Search PubMed⌕ Search

Biomedical subjects

Z R Li

Publications and source records attributed to Z R Li.

At least 55 records · Page 3Linked to original sources
PubMed1983

Effect of 3-deazauridine on the metabolism, toxicity, and antitumor activity of azacitidine in mice bearing L1210 leukemia sensitive and resistant to cytarabine.

The effect of 3-deazauridine (DAUR) on the intracellular purine and pyrimidine nucleotide pools and on the metabolism of azacitidine (aza-CR) in L1210 cells, sensitive (L1210/0) and resistant (L1210/ara-C) to cytarabine (ara-C), was examined. The consequences of such a modulation were correlated with the therapeutic efficacy of this combination in mice bearing L1210 leukemia. In vitro and in vivo treatment of both L1210 sublines with DAUR produced a dose- and time-dependent reduction in the CTP and dCTP pools and an increase in the UTP pool. In addition to these changes in the pyrimidine nucleotide pools, DAUR produced a modest increase in the GTP pool and a marked expansion of the ATP pool in L1210/ara-C 12 hrs following in vivo drug treatment. These perturbations in nucleoside triphosphate pools were more pronounced in L1210/ara-C cells. Treatment of mice bearing L1210/ara-C with 100 mg/kg of DAUR reduced the CTP and dCTP pools in the leukemic cells by greater than 90% within 1-3 hrs after administration of the drug, with complete recovery of these pools occurring within 12 hrs. Fluctuation of the pyrimidine nucleoside pools after DAUR treatment was correlated with the subsequent increase in aza-CR metabolism and its incorporation into RNA and with the potentiation of the in vivo toxicity of aza-CR. In mice bearing L1210/0 or L1210/ara-C tumors, DAUR or aza-CR produced a less than or equal to 23% increase in life-span (ILS). Administration of aza-CR 3 hrs after DAUR, however, produced about an 80% ILS among mice bearing L1210/ara-C tumors, but no more than an approximately 20% ILS among mice bearing L1210/0 tumors. These data suggest that the therapeutic activity of the sequential combination of DAUR and aza-CR against mice bearing L1210/ara-C cannot be explained, per se, on the basis of the initial intracellular modulation of nucleotide pools, since DAUR affected these pools of the two tumors to approximately the same degree. What appears to be important, however, is that such a modulation by DAUR preferentially affected the metabolism of aza-CR in leukemic cells resistant to ara-C which are devoid of deoxycytidine kinase activity.

3-Deazauridine↗
PubMed1983

Inhibition of DNA polymerase-alpha from rat hepatoma with a series of new synthetic polynucleotides.

In continuation of efforts to correlate the antitemplate activities of chemically modified polynucleotides with their base composition and structure, four synthetic copolymers, poly(A,C), poly(C,U), poly(A,C,U), and poly(A,C,G) were modified by thiolation of 2.6-4.8% of their pyrimidine bases. The resulting 5-mercaptoheteropolynucleotides and the previously described 5-mercapto-polycytidylate (MPC) and -polyuridylate (MPU) were tested in a comparative manner as inhibitors of the DNA polymerase-alpha from rat hepatoma. A wide scale of inhibitory potencies was obtained in the following (decreasing) order: MPU greater than M-poly(A,C,U) greater than M-poly(C,U) greater than MPC greater than M-poly(A,C) greater than or equal to M-poly(A,C,G). The sensitivity of the hepatoma DNA polymerase toward these antitemplates increased upon further purification of the enzyme through the DNA-agarose step. Partially thiolated DNA-isolates from rat hepatoma and calf thymus, respectively, showed significant inhibition of the hepatoma DNA polymerase, the thiolated hepatoma DNA being the more active inhibitor.

Animals↗
PubMedDate not supplied

Effect of molecular descriptor feature selection in support vector machine classification of pharmacokinetic and toxicological properties of chemical agents.

Statistical-learning methods have been developed for facilitating the prediction of pharmacokinetic and toxicological properties of chemical agents. These methods employ a variety of molecular descriptors to characterize structural and physicochemical properties of molecules. Some of these descriptors are specifically designed for the study of a particular type of properties or agents, and their use for other properties or agents might generate noise and affect the prediction accuracy of a statistical learning system. This work examines to what extent the reduction of this noise can improve the prediction accuracy of a statistical learning system. A feature selection method, recursive feature elimination (RFE), is used to automatically select molecular descriptors for support vector machines (SVM) prediction of P-glycoprotein substrates (P-gp), human intestinal absorption of molecules (HIA), and agents that cause torsades de pointes (TdP), a rare but serious side effect. RFE significantly reduces the number of descriptors for each of these properties thereby increasing the computational speed for their classification. The SVM prediction accuracies of P-gp and HIA are substantially increased and that of TdP remains unchanged by RFE. These prediction accuracies are comparable to those of earlier studies derived from a selective set of descriptors. Our study suggests that molecular feature selection is useful for improving the speed and, in some cases, the accuracy of statistical learning methods for the prediction of pharmacokinetic and toxicological properties of chemical agents.

Algorithms↗
PubMedDate not supplied

PEARLS: program for energetic analysis of receptor-ligand system.

Analysis of the energetics of small molecule ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions facilitates the quantitative understanding of molecular interactions that regulate the function and conformation of proteins. It has also been extensively used for ranking potential new ligands in virtual drug screening. We developed a Web-based software, PEARLS (Program for Energetic Analysis of Ligand-Receptor Systems), for computing interaction energies of ligand-protein, ligand-nucleic acid, protein-nucleic acid, and ligand-protein-nucleic acid complexes from their 3D structures. AMBER molecular force field, Morse potential, and empirical energy functions are used to compute the van der Waals, electrostatic, hydrogen bond, metal-ligand bonding, and water-mediated hydrogen bond energies between the binding molecules. The change in the solvation free energy of molecular binding is estimated by using an empirical solvation free energy model. Contribution from ligand conformational entropy change is also estimated by a simple model. The computed free energy for a number of PDB ligand-receptor complexes were studied and compared to experimental binding affinity. A substantial degree of correlation between the computed free energy and experimental binding affinity was found, which suggests that PEARLS may be useful in facilitating energetic analysis of ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions. PEARLS can be accessed at http://ang.cz3.nus.edu.sg/cgi-bin/prog/rune.pl.

Computer Simulation↗