Hemant Kumar Srivastava

Quinazolinone linked pyrrolo[2,1-c][1,4]benzodiazepine (PBD) conjugates: Design, synthesis and biological evaluation as potential anticancer agents

A series of novel quinazolinone linked pyrrolobenzodiazepine (PBD) conjugates were synthesized. These compounds 4a-f and 5a-f were prepared in good yields by linking C-8 of DC-81 with quinazolinone moiety through different alkane spacers. These conjugates were tested for anticancer activity against 11 human cancer cell lines and found to be very potent anticancer agents with GI(50) values in the range of <0.1-26.2microM. Among all the PBD conjugates, one of the conjugate 5c was tested against a panel of 60 human cancer cells. This compound showed activity for individual cancer cell lines with GI(50) values of <0.1microM. The thermal denaturation studies exhibited effective DNA binding ability compared to DC-81 and these results are further supported by molecular modeling studies. The detailed biological aspects of these conjugates on A375 cell line were studied. It was observed that compounds 4b and 5c induced the release of cytochrome c, activation of caspase-3, cleavage of PARP and subsequent cell death. Further, these compounds when treated with A375 cells showed the characteristic features of apoptosis like enhancement in the levels of p53, p21 and p27 inhibition of cyclin dependent kinase-2 (CDK2) and suppression of NF-kappaB. Moreover, these two compounds 4b and 5c control the cell proliferation by regulating anti-apoptotic genes like (B-cell lymphoma 2) Bcl-2. Therefore, the data generated suggests that these PBD conjugates activate p53 and inhibit NF-kappaB and thereby these compounds could be promising anticancer agents with better therapeutic potential for the suppression of tumours.

Comparison of computational methods to model DNA minor groove binders.

There has been a profound interest in designing small molecules that interact in sequence-selective fashion with DNA minor grooves. However, most in silico approaches have not been parametrized for DNA ligand interaction. In this regard, a systematic computational analysis of 57 available PDB structures of noncovalent DNA minor groove binders has been undertaken. The study starts with a rigorous benchmarking of GOLD, GLIDE, CDOCKER, and AUTODOCK docking protocols followed by developing QSSR models and finally molecular dynamics simulations. In GOLD and GLIDE, the orientation of the best score pose is closer to the lowest rmsd pose, and the deviation in the conformation of various poses is also smaller compared to other docking protocols. Efficient QSSR models were developed with constitutional, topological, and quantum chemical descriptors on the basis of B3LYP/6-31G* optimized geometries, and with this ΔT(m) values of 46 ligands were predicted. Molecular dynamics simulations of the 14 DNA-ligand complexes with Amber 8.0 show that the complexes are stable in aqueous conditions and do not undergo noticeable fluctuations during the 5 ns production run, with respect to their initial placement in the minor groove region.

Molecular Dynamics Investigation on a Series of HIV Protease Inhibitors: Assessing the Performance of MM-PBSA and MM-GBSA Approaches

The binding free energies (ΔG(Bind)) obtained from molecular mechanics with Poisson-Boltzmann surface area (MM-PBSA) or molecular mechanics with Generalized Born surface area (MM-GBSA) calculations using molecular dynamics (MD) trajectories are the most popular procedures to measure the strength of interactions between a ligand and its receptor. Several attempts have been made to correlate the ΔG(Bind) and experimental IC(50) values in order to observe the relationship between binding strength of a ligand (with its receptor) and its inhibitory activity. The duration of MD simulations seems very important for getting acceptable correlation. Here, we are presenting a systematic study to estimate the reasonable MD simulation time for acceptable correlation between ΔG(Bind) and experimental IC(50) values. A comparison between MM-PBSA and MM-GBSA approaches is also presented at various time scales. MD simulations (10 ns) for 14 HIV protease inhibitors have been carried out by using the Amber program. MM-PBSA/GBSA based ΔG(Bind) have been calculated and correlated with experimental IC(50) values at different time scales (0-1 to 0-10 ns). This study clearly demonstrates that the MM-PBSA based ΔG(Bind) (ΔG(Bind)-PB) values provide very good correlation with experimental IC(50) values (quantitative and qualitative) when MD simulation is carried out for a longer time; however, MM-GBSA based ΔG(Bind) (ΔG(Bind)-GB) values show acceptable correlation for shorter time of simulation also. The accuracy of ΔG(Bind)-PB increases and ΔG(Bind)-GB remains almost constant with the increasing time of simulation.

Viability of Clathrate Hydrates as CO2 Capturing Agents: A Theoretical Study

Capture and sequestration of green house gas CO(2) is a major challenge for scientists and identifying right materials for this purpose is a task of outstanding importance. Through reliable computational studies, we have demonstrated that the clathrate cages (5(12), 4(3)5(6)6(3), 5(12)6(2), 5(12)6(4), and 5(12)6(8)) have a great potential to store CO(2). All the considered clathrates and their CO(2) inclusion complexes are optimized at B3LYP/6-31G(d) level of theory. The impact of DFT-D, M05-2X, and MP2 functionals on interaction energy were tested using various basis sets. Although different functionals and basis sets show variation in absolute IE values, the trend is consistent and does not depend on the level of the calculations. Dispersion was found important for these complexes and DFT-D shows comparable IE values with MP2 functional. The optimum and maximum cage occupancy for all the considered cages were tested on the basis of quantum chemical calculations. The maximum cage occupancy for all five considered cages (5(12), 4(3)5(6)6(3), 5(12)6(2), 5(12)6(4), and 5(12)6(8)) is one, two, two, two, and seven CO(2) molecules, respectively, and the optimum cage occupancy is one, one, one, two, and five CO(2) molecules, respectively. Thus, 5(12)6(8) cages can host up to 7 CO(2) molecules, resulting in about 32 wt %, which makes them highly promising materials.

Analogue-based approaches in anti-cancer compound modelling: the relevance of QSAR models.

Background QSAR is among the most extensively used computational methodology for analogue-based design. The application of various descriptor classes like quantum chemical, molecular mechanics, conceptual density functional theory (DFT)- and docking-based descriptors for predicting anti-cancer activity is well known. Although in vitro assay for anti-cancer activity is available against many different cell lines, most of the computational studies are carried out targeting insufficient number of cell lines. Hence, statistically robust and extensive QSAR studies against 29 different cancer cell lines and its comparative account, has been carried out. Results The predictive models were built for 266 compounds with experimental data against 29 different cancer cell lines, employing independent and least number of descriptors. Robust statistical analysis shows a high correlation, cross-validation coefficient values, and provides a range of QSAR equations. Comparative performance of each class of descriptors was carried out and the effect of number of descriptors (1-10) on statistical parameters was tested. Charge-based descriptors were found in 20 out of 39 models (approx. 50%), valency-based descriptor in 14 (approx. 36%) and bond order-based descriptor in 11 (approx. 28%) in comparison to other descriptors. The use of conceptual DFT descriptors does not improve the statistical quality of the models in most cases. Conclusion Analysis is done with various models where the number of descriptors is increased from 1 to 10; it is interesting to note that in most cases 3 descriptor-based models are adequate. The study reveals that quantum chemical descriptors are the most important class of descriptors in modelling these series of compounds followed by electrostatic, constitutional, geometrical, topological and conceptual DFT descriptors. Cell lines in nasopharyngeal (2) cancer average R2 = 0.90 followed by cell lines in melanoma cancer (4) with average R2 = 0.81 gave the best statistical values.

Energy decomposition analysis of cation–π, metal ion–lone pair, hydrogen bonded, charge-assisted hydrogen bonded, and π–π interactions

This study probes the nature of noncovalent interactions, such as cation–π, metal ion–lone pair (M–LP), hydrogen bonding (HB), charge‐assisted hydrogen bonding (CAHB), and π–π interactions, using energy decomposition schemes—density functional theory (DFT)–symmetry‐adapted perturbation theory and reduced variational space. Among cation–π complexes, the polarization and electrostatic components are the major contributors to the interaction energy (IE) for metal ion–π complexes, while for onium ion–π complexes ( NH4+ , PH4+ , OH3+ , and SH3+ ) the dispersion component is prominent. For M–LP complexes, the electrostatic component contributes more to the IE except the dicationic metal ion complexes with H2S and PH3 where the polarization component dominates. Although electrostatic component dominates for the HB and CAHB complexes, dispersion is predominant in π–π complexes.Copyright

Modeling Anti-HIV Compounds: The Role of Analogue-Based Approaches

There has been a tremendous progress in the development of anti-HIV therapies since the discovery of the HIV virus. Computer aided drug design in general and analogue-based approaches in particular have played an important role in the process of HIV drug discovery. Structure-based approaches also have played a vital role in this process. There are a large number of studies reported in the literature where QSAR methodology was employed to study the structural requirements for inhibition against various HIV targets like reverse transcriptase, protease, entry and integrase. The current review focuses on those studies and provides a detailed description on the QSAR methodology, descriptors, statistical significance and important findings. This review categorizes the reported QSAR studies on the basis of chemical scaffolds against a particular target. In reverse transcriptase category, QSAR studies on HEPT, TIBO, DABO, DAPY, DATA, AASBN, pyridone and DATZD derivatives have been reviewed. Cyclic urea, fullerene, AHPBA and dihydropyrone derivatives were considered in protease inhibitors category. In addition, QSAR studies on styrylquinoline, carboxylic acid, MBSA and chalcone derivatives were reviewed in integrase inhibitors category. QSAR studies on entry inhibitors like piperidine, benzyl piperidine, benzyl pyrazole, pyrrole and diazepane urea have also been reviewed.

Efficient estimation of MMGBSA-based BEs for DNA and aromatic furan amidino derivatives

Molecular mechanics with Generalized Born surface area (MMGBSA) based binding energies (BEs) derived from the molecular dynamics (MD) trajectories are highly reliable and extensively used standards to estimate the strength of interactions between ligands and their receptor. MD simulations (5 ns) for 30 aromatic furan aminidino derivatives (anti-Pneumocystis carnii agents) have been carried out by using Amber program and BEs have been calculated by using Generalized Born (GB) method. Based on the generated data, we present a simple and effective method for the approximation of BEs without performing MD simulations and MMGBSA calculations. Quantum chemical (density functional theory based) and geometrical descriptors are used for the prediction of the BE values. All the developed models are statistically significant with high values of correlation and cross-validation coefficients. The prediction ability and effectiveness of the models are tested by the division of the data-set into four different training and test sets and the average error was only 4–7% (1.56–2.61 kcal/mol) of the actual BEs.

The efficacy of conceptual DFT descriptors and docking scores on the QSAR models of HIV protease inhibitors.

This study critically examines the role of conceptual DFT descriptors and docking scores on a diverse set of 156 inhibitors of HIV proteases. Five QSAR models were developed on the basis of available experimental IC(50) values (HIV-I and HIV-IIIB infected MT4 and CEMSS cells and HIV-I infected C8166 cells) and sixth QSAR model was generated by combining the inhibitors of all five models. B3LYP/6-31G(d) optimizations were carried out on all considered inhibitors, and the results are compared with more economic semi-empirical SCF AM1 results in order to find out the best and efficient way of descriptor calculations. Interestingly semi-empirical results appear to be satisfactory for this class of inhibitors. Selected QSAR models were validated by taking about 20% of inhibitors in the test sets. The effect of the number of descriptors on the R(2) and R(2)(cv) values was tested and three to four orthogonal descriptors based models were selected to be the optimum ones to avoid over correlation.