Synthesis of substituted diarylmethylenepiperidines (DAMPs), a novel class of anti-HIV agents

Synthesis, characterization, computational calculation and biological studies of some 2,6-diaryl-1-(prop-2-yn-1-yl)piperidin-4-one oxime derivatives

A new series of 2,6-diaryl-1-(prop-2-yn-1-yl)piperidin-4-one oximes (17-24) were designed and synthesized from 2,6-diarylpiperidin-4-one oximes (9-16) with propargyl bromide. Unambiguous structural elucidation has been carried out by investigating IR, NMR ((1)H, (13)C, (1)H-(1)H COSY and HSQC), mass spectral techniques and theoretical (DFT) calculations. Further, crystal structure of compound 17 was evaluated by single crystal X-ray diffraction analysis. Single crystal X-ray structural analysis of compound 17 evidenced that the configuration about CN double bond is syn to C-5 carbon (E-form). The existence of chair conformation was further confirmed by theoretical DFT calculation. All the synthesized compounds were screened for in vitro antimicrobial activity against a panel of selected bacterial and fungal strains using Ciprofloxacin and Ketoconazole as standards. The minimum inhibition concentration (MIC) results revealed that most of the 2,6-diaryl-1-(prop-2-yn-1-yl)piperidin-4-one oximes (17, 19, 20 and 23) exhibited better activity against the selected bacterial and fungal strains.

Synthesis and biological evaluation of 2-amino-3-(3',4',5'-trimethoxybenzoyl)-6-substituted-4,5,6,7-tetrahydrothieno[2,3-c]pyridine derivatives as antimitotic agents and inhibitors of tubulin polymerization

Microtubules are among the most successful targets of compounds potentially useful for cancer therapy. A new series of inhibitors of tubulin polymerization based on the 2-amino-3-(3,4,5-trimethoxybenzoyl)-4,5,6,7-tetrahydrothieno[b]pyridine molecular skeleton was synthesized and evaluated for antiproliferative activity, inhibition of tubulin polymerization, and cell cycle effects. The most promising compound in this series was 2-amino-3-(3,4,5-trimethoxybenzoyl)-6-methoxycarbonyl-4,5,6,7-tetrahydrothieno[b]pyridine, which inhibits cancer cell growth with IC(50)-values ranging from 25 to 90 nM against a panel of four cancer cell lines, and interacts strongly with tubulin by binding to the colchicine site. In this series of N(6)-carbamate derivatives, any further increase in the length and in the size of the alkyl chain resulted in reduced activity.

Exploring molecular shape analysis of styrylquinoline derivatives as HIV-1 integrase inhibitors

HIV-1 integrase inhibitory activity data of styrylquinoline derivatives have been subjected to 3D-QSAR study by molecular shape analysis (MSA) technique using Cerius(2) version 4.8 software (Accelrys). For the selection of test set compounds, initially a QSAR analysis was done based on topological and structural descriptors and K-means clustering technique was used to classify the entire data set (n=36). Clusters were formed from the factor scores of the whole data set comprising of topological and structural descriptors without the biological activity, and based on the clusters, the data set was divided into training and test sets (n=26 and n=10, respectively) so that all clusters are properly represented in both training and test sets. In the molecular shape analysis, the major steps were (1) generation of conformers and energy minimization; (2) hypothesizing an active conformer (global minimum of the most active compound); (3) selecting a candidate shape reference compound (based on active conformation); (4) performing pair-wise molecular superimposition using maximum common subgroup [MCSG] method; (5) measuring molecular shape commonality using MSA descriptors; (6) determination of other molecular features by calculating spatial and conformational parameters; (7) selection of conformers; (8) generation of QSAR equations by standard statistical techniques. The best model obtained from stepwise regression and GFA techniques shows 51.6% predicted variance (leave-one-out) and 57.3% explained variance. In case of FA-PLS regression, the best relation shows 54.0% predicted variance and 57.9% explained variance. The R(2)(pred) and R(2)(test) values for the GFA derived model are 0.611 and 0.664, respectively, while the best FA-PLS model has R(2)(pred) and R(2)(test) values of 0.602 and 0.656, respectively. These models show the importance of Jurs descriptors (total polar surface area, relative polar surface area, relative hydrophobic surface area, relative positive charge), fraction area of the molecular shadow in the XZ plane (ShadowXZfrac), common overlap steric volume and the ratio of common overlap steric volume to volume of individual molecules. Statistically reliable MSA models obtained from this study suggest that this technique could be useful to design potent HIV-1 integrase inhibitors.

Comparative QSAR modeling of CCR5 receptor binding affinity of substituted 1-(3,3-diphenylpropyl)-piperidinyl amides and ureas

The present QSAR study attempts to explore the structural and physicochemical requirements of substituted 1-(3,3-diphenylpropyl)-piperidinyl amides and ureas for CCR5 binding affinity using linear free energy-related (LFER) model of Hansch. QSAR models have been developed using electronic (Hammett sigma), hydrophobicity (pi), and steric (molar refractivity and STERIMOL L, B1, and B5) parameters of phenyl ring substituents of the compounds along with appropriate dummy variables. Whole molecular descriptor like partition coefficient (logP(calcd)) was also tried as an additional descriptor. Statistical techniques like stepwise regression, multiple linear regression with factor analysis as the data preprocessing step (FA-MLR), partial least squares with factor analysis as the preprocessing step (FA-PLS), principal component regression analysis (PCRA), multiple linear regression with genetic function approximation (GFA-MLR), and genetic partial least squares (G/PLS) were applied to identify the structural and physicochemical requirements for the CCR5 binding affinity. The generated equations were statistically validated using leave-one-out technique. The quality of equations obtained from stepwise regression, FA-MLR, FA-PLS, and PCRA is of acceptable statistical range (explained variance ranging from 71.9% to 80.4%, while predicted variance ranging from 67.4% to 77.0%). The GFA-derived models show high intercorrelation among predictor variables used in the equations while the G/PLS model shows lowest statistical quality among all types of models. The best models were also subjected to leave-25%-out crossvalidation.

QSAR by LFER model of HIV protease inhibitor mannitol derivatives using FA-MLR, PCRA, and PLS techniques

The present quantitative structure-activity relationship (QSAR) study attempts to explore the structural and physicochemical requirements of mannitol derivatives for HIV protease inhibitory activity using linear free energy related model of Hansch. QSAR models have been developed using electronic (Hammett sigma), hydrophobicity (pi), and steric (molar refractivity and STERIMOL L, B1, and B5) parameters of phenyl ring substituents of the compounds along with appropriate dummy variables. Whole molecular descriptors like partition coefficient (logP(calcd)) and molar refractivity (MR) were also tried as additional descriptors. Statistical techniques like stepwise regression, multiple linear regression with factor analysis as the data preprocessing step (FA-MLR), principal component regression analysis (PCRA), and partial least squares (PLS) analysis were applied to identify the structural and physicochemical requirements for HIV protease inhibitory activity. The generated equations were statistically validated using leave-one-out technique. The quality of equations obtained from stepwise, FA-MLR, PCRA, and PLS are of acceptable statistical range (explained variance ranging from 74.0% to 80.5%, while predicted variance ranges from 70.3% to 77.1%). The coefficient of molar refractivity shows that the activity decreases with increase in volume. Lipophilicity of the para substituents at Y position is conducive to the activity while lipophilicity of the para substituents at X position is detrimental to the activity. The coefficients of molar refractivity (mr(Y_p)) and STERIMOL parameters for para substituents at X and Y positions (B1(X_p) and B5(Y_p)) of the phenyl rings indicate that the width of the substituents at X position and the overall size of para substituents at Y position are the detrimental factors for the activity. The fluoro substituent at ortho position (Y) decreases the activity when compared to the corresponding unsubstituted congener. Presence of hydrogen bond donor groups at para position (Y) also reduces the activity. Additionally, presence of substituent at ortho position (X) and the presence of substituent at para position (Y) are conducive for the activity. Presence of fluorine at X and Y positions also increases the activity.

QSAR analyses of 3-(4-benzylpiperidin-1-yl)-N-phenylpropylamine derivatives as potent CCR5 antagonists

CCR5 receptor binding affinity of a series of 3-(4-benzylpiperidin-1-yl)propylamine congeners was subjected to QSAR study using the linear free energy related (LFER) model of Hansch. Appropriate indicator variables encoding different group contributions and different physicochemical variables such as hydrophobicity (pi), electronic (Hammett sigma), and steric (molar refractivity, STERIMOL values) parameters of phenyl ring substituents of the compounds were used as predictor variables. The Hansch analysis explores the importance of the lipophilicity and electron-donating substituents for the binding affinity. However, this method could not give more insight into the structure-activity relationships because of the diverse molecular features in the data set. 3D-QSAR analyses of the same data set using Molecular Shape Analysis (MSA), Receptor Surface Analysis (RSA), and Molecular Field Analysis (MFA) techniques were also performed. The best model with acceptable statistical quality was derived from the MSA, which showed the importance of the relative negative charge (RNCG): substituents with a high RNCG value have more binding affinity than the unsubstituted piperidine and phenyl (R1 position) congeners. The relative negative charge surface area (RNCS) is detrimental (e.g. R2 = 3,4-Cl2) for the activity. An increase in the length of the molecule in the Z dimension (Lz) is conducive (e.g. R3 = sulfonylmorpholino), while an increase in the area of the molecular shadow in the XZ plane (Sxz) is detrimental (e.g. R1 = N-c-hexylmethyl-5-oxopyrrolidin-3-yl) for the binding affinity. The presence of a chiral center makes the molecule less active (e.g. R1 = N-methyl-5-oxopyrrolidin-3-yl). An increase in the van der Waals area, the molecular volume, and the difference between the volume of the individual molecule and the shape reference compound are conducive (e.g. R3 = (CH3)2NSO2-) for the binding affinity. Substituents with higher JursFPSA_2 values (fractional charged partial surface area) like the N-methylsulfonylpiperidin-4-yl (R1 position) group have better binding affinity than the substituents such as 4-chlorophenylamino (R1 position). Unsubstituted piperidines (R1 position) with less JursFNSA_1 values have lower binding affinity than the 4-chlorophenyl substituted compounds. The MFA derived equation shows interaction energies at different grid points, while the RSA model shows the importance of hydrophobicity and charge at different regions of the molecules. The models were validated through the leave-one-out, leave-15%-out, and leave-25%-out cross-validation techniques. The developed models were also subjected to a randomization test (99% confidence level). Although the MSA derived models had excellent statistical qualities both for the training as well as test sets, RSA and MFA results for the test sets are not comparable statistically with the MSA derived models.

QSAR by LFER model of cytotoxicity data of anti-HIV 5-phenyl-1-phenylamino-1H-imidazole derivatives using principal component factor analysis and genetic function approximation

Cytotoxicity data of anti-HIV 5-phenyl-1-phenylamino-1H-imidazole derivatives were subjected to quantitative structure-activity relationship (QSAR) study using linear free energy related (LFER) model of Hansch using electronic (Hammett sigma), hydrophobicity (pi) and steric (molar refractivity and STERIMOL L, B1, B2, B3 and B4) parameters of phenyl ring substituents of the compounds, along with appropriate indicator variables. Principal component factor analysis (FA) was used as the data-preprocessing step to identify the important predictor variables contributing to the response variable and to avoid collinearities among them. The generated multiple linear regression (MLR) equations were statistically validated using leave-one-out technique. Genetic function approximation (GFA) was also used on the same data set to develop QSAR equations, which produced the same best equation as obtained with FA-MLR. The final equation is of acceptable statistical quality (explained variance 80.2%) and predictive potential (leave-one-out predicted variance 74%). The analysis explores the structural and physicochemical contributions of the compounds for cytotoxicity. A thiol substituent at 2 position of the imidazole nucleus decreases cytotoxicity when compared to the corresponding unsubstituted congener. Presence of hydrogen bond donor group at meta position of the phenyl ring present at 5 position of the imidazole nucleus also reduces cytotoxicity. Additionally, absence of any substituent at 2 and 3 positions of the phenyl ring of 1-phenylamino fragment reduces the cytotoxicity. The negative coefficient of sigmap indicates that presence of electron-withdrawing substituents at the para position of the phenyl ring of the 1-phenylamino fragment is not favourable for the cytotoxicity. Again, lipophilicity of meta substituents of the 5-phenyl ring increases cytotoxicity. The coefficients of molar refractivity (MRm) and STERIMOL parameters for meta substituents (Lm, B1m and B4m) of the phenyl ring of 1-phenylamino fragment indicate that the length, width and overall size of meta substituents are conducive factors for the cytotoxicity.