In Silico Screeing of Natural Compounds as Novel Drug Targets for Treatment of Multiple Myeloma

In Silico Screening of Natural Compounds as Novel Drug Targets for The Treatment of Multiple MyelomaRousselene Larson1 2, Naveen Duhan1, and Rakesh Kaundal1 2 *1Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences; 2Bioinformatics Facility, Center for Integrated BioSystems; Utah State University, Logan, UT 84322 USA* corresponding author (e-mail: rkaundal@usu.edu)Telephone: +1 (435) 797-4117Fax: +1 (435) 797-2766Abstract: Multiple Myeloma (MM) is an incurable hematological malignancy cancer characterized by excessive clonal plasma cell proliferation in the bone marrow. In the United States, MM is the second most prevalent type of cancer that affects about 4 in 100,000 Americans. Toxicity and resistance are correlated with existing therapies for MM, emphasizing the need for novel, effective therapeutics. Due to their pharmacological or biological activity, small molecules found in natural products (many are plants based) provide therapeutic benefits that may increase or decrease human protein expression. In this study, we are performing large scale in silico molecular protein-ligand docking. As a preliminary step, we have prepared ~200,000 natural compounds as ligands and several MM target proteins like CDH1 and CCL22 as receptor molecules. Over 500 target proteins are being tested. These proteins have been found to be present in MM patients that are actually tested for the disease. The protein-ligand complexes obtained from molecular docking will be subjected for molecular dynamics simulation at ~10-100ns to explore the protein and complex conformational energy landscape. Further, a webserver of these docking complexes will be implemented using PHP, HTML5, JQuery, JavaScript. The tool will allow users to select a human MM target protein and natural compound and check their binding affinity with a protein-ligand complex. Additionally, it will provide options to run molecular dynamics simulation on the complex using the High-Performance Computing cluster.