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Chemical genomics (or chemogenomics) is an interdisciplinary research that utilizes chemicals/drugs and genome-wide data to systematically identify and analyze chemicals-protein interactions for the purpose of enhancing new drug design. Computational chemogenomics draws from the cheminformatics and bioinformatics disciplines to produce useful information systems for researchers in pursuit of chemogenomics data, predictive modeling, as well as techniques in ligand- and structure-based drug design. In this regard, there are fast growing andlarge volume of relevant scientific data and information generated, albeit scattered in the literature. It is a challenge for scientists to characterize the molecular interaction networks in chemical genomics scale for pharmacotherapy. Herein, we have established cloud computing chemogenomics knowledgebase drug discovery (CloudDD) platform with our advanced GPU-accelerated machine learning/cheminformatics/bioinformatics algorithms and tools. These include online programs (TargetHunter, HTDocking, LiCABEDS classifier, ANN-QSAR and BBB predictors, etc) and diseases domain-specific chemogenomics databases (multiple myeloma,liver fibrosis, Alzheimer’s disease, etc). It transforms the one-target-one-drug development process to a new multi-target-multi-drug paradigm; as such it is perfect for thestudy of polydrug polypharmacology networks of drugs or chemicals for drug repurposing and new drug discovery.Such a cloud computing server will augment our capacity to benefit the broad research community and will help break the knowledge barrier, reduce costs, and accelerate advances in computer-aided drug design by consolidating existing data and computational technology. Ultimately, it will effectively assist medicinal chemists to conduct “virtual to real” translational research for target identification and drug design discovery. (CloudDD. Cloud computing chemogenomics knowledgebase platform for drug discovery, Xiang-Qun (Sean) Xie)
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Last date updated on July, 2014

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