Chemogenomics approaches to G-protein coupled receptor lead finding

Computing highly correlated positions using mutual information and graph theory for G protein-coupled receptors

G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families.

Potentials of phenolic molecules of natural origin and their derivatives as anti-HIV agents

Identification of phenolic compounds and their derivatives interfering the several steps of the viral life cycle of the human immunodeficiency virus type 1 (HIV-1) is focused for the development of novel molecules for the treatment of AIDS. Several phenolic compounds isolated and characterized from natural sources have been studied in detail and found to exhibit inhibitory effects against different steps of the HIV-1 life cycle, including virus-cell fusion and virus absorption, reverse transcription, integration (IN) and proteolytic cleavage. In the review, we are summarizing some strong evidences demonstrating several phenolic molecules and their derivatives from natural sources display promising anti-HIV-1 activities. The anti-HIV compounds have been organized in this review according to their mechanism of action in the life cycle of HIV. We also mentioned some findings using in silico approaches, like virtual screening, docking, neural network, etc., and even the chemogenomics and/or functional genomics approaches could be useful for the quick identifying promising new lead anti-HIV molecules without having any other unwanted pharmacological effects. Plants having large amount of phenolic compounds, can be considered as strong sources of molecules for the treatment of HIV-1. Despite the continuous advances made in antiretroviral combination therapy, AIDS has become the leading cause of death in Africa and the fourth worldwide. Today, many research groups are exploring the bio- and chemo-diversity of the plant kingdom to find new and better anti-HIV drugs with novel mechanisms of action.