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G. g. cholinergic, prostanoid modulators). While instrumental to get insights into the design strategies of GPCRs modulators, this work provides novel clues on the molecular mechanisms that may underlie the modulation of this class of receptors. References 1. , Groom CR. The druggable genome. Nat Rev Drug Discov. 2002, 1, 727-30. 2. , Hopkins A. Navigating chemical space for biology and medicine. Nature, 2004, 432, 855-861. 3. Bleicher K. , Bohm H. , Muller, K. & Alanine, A. I. Hit and lead generation: beyond high-throughput screening.
The further blind tests on seven mostly high-potent candidates (not originally in the training subset) also show very high accuracies. Finally, six new ligands are designed for optimal binding based on our predictions. The binding mechanism of this HIV-1RT receptor is also analyzed in detail. For the influenza antigen-receptor and antigen-antibody binding, the goal is to identify which mutations on the viral glycoprotein hemagglutinin (HA) might cause its receptor binding specificity to switch from avian to human, and which mutations might cause its escape of antibody neutralization, through large scale Free Energy Perturbation calculations.
In the past QSAR modelling was a slow process and often of limited use to medicinal chemistry projects. New pipelining technology now makes it easier to build and update QSAR models fully automatically so that such models can use the latest available data to produce robust local and global predictive in silico physchem and ADMET models [5-7]. Drug discovery teams have therefore now access to the best and latest models which can be updated daily, weekly, or monthly. Automation also ensures that all data is being used for all projects.