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.

Considering the potential of peripheral benzodiazepine receptor (PBR) ligands in therapeutic applications and clinical benefit in the management of a large spectrum of different indications, quantitative structure-activity relationship (QSAR) study has been attempted to explore the structural and physicochemical requirements for selectivity of 2-phenylimidazo[1,2-a]pyridineacetamides for binding with peripheral over central benzodiazepine receptors (CBRs). For PBR binding affinity, molar refractivity (MR) shows a parabolic relation with binding affinity suggesting that binding affinity increases with increase in volume of the compounds, until it reaches the critical value, after which the affinity decreases. The negative coefficients of S_aaN and S_ssNH indicate that binding affinity increases with decrease in E-state value of (N/)(aromatic nitrogen) and HN<(secondary amino group) fragments. The coefficient of 3XVC and JX term indicates the importance of shape and branching for binding affinity. For CBR binding affinity, lipophilicity of molecules is detrimental to the binding affinity, while presence of hydrogen at Y position is conducive to the activity. Selectivity pattern of these ligands for peripheral (cortex) over central receptors requires the presence and absence of methyl group at R2 and R3 positions respectively, and shows the importance of MR and shape parameter. Similarly, selectivity of these ligands for peripheral (ovary) over central receptors requires the presence and absence of methyl group at R2 and R3 positions respectively, presence of phenyl group at R1 and R2 positions and selectivity relation shows importance of MR, shape and branching.

The new generation of antiviral drugs intended to counter HIV-1 entry into susceptible cells is emerging swiftly. The antiviral agents that inhibit HIV entry to the target cells (denoted as HIV entry inhibitors) are already in different phases of clinical trials. Operating early in the viral life cycle, they prevent viral entry, and have a novel, highly specific mechanism of action with a low toxicity profile. Entry inhibitors have different toxicity and resistance profiles than the existing reverse transcriptase and protease inhibitors. Some of these compounds demonstrated in vitro synergism with other classes of antivirals, thus offering the rationale for their combination in therapies for HIV-infected individuals. It is worth focusing on recent developments in HIV entry inhibitors, as most of the current drug regimens suffer from the events of developing resistance against existing combination therapies. Recent advances in the understanding of the cellular and molecular mechanisms of HIV-1 entry provide the basis for novel therapeutic strategies that prevent viral penetration of the target cell-membrane, while reducing detrimental virus and treatment effects on cells and prolonging virion exposure to immune defenses. A number of potential sites for therapeutic intervention become accessible during the narrow window between virus attachment and the subsequent fusion of viral envelope with the cell membrane. The HIV-1 coreceptors are particularly attractive from the perspective of identifying new antiviral compounds, since they are seven-transmembrane motif G protein-coupled receptors (GPCRs), a family of proteins that is a well-validated target for drug development. Among the many chemokine receptors that can mediate HIV-1 entry in vitro, only CCR5 and CXCR4 are of frontline pharmacological importance. In particular, CCR5 is essential for viral transmission and replication during the early and clinically latent phase of disease. Several small-molecule antagonists of CCR5 and CXCR4 that block chemokine binding and HIV-1 entry have been identified in recent years. Considerable advances have been made in the last years in the design of derivatives acting as inhibitors of HIV entry. The molecular mechanism involved in viral entry, the structural and functional aspects of entry inhibitors are reviewed here. We have also summarized the recent insights into how small-molecule antagonists interact with CCR5 and CXCR4, focusing on drug development programs that are well documented in the scientific literature. An overview of the entry inhibitors that are in preclinical or early clinical development, and the Quantitative Structure-Activity Relationships (QSAR) studies reported for the coreceptor antagonists are also be presented.

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.

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.

Binding affinity data [Bioorg Med Chem (2004) 12:613-623] of thiazole and thiadiazole derivatives (n = 30) for the human adenosine A(3) receptor subtype have been subjected to 3D-QSAR (Quantitative structure-activity relationships) analyses by molecular shape analysis (MSA) and molecular field analysis (MFA) techniques using Cerius2 Version 4.8. In the case of the MSA, 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 the active conformation);(4) performing pairwise molecular superimposition using the maximum common subgroup (MCSG) method;(5) measuring molecular shape commonality using MSA descriptors;(6) determining other molecular features by calculating spatial, electronic and conformational parameters;(7) selection of conformers;(8) generation of QSAR equations by genetic function algorithm (GFA) or stepwise regression. The best 3D-QSAR equation (MSA) obtained from GFA technique shows 70.0% predicted variance (leave-one-out) and 77.7% explained variance. This equation shows the importance of Jurs descriptors (atomic charge weighted positive surface area, relative negative charge and relative positive charge surface area), partial moment of inertia, energy of the most stable conformer and the ratio of common overlap steric volume to volume of individual molecules. In the case of stepwise regression, the best relation showed 46.1% predicted variance and 72.3% explained variance. In the case of MFA, the major steps were (1) generating conformers and energy minimization;(2) matching atoms using a maximum common substructure (MCS) search and aligning molecules using the default options;(3) setting MFA preferences (rectangular grid with 2 A step size, charges by the Gasteiger algorithm, H(+) and CH(3) as probes);(4) creating the field;(5) analysis by the Genetic partial least squares (G/PLS) method. The equation obtained was of excellent statistical quality: 96.1% explained variance and 71.6% predicted variance. Statistically reliable 3D-QSAR models obtained from this study suggest that these techniques could be useful to design potent A(3) receptor antagonists. Figure Adenosine A3 binding affinity data of thiazole and thiadiazole derivatives have been subjected to 3D-QSAR study using molecular shape analysis and molecular field analysis.

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.

Binding affinity data of thiazole and thiadiazole derivatives (n=30) for human adenosine A3 receptor subtype have been subjected to Quantitative Structure-Activity Relationship (QSAR) analysis using quantum chemical and hydrophobicity parameters. Wang-Ford charges of the common atoms of the compounds [calculated from molecular electrostatic potential surface of energy minimized geometry using Austin Model 1 (AM1) technique] were used as independent variables apart from partition coefficient (logP) and suitable dummy parameters. The variables for the multiple regression analyses were selected based on principal component factor analysis (FA), and generated equations were statistically validated using leave-one-out technique. The best equation thus obtained explained and predicted 74.4% and 68.9% respectively of the variance of the binding affinity. The results suggested importance of Wang-Ford charges of atoms C2, C5 and C7. Furthermore, the A3 binding affinity increases with decrease of lipophilicity of the compounds and in the presence of methyl or ethyl substituent at R position. Again, the binding affinity decreases in the presence of tert-butyloxy group at R position. When factor scores were used as predictor variables in principal component regression analysis, the resulted model showed 87.0% predicted variance and 89.5% explained variance. The data set was also modeled using genetic function approximation (GFA) technique. The best two equations derived from GFA show better predicted variance values (0.753 and 0.739) than that found in case of the best equation derived from FA. However, considerable intercorrelation was found between two predictor variables in case of GFA derived equations. GFA derived equations show importance of Wang-Ford charges of different atoms of the thiazole/thiadiazole nucleus and phenyl ring (S9, X8 and C2, the effects of the first two being predominant) along with similar impact of lipophilicity and R group on the binding affinity as found in case of the FA derived relation.

Three series of anti-HIV data (reverse transcriptase inhibitory activity, cytopathicity data, and cytotoxicity data) of alkenyldiarylmethanes were modeled with physicochemical, topological and structural descriptors by multiple regression analysis using principal component factor analysis as the data pre-processing step. Molar refractivity was found to be a significant contributor in modeling all three data sets. Apart from this, partition coefficient, E-state index, valence connectivity and indicator parameters were important in modeling different activity series. The final relations were of moderate to good quality as evidenced from regression statistics (R2 values ranging 66-75%) and leave-one-out cross validation data (Q2 values ranging 54-70%).

A series of 8-substituted quinolines were synthesized and tested against seizures induced by maximal electro shock (MES), pentylenetetrazole (scMet) and antihypertensive activities. Neurologic deficit was evaluated by the rotarod test. Among the newly synthesized derivatives, several compounds with a 2-hydroxypropyloxyquinoline moiety displayed excellent anticonvulsant and antihypertensive activities. Compound 20 (8-(3'-(4''-phenylpiperazino)-2'-hydroxypropyloxy)quinoline) was potent in both series as an anticonvulsive agent. 13 (8-(3'-piperazino)-2'-hydroxypropyloxyquinoline) and 14 (8-(3'-imidazolo)-2'-hydroxypropyloxyquinoline) showed very good anticonvulsant activities in the propanol series of compound, whereas in the ethane series, 1 (8-(2'-piperazino-ethanoxy)quinoline) and 2 (8-(2'-imidazolo-ethanoxy)quinoline) were the most active as anticonvulsive agents. Compounds 20 (8-(3'-(4''-phenylpiperazino)-2'-hydroxypropyloxy)quinoline), 13 (8-(3'-piperazino)-2'-hydroxypropyloxyquinoline) and 19 (8-(3'-(4''-ethylpiperazino)-2'-hydroxypropyloxy)quinoline) have shown excellent antihypertensive activity. They have significantly antagonized the pressor response elicited by adrenaline. These pharmacological results suggest that their anticonvulsant and antihypertensive effects may be correlated to the presence of beta-blocking properties, and that those properties depend on the presence of aryloxypropanolamine.