Structure based design, synthesis and biological evaluation of amino phosphonate derivatives as human glucokinase activators.

Glucokinase (GK) is a potential therapeutic target of type 2 diabetes and GK activators (GKAs) represent a promising class of small organic molecules which enhance GK activity. Based on the configuration and conformation of the allosteric site of GK, we have designed a novel class of amino phosphonate derivatives in order to develop potent GKAs. The QSAR model developed using numerous descriptors revealed its potential with the best effective statistical values of RMSE=1.

Design, synthesis, in silico and in vitro studies of novel 4-methylthiazole-5-carboxylic acid derivatives as potent anti-cancer agents.

Since inhibitors of mucin onco proteins are potential targets for breast cancer therapy, a series of novel 4-methylthiazole-5-carboxylic acid (1) derivatives 3a-k were synthesized by the reaction of 1 with SOCl2 followed by different bases/alcohols in the presence of triethylamine. Once synthesized and characterized, their binding modes with MUC1 were studied by molecular docking analysis using Aruglab 4.0.

Molecular designing and in silico evaluation of darunavir derivatives as anticancer agents.

Darunavir is a synthetic nonpeptidic protease inhibitor which has been tested for anticancer properties. To deduce and enhance the anticancer activity of the Darunavir, we have modified its reactive moiety in an effective way. We designed 9 analogues in ChemBioOffice 2010 and minimized using the LigPrep tool of Schrödinger 2011.

Identification of substituted [3, 2-a] pyrimidines as selective antiviral agents: molecular modeling study.

A series of novel substituted dihydropyrimidine and 5H-thiazolo [3, 2-a] pyrimidine derivatives were designed and synthesized as a potential target to discover drugs fighting against the viral diseases. The main objective of the present work is to carry out the QSAR studies for all the series of the compounds starting from 4a to 6j to find out their molecular descriptors and predict the biological properties. All of them are showing the best QSAR descriptors, hence chosen for the prediction of anti-viral activity against Newcastle disease virus (NDV).