In normal functioning of the cell, there is a balance between generation and neutralization of reactive oxygen species (ROS) by endogenous cellular defense machinery. Low levels of ROS inside the cells are required for normal functioning of the cell, which regulate signaling mechanisms involved in mitosis and apoptosis; excess of ROS production may cause oxidative stress leading to damage in vital cellular molecules, namely cytosolic lipids, proteins, and DNA. In the situation of intracellular redox imbalance, molecules of cells are altered by ROS leading to pathogenic state. It is to be noted that ROS is not only known to be involved in tumor induction and progression processes but also enhances tumor cell radiosensitivity. The level of ROS-mediated oxidative stress is linked to cellular radiosensitivity. In general, cancer cells exhibit high levels of ROS, which forms a target for selectively killing them by radiation. In this paper, we have reviewed how oxidative stress determines the radiosensitivity of tumor cells involving ROS in the mechanism of radiation induced tumor cell killing. It is suggested that radiation-induced ROS play a key role in the mechanism of tumor cell killing by altering the signaling network and triggering of apoptosis. Furthermore, it is pointed out that combined use of plant-derived antioxidants and radiation enhance overproduction of ROS in tumor cells leading to enhanced radiosensitivity, which may find practical applications in clinic.
A combined ligand and structure-based drug design approach provides a synergistic advantage over either methods performed individually. Present work bestows a good assembly of ligand and structure-based pharmacophore generation concept. Ligand-oriented study was accomplished by employing the HypoGen module of Catalyst in which we have translated the experimental findings into 3-D pharmacophore models by identifying key features (four point pharmacophore) necessary for interaction of the inhibitors with the active site of HIV-1 protease enzyme using a training set of 33 compounds belonging to the cyclic cyanoguanidines and cyclic urea derivatives. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, two hydrogen bond acceptors and two hydrophobic, showed a correlation (r) of 0.90 and a root mean square of 0.71 and cost difference of 56.59 bits between null cost and fixed cost. The model was validated using CatScramble technique, internal and external test set prediction. In the second phase of our study, a structure-based five feature pharmacophore hypothesis was generated which signifies the importance of hydrogen bond donor, hydrogen bond acceptors and hydrophobic interaction between the HIV-1 protease enzyme and its inhibitors. This work has taken a significant step towards the full integration of ligand and structure-based drug design methodologies as pharmacophoric features retrieved from structure-based strategy complemented the features from ligand-based study hence proving the accuracy of the developed models. The ligand-based pharmacophore model was used in virtual screening of Maybridge and NCI compound database resulting in the identification of four structurally diverse druggable compounds with nM activities.
Topoisomerase I (TOP I) is a valuable molecular target for the development of clinically used anticancer agents. Indenoisoquinolines have emerged as potent topoisomerase I inhibitors. So, with an aim to elucidate the important features responsible for their activity, QSAR studies on breast cancer cell line using stepwise multiple linear regressions, partial least square, and neural network were performed. The MLR and PLS models showed good correlation values of 2 = 0.932, 2 cv = 0.897, and 2 = 0.932, 2 cv = 0.913 respectively. The model revealed the importance of steric arrangement of functional groups and number of H bond acceptors. In addition to MLR and PLS, neural network architecture was also constructed using selected descriptors and the inhibitory activities in order to evaluate the mode of dependencies of biological activity on obtained descriptors.
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