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MMP-2 overexpression is strongly related to several diseases including cancer. However, none of the MMP-2 inhibitors have been marketed as drug candidates due to various adverse effects. Here, a set of sulphonyl pyrrolidines was subjected to validation of molecular modelling followed by binding mode analysis to explore the crucial structural features required for the discovery of promising MMP-2 inhibitors. This study revealed the importance of hydroxamate as a potential zinc-binding group compared to the esters. Importantly, hydrophobic and sterical substituents were found favourable at the terminal aryl moiety attached to the sulphonyl group. The binding interaction study revealed that the S1′ pocket of MMP-2 similar to 'a basketball passing through a hoop' allows the aryl moiety for proper fitting and interaction at the active site to execute potential MMP-2 inhibition. Again, the sulphonyl pyrrolidine moiety can be a good fragment necessary for MMP-2 inhibition. Moreover, some novel MMP-2 inhibitors were also reported. They showed the significance of the 3rd position substitution of the pyrrolidine ring to produce interaction inside S2′ pocket. The current study can assist in the design and development of potential MMP-2 inhibitors as effective drug candidates for the management of several diseases including cancers in the future. [ABSTRACT FROM AUTHOR]

Mycobacterium tuberculosis DNA gyrase subunit B (GyrB) has been identified as a promising target for rational drug design against fluoroquinolone drug-resistant tuberculosis. In this study, we attempted to identify the key structural feature for highly potent GyrB inhibitors through 2D-QSAR using HQSAR, 3D-QSAR using CoMSIA and molecular dynamics (MD) simulations approaches on a series of thiazole urea core derivatives. The best HQSAR and CoMSIA models based on IC50 and MIC displayed the structural basis required for good activity against both GyrB enzyme and mycobacterial cell. MD simulations and binding free energy analysis using MM-GBSA and waterswap calculations revealed that the urea core of inhibitors has the strongest interaction with Asp79 via hydrogen bond interactions. In addition, cation-pi interaction and hydrophobic interactions of the R2 substituent with Arg82 and Arg141 help to enhance the binding affinity in the GyrB ATPase binding site. Thus, the present study provides crucial structural features and a structural concept for rational design of novel DNA gyrase inhibitors with improved biological activities against both enzyme and mycobacterial cell, and with good pharmacokinetic properties and drug safety profiles. [ABSTRACT FROM AUTHOR]

The current study deals with chemometric modelling strategies (Naïve Bayes classification, hologram-based quantitative structure-activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA)) to explore the important features of hydroxylamine derivatives for exerting potent human immunodeficiency virus-1 (HIV-1) protease inhibition. Depending on the statistically validated reliable and robust quantitative structure-activity relationship (QSAR) models, important and crucial structural features have been identified that may be responsible for enhancing the activity profile of these hydroxylamine compounds. Arylsulfonamide function along with methoxy or fluoro substitution is important for enhancing activity. Bulky steric substitution at the sulfonamide nitrogen disfavours activity whereas smaller hydrophobic substitution at the same position is found to be favourable. Apart from the crucial oxazolidinone moiety, pyrrolidine, cyclic urea and methyl ester functions are also responsible for increasing the HIV-1 protease inhibitory profile. Observations derived from these modelling studies may be utilized further in designing promising HIV-1 protease inhibitors of this class. [ABSTRACT FROM AUTHOR]

Pathogenic Gram-negative bacteria are responsible for nearly half of the serious human infections. Hologram quantitative structure-activity relationships (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) were implemented on a group of 32 of potent Gram-negative LpxC inhibitors. The most effective HQSAR model was obtained using atoms, bonds, donor, and acceptor as fragment distinction. The cross-validated correlation coefficient (q2), non-cross-validated correlation coefficient (r2), and predictive correlation coefficient (r2Pred) for test set of HQSAR model were 0.937, 0.993, and 0.892, respectively. The generated models were found to be statistically significant as the CoMFA model had (r2 = 0.967, q2 = 0.804, r2Pred = 0.827); the CoMSIA model had (r2 = 0.963, q2 = 0.752, r2Pred = 0.857). Molecular docking was employed to validate the results of the HQSAR, CoMFA, and CoMSIA models. Based on the obtained information, six new LpxC inhibitors have been designed. [ABSTRACT FROM AUTHOR]

Matrix metalloproteinase-2 (MMP-2) is a potential target in anticancer drug discovery due to its association with angiogenesis, metastasis and tumour progression. In this study, 67 glutamic acid derivatives, synthesized and evaluated as MMP-2 inhibitors, were taken into account for multi-QSAR modelling study (regression-based 2D-QSAR, classification-based LDA-QSAR, Bayesian classification QSAR, HQSAR, 3D-QSAR CoMFA and CoMSIA as well as Open3DQSAR). All these QSAR studies were statistically validated individually. Regarding the 3D-QSAR analysis, the Open3DQSAR results were better than CoMFA and CoMSIA, although all these 3D-QSAR models supported each other. The importance of biphenylsulphonyl moiety over phenylacetyl/naphthylacetyl moieties was established due to its association with favourable steric and hydrophobic characters. HQSAR, LDA-QSAR and Bayesian classification QSAR studies also suggested that the biphenylsulphonamido group was better than the phenylacetylcarboxamido function. Additionally, glutamines were proven to be far better inhibitors than isoglutamines. Observations obtained from the current study were revalidated and supported by the earlier reported molecular modelling studies. Depending on these observations, newer glutamic acid-based compounds may be designed further in future for potent MMP-2 inhibitory activity. [ABSTRACT FROM AUTHOR]

The dopamine hypothesis states that decreased dopaminergic neurotransmission reduces schizophrenia symptoms. Neurokinin-3 receptor (NK3) antagonists reduce dopamine release and have shown positive effects in pre-clinical and clinical trials. We employed 2D and 3D-QSAR analysis on a series of 40 non-peptide NK3antagonists. Multivariate statistical analysis, PCA and HCA, were performed to rational training/test set splitting and PLS regression was employed to construct all QSAR models. We constructed one highly predictive CoMFA model (q2 = 0.810 andr2 = 0.929) and acceptable HQSAR and CoMSIA models (HQSARq2 = 0.644 andr2 = 0.910; CoMSIAq2 = 0.691,r2 = 0.911). The three different techniques provided convergent physicochemical results. All models indicate cyclopropane, piperidine and di-chloro-phenyl ring attached to cyclopropane ring and also the amide group attached to the piperidine ring could play an important role in ligand–receptor interactions. These findings may contribute to develop potential NK3receptor antagonists for schizophrenia. [ABSTRACT FROM AUTHOR]

Dual inhibition of A2Aand MAO-B is an emerging strategy in neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). In this study, atom-based three-dimensional quantitative structure–activity relationship (3D-QSAR) and hologram quantitative structure–activity relationship (HQSAR) models were generated with benzothiazine and deazaxanthine derivatives. Based on activity against A2Aand MAO-B, two statistically significant 3D-QSAR models (r2= 0.96,q2= 0.76 andr2= 0.91,q2= 0.63) and HQSAR models (r2= 0.93,q2= 0.68 andr2= 0.97,q2= 0.58) were developed. In an activity cliff analysis, structural outliers were identified by calculating the Mahalanobis distance for a pair of compounds with A2Aand MAO-B inhibitory activities. The generated 3D-QSAR and HQSAR models, activity cliff analysis, molecular docking and dynamic studies for dual target protein inhibitors provide key structural scaffolds that serve as building blocks in designing drug-like molecules for neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

The development of resistant malaria and lethality of the disease demands the search for new therapeutic candidates. In this line-up, thiolactone was identified as the potential lead structure and subjected to hologram quantitative structure–activity relationship (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Overall, the QSAR results shows that the LOO cross-validatedq2values of HQSAR, CoMFA and CoMSIA models are 0.791, 0.737 and 0.753, respectively. According to HQSAR, the hydrogen bond donor and acceptor were found to play an important role in governing antimalarial activity of thiolactone derivatives. The fragment contribution map of HQSAR, and contour maps of CoMFA and CoMSIA showed the presence of an electronegative group at the fifth position, and a bulky group at the third and fourth positions of the thiolactone ring, positively contributing to antimalarial activity. Furthermore, molecular docking was performed to analyze the binding mode of newly designed thiolactones with the active site residues ofpfKAS I/II. The prediction of newly designed thiolactone molecules based on QSAR and docking score are in good accordance with each other. Therefore the ligand-based QSAR models and target structure-based docking model developed in this study may be successfully utilized for the design of new antimalarial agents. [ABSTRACT FROM AUTHOR]

Peroxysome proliferator-activated receptors (PPARs) have grown greatly in importance due to their role in the metabolic profile. Among three subtypes (α, γ and δ), we here consider the least investigated δ subtype to explore the molecular fingerprints of selective PPARδ agonists. Validated QSAR models (regression based 2D-QSAR, HQSAR and KPLS) and molecular docking with dynamics analyses support the inference of classification-based Bayesian and recursive models. Chemometric studies indicate that the presence of ether linkages and heterocyclic rings has optimum influence in imparting selective bioactivity. Pharmacophore models and docking with molecular dynamics analyses postulate the occurrence of aromatic rings, HB acceptor and a hydrophobic region as crucial molecular fragments for development of PPARδ modulators. Multi-chemometric studies suggest the essential structural requirements of a molecule for imparting potent and selective PPARδ modulation. [ABSTRACT FROM PUBLISHER]

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 (r2pred) 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. [ABSTRACT FROM AUTHOR]

Adenosine receptors have been considered as potential targets for drug development, but one of the main obstacles to this goal is to selectively inhibit one receptor subtype over the others. This subject is particularly crucial for adenosine A2b receptor antagonists (AdoRA2B). The structure--activity relationships of xanthine derivatives which are AdoRA2B have been comprehensively investigated, but the steric and electronic requirements of deazaxanthine AdoRA2B have not been described from a quantitative standpoint of view. Herein we report our efforts to shorten this knowledge gap through 2D-QSAR (HQSAR) and 3D-QSAR (CoMFA) approaches. The good statistical quality (HQSAR - r2 = 0.85, = 0.77; CoMFA - r2 = 0.86, q2 = 0.70) and predictive ability (= 0.78, = 0.78 and = 0.70, = 0.70, respectively) of the models, along with the information provided by contribution and contour maps hints their usefulness to the design of more potent 9-deazaxanthine derivatives. [ABSTRACT FROM AUTHOR]

Molecular modelling studies were performed to identify the essential structural requirements of quinoline-based derivatives for improving their antimalarial activity. The developed CoMFA, CoMSIA and HQSAR models for a training set comprising 37 derivatives showed good statistical significance in terms of internal cross validation (q2) 0.70, 0.69 and 0.80 and non-cross validation (r2) 0.80, 0.79 and 0.80. Also, the predictedr2values (r2pred) of 0.63, 0.61 and 0.72 for a test set consisting of 12 compounds suggested significant predicting ability of the models. Structural features were correlated in terms of steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor interactions. Furthermore, the bioactive conformation was explored and explained by docking compounds #28, 32 and 40 into the active binding site of lactate dehydrogenase ofPlasmodium falciparum. The QSAR models, contour map and docking binding affinity obtained could be successfully utilized as a guiding tool for the design and discovery of novel quinoline-based derivatives with potent antimalarial activity. [ABSTRACT FROM AUTHOR]

This study reports the utilization of three approaches – pharmacophore, CoMFA/CoMSIA and HQSAR studies – to identify the essential structural requirements in 3D chemical space for the modulation of the antimalarial activity of substituted 1,2,4-trioxanes. The superiority of quantitative pharmacophore-based alignment (QuantitativePBA) over global minima energy conformer-based alignment (GMCBA) has been reported in CoMFA and CoMSIA studies. The developed models showed good statistical significance in internal validation (q2, group cross-validation and bootstrapping) and performed very well in predicting the antimalarial activity of test set compounds. Structural features in terms of their steric, electrostatic and hydrophobic interactions in 3D space have been found to be important for the antimalarial activity of substituted 1,2,4-trioxanes. Further, the HQSAR studies based on the same training and test set acted as an additional tool to find the sub-structural fingerprints of substituted 1,2,4-trioxanes for their antimalarial activity. Together, these studies may facilitate the design and discovery of new substituted 1,2,4-trioxanes with potent antimalarial activity. [ABSTRACT FROM AUTHOR]

The estrogen receptor-beta subtype (ERβ) is an attractive drug target for the development of novel therapeutic agents for hormone replacement therapy. Hologram quantitative structure-activity relationships (HQSAR) were conducted on a series of 6-phenylnaphthalene and 2-phenylquinoline derivatives, employing values of ERβ binding affinity. A training set of 65 compounds served to derive the models. The best statistical HQSAR model (q2 = 0.73 and r2 = 0.91) was generated using atoms, bonds, connections and donor and acceptor as fragment distinction parameters, and fragment size default (4-7) with hologram length of 199. The model was used to predict the binding affinity of an external test set of 16 compounds, and the predicted values were in good agreement with the experimental results. The final HQSAR model and the information obtained from 2D contribution maps should be useful for the design of novel ERβ modulators having improved affinity. [ABSTRACT FROM AUTHOR]

The enzyme FabH catalyzes the initial step of fatty acid biosynthesis via a type II fatty acid synthase. The pivotal role of this essential enzyme combined with its unique structural features and ubiquitous occurrence in bacteria has made it an attractive new target for the development of antibacterial and antiparasitic compounds. Predictive hologram quantitative structure activity relationship (HQSAR) model was developed for a series of benzoylamino benzoic acid derivatives acting as FabH inhibitor. The best HQSAR model was generated using atoms and bond types as fragment distinction and 4–7 as fragment size showing cross-validated q2 value of 0.678 and conventional r2 value of 0.920. The predictive ability of the model was validated by an external test set of 6 compounds giving satisfactory predictive r2 value of 0.82. The contribution maps obtained from this model were used to explain the individual atomic contributions to the overall activity. It was confirmed from the contribution map that both ring A and ring C play a vital role for activity. Moreover hydroxyl substitution in the ortho position of ring A is favorable for better inhibitory activity. Therefore the information derived from the contribution map can be used to design potent FabH inhibitors. [ABSTRACT FROM AUTHOR]

By using hologram quantitative structure-activity relationship (HQSAR) and comparative molecular field analysis (CoMFA) methods, the relationships between the structures of 49 gallic acid derivatives and their analgesic activity have been investigated to yield statistically reliable models with considerable predictive power. The best HQSAR model was generated using atoms, bond and connectivity as fragment distinction parameters and fragment size 5-7 from a hologram length of 307 with 3 components. High conventional r 2 ( r 2 =0.825) and cross-validation r 2 ( r cv 2 =0.726) values were obtained. CoMFA analyses varying lattice size and location, grid spacing, probe charges and using, Tripos standard and Indicator force field were performed. The best model was developed with 4 components using sp 3 -hybridized carbon atom with +1.0 charge as probe, grid spacing (2 Å), lattice offset (1.0, 3.0, -2.5). The CoMFA model showed a conventional correlation coefficient r 2 of 0.889 and a cross-validation r cv 2 equals to 0.633. The robustness and predictive ability of the HQSAR and CoMFA models have been validated by means of an external test set. The results indicate that both models possess high statistical quality in the prediction of analgesic potency of novel gallic acid analogs. [ABSTRACT FROM AUTHOR]