Study of DNA base-Li doped SiC nanotubes in aqueous solutions: a computer simulation study

Study of folate-based carbon nanotube drug delivery systems targeted to folate receptor α by molecular dynamic simulations

We designed targeted drug delivery systems containing folate (FOL), the functionalized carbon nanotube (f-CNT) and doxorubicin (DOX), and studied the targeting properties of folate, f-CNT-FOL and DOX/f-CNT-FOL to folate receptor α (FRα). Folate was actively targeted to FRα in molecular dynamics simulations, and the dynamic process, effect of folate receptor evolution, and characteristics were analyzed. On this basis, the f-CNT-FOL and DOX/f-CNT-FOL nano-drug-carrier systems were designed, and the drug delivery process targeted to FRα was studied by 4 times MD simulations. The system evolution and detailed interactions of f-CNT-FOL and DOX/f-CNT-FOL with FRα residues were examined. We found that though the connection of CNT with the FOL could decrease the insertion depth of the pterin of FOL into the pocket of FRα, the loading of drug molecules could reduce this effect. Representative snapshots from the MD simulations were analyzed, showing that the location of DOX on the surface of CNT was constantly changed during the MD simulation, but the surface of the four rings of DOX were almost always parallel to the surface of CNT. The RMSD and RMSF were used to further analyze. The results may provide new insights for the design of novel targeted nano-drug-delivery systems.

DFT based QSAR study on quinolone-triazole derivatives as antibacterial agents

QSAR modeling was performed on 39 quinolone-triazole derivatives against gram-positive Staphylococcus aureus and gram-negative Pseudomonas aeruginosa bacteria. The molecular structures were optimized using the DFT/B3LYP method and 6-31 G basis set. Molecular descriptors were extracted using quantum mechanical calculations. The hierarchical cluster analysis was performed for a rational subset division. The initial dataset was divided into calibration and validation sets, and modeling was done by stepwise MLR method for each of the two bacteria. Internal and external validation methods confirmed the robustness and predictability of the obtained models. According to the obtained model for S. aureus (R² = 0.889, R²_ext = 0.938, Q²_LOO = 0.853), the four descriptors- partial atomic charges for the N1 atom in triazole and C7 of the quinolone nucleus, 4-carbonyl bond length, and ¹³C-NMR chemical shift of 3-carboxylic acid- were found to be the descriptors controlling the activity. According to the obtained model for P. aeruginosa (R² = 0.957, R²_ext = 0.923, Q²_LOO = 0.909), the O atom's partial charge in carbonyl, LUMO-HOMO energy gap, and logP were found to be the descriptors having the highest correlation with the antibacterial activity. Finally, some new compounds with higher activities were designed and proposed.