On the behavior of ECN/RED gateways under a large number of TCP flows: Limit theorems

We consider a discrete-time stochastic model of an ECN/RED gateway where competing TCP sources share the link capacity. As the number of competing flows becomes large, the asymptotic queue behavior (normalized by the number of flows) at the gateway can be described by a simple recursion and the throughput behavior of individual TCP flows becomes asymptotically independent. A Central Limit Theorem complement is also presented, yielding a more accurate characterization of the asymptotic queue size. These results suggest a scalable yet accurate model of this complex large-scale stochastic feedback system, and crisply reveal the sources of queue fluctuations. This work was prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. This work was also supported by the Space and Naval Warfare Systems Center—San Diego under Contract No: N66001-00-C-8063. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government.     

Virtual screening for anti-HIV-1 RT and anti-HIV-1 PR inhibitors from the Thai medicinal plants database: a combined docking with neural networks approach

The virtual screening approach for docking small molecules into a known protein structure is a powerful tool for drug design. In this work, a combined docking and neural network approach, using a self-organizing map, has been developed and applied to screen anti-HIV-1 inhibitors for two targets, HIV-1 RT and HIV-1 PR, from active compounds available in the Thai Medicinal Plants Database. Based on nevirapine and calanolide A as reference structures in the HIV-1 RT binding site and XK-263 in the HIV-1 PR binding site, 2,684 compounds in the database were docked into the target enzymes. Self-organizing maps were then generated with respect to three types of pharmacophoric groups. The map of the reference structures were then superimposed on the feature maps of all screened compounds. Only the structures having similar features to the reference compounds were accepted. By using the SOMs, the number of candidates for HIV-1 RT was reduced to six and nine compounds consistent with nevirapine and calanolide A, respectively, as references. For the HIV-1 PR target, there are 135 screened compounds showed good agreement with the XK-263 feature map. These screened compounds will be further tested for their HIV-1 inhibitory affinities. The obtained results indicate that this combined method is clearly helpful to perform the successive screening and to reduce the analyzing step from AutoDock and scoring procedure.