structural features and conformational plasticity of LpxC enzymes for optimizing LpxC inhibitors as broad-spectrum antibiotics against gram-negative infections.     

Experimental and theoretical studies on the inhibition potentials of some derivatives of cyclopenta‐1,3‐diene for the corrosion of mild steel in HCl solutions

The inhibition of the corrosion of mild steel in HCl by some cyclopentadiene‐1,3‐diene derivatives, namely, 1‐(thiophen‐2‐yl)ethanone (2APT), 1‐(1H‐pyrrol‐2‐yl)ethanone (2AP), and (E)‐2‐(1‐hydrazonoethyl)‐1H‐pyrrole (2APH)), was studied experimentally using weight loss and hydrogen gas evolution measurements. The theoretical aspect was studied using the density functional theory and quantitative structure activity relation (QSAR) methods. The results obtained indicated that the studied compounds are good inhibitors for the corrosion of mild steel in HCl. The adsorption of the inhibitor on mild steel surface was found to be spontaneous, exothermic, and obeyed the Langmuir adsorption isotherm model. A good correlation was found between experimental inhibition efficiencies and some calculated quantum chemical parameters and also with the theoretical inhibition efficiencies obtained from QSAR modeling. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011     

Escherichia coli versus Pseudomonas aeruginosa deacetylase LpxC inhibitors selectivity: surface and cavity-depth-based analysis

Although Escherichia coli and Pseudomonas aeruginosa LpxC share sequence and functional similarity, E. coli LpxC inhibitiors are ineffective against P. aeruginosa LpxC. It was earlier speculated that inactivity of the inhibitors is due to intrinsic resistance possibly mediated by efflux pumps. However, a recent study has documented that the inactivity is due to failure of inhibitor(s) to inhibit the enzyme rather then intrinsic resistance. In this study, we carried out a surface and cavity-depth-based analysis on homology models of E. coli and P. aeruginosa LpxC to get some new insights into the ligand-binding features of these enzymes. The surface analysis of the P. aeruginosa LpxC model suggested that the LpxC catalytic domain (where inhibitors are supposed to bind) has several minor but potentially important structural differences as compared to E. coli LpxC. Molecular docking studies which could distinguish between the reported receptor affinities of the inhibitors additionally helped in the identification of key binding-site residues and interactions. These differences can be exploited for designing broad-spectrum LpxC inhibitors against this target.     

Unified QSAR & network‐based computational chemistry approach to antimicrobials. II. Multiple distance and triadic census analysis of antiparasitic drugs complex networks

In the previous work, we reported a multitarget Quantitative Structure‐Activity Relationship (mt‐QSAR) model to predict drug activity against different fungal species. This mt‐QSAR allowed us to construct a drug–drug multispecies Complex Network (msCN) to investigate drug–drug similarity (González‐Díaz and Prado‐Prado, J Comput Chem 2008, 29, 656). However, important methodological points remained unclear, such as follows: (1) the accuracy of the methods when applied to other problems; (2) the effect of the distance type used to construct the msCN; (3) how to perform the inverse procedure to study species–species similarity with multidrug resistance CNs (mdrCN); and (4) the implications and necessary steps to perform a substructural Triadic Census Analysis (TCA) of the msCN. To continue the present series with other important problem, we developed here a mt‐QSAR model for more than 700 drugs tested in the literature against different parasites (predicting antiparasitic drugs). The data were processed by Linear Discriminate Analysis (LDA) and the model classifies correctly 93.62% (1160 out of 1239 cases) in training. The model validation was carried out by means of external predicting series; the model classified 573 out of 607, that is, 94.4% of cases. Next, we carried out the first comparative study of the topology of six different drug–drug msCNs based on six different distances such as Euclidean, Chebychev, Manhattan, etc. Furthermore, we compared the selected drug–drug msCN and species–species mdsCN with random networks. We also introduced here the inverse methodology to construct species–species msCN based on a mt‐QSAR model. Last, we reported the first substructural analysis of drug–drug msCN using Triadic Census Analysis (TCA) algorithm. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010     

Variable selection and specification of robust QSAR models from multicollinear data: arylpiperazinyl derivatives with affinity and selectivity for α<Subscript>2</Subscript>-adrenoceptors

Two QSAR models have been identified that predict the affinity and selectivity of arylpiperazinyl derivatives for alpha1 and alpha2 adrenoceptors (ARs). The models have been specified and validated using 108 compounds whose structures and inhibition constants (Ki) are available in the literature [Barbaro et al., J. Med. Chem., 44 (2001) 2118; Betti et al., J. Med. Chem., 45 (2002) 3603; Barbaro et al., Bioorg. Med. Chem., 10 (2002) 361; Betti et al., J. Med. Chem., 46 (2003) 3555]. One hundred and forty-seven predictors have been calculated using the Cerius 2 software available from Accelrys. This set of variables exhibited redundancy and severe multicollinearity, which had to be identified and removed as appropriate in order to obtain robust regression models free of inflated errors for the beta estimates - so-called bouncing betas. Those predictors that contained information relevant to the alpha2 response were identified on the basis of their pairwise linear correlations with affinity (-log Ki) for alpha2 adrenoceptors; the remaining variables were discarded. Subsequent variable selection made use of Factor Analysis (FA) and Unsupervised Variable Selection (UzFS). The data was divided into test and training sets using cluster analysis. These two sets were characterised by similar and consistent distributions of compounds in a high dimensional, but relevant predictor space. Multiple regression was then used to determine a subset of predictors from which to determine QSAR models for affinity to alpha2-ARs. Two multivariate procedures, Continuum Regression (the Portsmouth formulation) and Canonical Correlation Analysis (CCA), have been used to specify models for affinity and selectivity, respectively. Reasonable predictions were obtained using these in silico screening tools.     

QSID Tool: a new three-dimensional QSAR environmental tool

QSID Tool (Quantitative structure–activity relationship tool for Innovative Discovery) was developed to provide an easy-to-use, robust and high quality environmental tool for 3D QSAR. Predictive models developed with QSID Tool can accelerate the discovery of lead compounds by enabling researchers to formulate and test hypotheses for optimizing efficacy and increasing drug safety and bioavailability early in the process of drug discovery. QSID Tool was evaluated by comparison with SYBYL^® using two different datasets derived from the inhibitors of Trypsin (Böhm et al., J Med Chem 42:458, 1999) and p38-MAPK (Liverton et al., J Med Chem 42:2180, 1999; Romeiro et al., J Comput Aided Mol Des 19:385, 2005; Romeiro et al., J Mol Model 12:855, 2006). The results suggest that QSID Tool is a useful model for the prediction of new analogue activities.     

Development of non-peptide ACE inhibitors as novel and potent cardiovascular therapeutics: An in silico modelling approach

Angiotensin-converting enzyme (ACE) inhibitors have been acknowledged as first-line agents for the treatment of hypertension and a variety of cardiovascular disorders. In this context, quantitative structure–activity relationship (QSAR) models for a series of non-peptide compounds as ACE inhibitors are developed based on Simplified Molecular Input-Line Entry System (SMILES) notation and local graph invariants. Three random splits into the training and test sets are used. The Monte Carlo method is applied for model development. Molecular docking studies are used for the final assessment of the developed QSAR model and the design of novel inhibitors. The statistical quality of the developed model is good. Molecular fragments responsible for the increase/decrease of the studied activity are calculated. The computer-aided design of new compounds, as potential ACE inhibitors, is presented. The predictive potential of the applied approach is tested, and the robustness of the model is proven using different methods. The results obtained from molecular docking studies are in excellent correlation with the results from QSAR studies. The presented study may be useful in the search for novel cardiovascular therapeutics based on ACE inhibition.     

咪唑啉衍生物缓蚀剂的定量构效关系及分子设计

采用量子化学密度泛函理论(DFT)及线性回归分析方法, 对十一烷基咪唑啉衍生物缓蚀剂抗H2S、CO2腐蚀性能进行了定量构效关系(QSAR)研究. 通过回归分析, 筛选出了影响缓蚀剂缓蚀性能的主要因素, 建立了QSAR模型, 并使用留一法交叉验证对模型的稳定性及预测能力进行了分析. 结果表明, 电子转移参数△N、咪唑环上非氢原子静电荷之和∑Qring及分子极化率α对咪唑啉类缓蚀剂的缓蚀性能有很大的贡献, 所得模型的拟合相关系数(R2)和交叉验证相关系数(q2)分别为0.924 和0.917, 模型对此类缓蚀剂抗H2S、CO2腐蚀性能具有较好的预测效果. 应用QSAR研究结果进行了分子设计, 在理论上提出了一些具有较高抗H2S、CO2腐蚀性能的新型咪唑啉衍生物, 为实验工作者合成新型缓蚀剂提供理论参考.     

One-pot three-component azide-alkyne cycloaddition: Synthesis of new pyrazole, 1,2,3-triazole,and oxadiazole tethered and their anti-inflammatory,quantitative structure-activity relationship,and docking studies

A simple and efficient one-pot three-component azide-alkyne cycloaddition of 5-chloro-1-phenyl-pyrazole-4-carbaldehyde with 2-(prop-2-yn-1-ylthio)-5-(substituted phenoxy)methyl-1,3,4-oxadiazole and sodium azide is reported. The newly synthesized compounds were characterized by spectral and analytical data. They were screened for in vitro anti-inflammatory activity by bovine serum albumin denaturation assay. All the tested compounds showed moderate anti-inflammatory activity, whereas three compounds ( 4d , 4i , and 4k ) showed excellent activity comparable with that of the standard drug diclofenac sodium. The quantitative structure-activity relationship (QSAR) study was carried out for anti-inflammatory activities of the synthesized compounds and developed a QSAR model. Inspired by their in vitro anti-inflammatory activities, they were docked to the active site of COX-2 to know the anti-inflammatory potency in silico.     

Conceptual DFT properties‐based 3D QSAR: Analysis of inhibitors of the nicotine metabolizing CYP2A6 enzyme

Structure‐activity relationships of 46 P450 2A6 inhibitors were analyzed using the 3D‐QSAR methodology. The analysis was carried out to confront the use of traditional steric and electrostatic fields with that of a number of fields reflecting conceptual DFT properties: electron density, HOMO, LUMO, and Fukui f⁻ function as 3D fields. The most predictive models were obtained by combining the information of the electron density with the Fukui f⁻ function (r² = 0.82, q² = 0.72), yielding a statistically significant and predictive model. The generated model was able to predict the inhibition potencies of an external test set of five chemicals. The result of the analysis indicates that conceptual DFT‐based molecular fields can be useful as 3D QSAR molecular interaction fields. © 2008 Wiley Periodicals, Inc. J Comput Chem 2009     

Theoretical analysis of peptidyl alpha-ketoheterocyclic inhibitors of human neutrophil elastase: Insight into the mechanism of inhibition and the application of QM/MM calculations in structure-based drug design

It has been suggested from QSAR data (P. D. Edwards, D. J. Wolanin, D.A. Andisik and M. W. Davis, J. Med. Chem., 1995, 38, 76) that the inhibition of elastase by peptidyl alpha-ketoheterocyclic inhibitors can occur in two ways, the less potent inhibitors forming a non-bonded Michaelis complex and the more potent set a covalently bonded enzyme-substrate intermediate. We report QM/MM studies of both binding and reactivity that confirm these findings, showing that the activity of the least potent set of inhibitors correlates with the calculated binding energy, and that of the more potent set correlates with the stability of the intermediate. These calculations show that QM/MM methods can be successfully employed to understand complicated structure-activity relationships and might be employed in the design and assessment of new inhibitors.