We will create a comprehensive computational drug discovery platform by enhancing a novel technique for a dynamic, fragment based, screening of small molecule compounds against the three dimensional structures of multiple protein targets from infectious disease causing pathogens, followed by prospective in vitro and in vivo experimental verification. We will further modify the most promising lead candidates computationally and screen them against all known human proteins and variants simultaneously to assess for side effects against essential proteins, and to ensure that they possess safe and effective absorption, distribution, metabolism, and excretion profiles against major proteins in known drug delivery pathways. The top ranking leads will again be experimentally verified, and the computational protocol will be iteratively refined using machine learning techniques. We will initially focus on discovering preclinical drug candidates against infections caused by all eight human herpes viruses (HHVs). This virus family infects billions of humans worldwide every year and is the source of significant mortality in immunocompromised patients. Broad spectrum therapeutics against these key pathogens will benefit the entire global community. In contrast to other computational efforts, my group has successfuly applied and experimentally verified their predictions of inhibitors to treat herpes, malaria, and dengue. This was accomplished at a fraction of the time, effort, and cost typically required by pharmaceutical companies. Our significant successes thus far attest to the efficacy of our drug discovery technologies. The Pioneer Award funds will therefore allow us to bridge the gap of discovering computationally predicted lead compounds and demonstrating their preclinical effectiveness for further clinical and therapeutic use. The ultimate goal is to create a comprehensive computational drug discovery pipeline, applicable to any disease, thereby increasing the success rate and reducing the risk, cost, and time associated with traditional drug discovery methods.
This Pioneer award application will focus on the creation and improvement of computational methods to develop broad spectrum therapeutics against any infectious or inherited disease. Pathogens of focus include all human herpes viruses (HHVs), which infect billions worldwide every year, with a significant mortality rate in immunocompromised patients;yet limited therapeutics exist for many of these viruses and virus populations are becoming resistant to current drugs. The ultimate goal is to create a comprehensive computational drug discovery pipeline, applicable to any disease, thereby increasing the success rate and reducing the risk, cost, and time associated with traditional drug discovery methods.
|Sethi, Geetika; Chopra, Gaurav; Samudrala, Ram (2015) Multiscale modelling of relationships between protein classes and drug behavior across all diseases using the CANDO platform. Mini Rev Med Chem 15:705-17|
|Matasci, Naim; Hung, Ling-Hong; Yan, Zhixiang et al. (2014) Data access for the 1,000 Plants (1KP) project. Gigascience 3:17|
|Hung, Ling-Hong; Samudrala, Ram (2014) fast_protein_cluster: parallel and optimized clustering of large-scale protein modeling data. Bioinformatics 30:1774-6|
|Minie, Mark; Chopra, Gaurav; Sethi, Geetika et al. (2014) CANDO and the infinite drug discovery frontier. Drug Discov Today 19:1353-63|
|Laurenzi, Adrian; Hung, Ling-Hong; Samudrala, Ram (2013) Structure prediction of partial-length protein sequences. Int J Mol Sci 14:14892-907|
|Lertkiatmongkol, Panida; Assawamakin, Anunchai; White, George et al. (2013) Correction: Distal Effect of Amino Acid Substitutions in CYP2C9 Polymorphic Variants Causes Differences in Interatomic Interactions against (S)-Warfarin. PLoS One 8:|
|Afzal, Ahmed J; Srour, Ali; Goil, Abhishek et al. (2013) Homo-dimerization and ligand binding by the leucine-rich repeat domain at RHG1/RFS2 underlying resistance to two soybean pathogens. BMC Plant Biol 13:43|
|Goldman, Aaron David; Baross, John A; Samudrala, Ram (2012) The enzymatic and metabolic capabilities of early life. PLoS One 7:e39912|
|Martinez-Avila, Olga; Wu, Shenping; Kim, Seung Joong et al. (2012) Self-assembly of filamentous amelogenin requires calcium and phosphate: from dimers via nanoribbons to fibrils. Biomacromolecules 13:3494-502|
|Hung, Ling-Hong; Samudrala, Ram (2012) Accelerated protein structure comparison using TM-score-GPU. Bioinformatics 28:2191-2|
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