Molecular structure-activity relationship study of some non-steroidal antiinflammatory agents using electrostatic potential mapping

A series of 6,11-dihydro-11-oxodibenz[b,e]oxepin-2-acetic acids (DOAA) which are known to be anti-inflammatory agents were studied. The geometries of some of the molecules obtained from X-ray crystallography were used in the calculations as such while the geometries of their derivatives were obtained by local, partial geometry optimization around the Sites of substitution employing the AMI method, keeping the remaining parts of the geometries the same as those in the parent molecules. Molecular electrostatic potential (MEP) mapping was performed for the molecules using optimized hybridization displacement charges (HDC) combined with Lowdin charges, as this charge distribution has been shown earlier to yield near ab initio quality results. A good correlation has been found between the MEP values near the oxygen atoms of the hydroxyl groups of the carboxy groups of the molecules and their anti-inflammatory activities. The result is broadly in agreement with the model proposed earlier by other authors regarding the structure-activity relationship for other similar molecules.

Copper(I) complexes of modified nucleobases and vitamin B3 as potential chemotherapeutic agents: In vitro and in vivo studies

Three new complexes of Cu(I) have been synthesized using ancillary ligands like thiopyrimidine (tp) a modified nucleobase, and nicotinamide (nie) or vitamin B3, and characterized by spectroscopy and X-ray crystallography. In vitro cytotoxicity studies of the complexes on various human cancer cell lines such as Colo295, H226, HOP62, K562, MCF7 and T24 show that Cu(PPh3)(2)(tp)Cl] and Cu(PPh3)(2)(tp)ClO4 (2) have in vitro cytotoxicity comparable to cisplatin. Complex Cu(nic)(3)PPh3]ClO4 (3) is non-toxic and increases the life span by about 55 % in spontaneous breast tumor model. DNA binding and cleavage studies show that complex (3) binds to calf thymus DNA with an apparent binding constant of 5.9 x 10(5)M and completely cleaves super-coiled DNA at a concentration of 400 mu M, whereas complexes (1) and (2) do not bind DNA and do not show any cleavage even at 1200 mu M. Thus, complex (3) may exhibit cytotoxicity Via DNA cleavage whereas the mechanism of cytotoxicity of (1) and (2) probably involves a different pathway.

A sharable instructable agent for information filtering

In this paper we present an information filtering agent called sharable instructable information filtering agent (SIIFA). It adopted the approach of sharable instructable agents. SIIFA provides comprehensible and flexible interaction to represent and filter the documents. The representation scheme in SIIFA is personalized. It, either fully or partly, can be shared among the users of the stream while not revealing their interests and can be easily edited. SIIFA is evaluated on the comp.ai.neural-nets Usent newsgroup documents and compared with the vector space method.

Forming Networks of Strategic Agents with Desired Topologies

Many networks such as social networks and organizational networks in global companies consist of self-interested agents. The topology of these networks often plays a crucial role in important tasks such as information diffusion and information extraction. Consequently, growing a stable network having a certain topology is of interest. Motivated by this, we study the following important problem: given a certain desired network topology, under what conditions would best response (link addition/deletion) strategies played by self-interested agents lead to formation of a stable network having that topology. We study this interesting reverse engineering problem by proposing a natural model of recursive network formation and a utility model that captures many key features. Based on this model, we analyze relevant network topologies and derive a set of sufficient conditions under which these topologies emerge as pairwise stable networks, wherein no node wants to delete any of its links and no two nodes would want to create a link between them.

Sufficient conditions for formation of a network topology by self-interested agents

Networks such as organizational network of a global company play an important role in a variety of knowledge management and information diffusion tasks. The nodes in these networks correspond to individuals who are self-interested. The topology of these networks often plays a crucial role in deciding the ease and speed with which certain tasks can be accomplished using these networks. Consequently, growing a stable network having a certain topology is of interest. Motivated by this, we study the following important problem: given a certain desired network topology, under what conditions would best response (link addition/deletion) strategies played by self-interested agents lead to formation of a pairwise stable network with only that topology. We study this interesting reverse engineering problem by proposing a natural model of recursive network formation. In this model, nodes enter the network sequentially and the utility of a node captures principal determinants of network formation, namely (1) benefits from immediate neighbors, (2) costs of maintaining links with immediate neighbors, (3) benefits from indirect neighbors, (4) bridging benefits, and (5) network entry fee. Based on this model, we analyze relevant network topologies such as star graph, complete graph, bipartite Turan graph, and multiple stars with interconnected centers, and derive a set of sufficient conditions under which these topologies emerge as pairwise stable networks. We also study the social welfare properties of the above topologies.

A Multi-phase Approach for Improving Information Diffusion in Social Networks

For maximizing influence spread in a social network, given a certain budget on the number of seed nodes, we investigate the effects of selecting and activating the seed nodes in multiple phases. In particular, we formulate an appropriate objective function for two-phase influence maximization under the independent cascade model, investigate its properties, and propose algorithms for determining the seed nodes in the two phases. We also study the problem of determining an optimal budget-split and delay between the two phases.