The posttranscriptional gene silencing mechanism initially mistaken as co-suppression but later identified as RNA interference mediated and regulated by small interfering RNAs (siRNAs), and microRNAs (miRNAs) has gradually emerged as a landmark discovery of the last decade. siRNA-based therapeutics is currently being investigated as an emerging opportunity for healthcare. The lack of structural data of the RNA-induced silencing complex and its key players has hindered the progress of utilization of this unique mechanism in the betterment of humanity. Crystallographic information regarding the Argonaute (Ago)-DNA-RNA complexes have helped in understanding the chemistry of the complex, but other valuable structural details still remain elusive. It is an immediate requirement to understand the exact mechanisms of interactions that occur between the key players of the microprocessor complex or for that matter the holo-RISC. Unless these interaction maps are obtained, complete effective usage and manipulation of this natural phenomenon shall remain uphill tasks for researchers worldwide. To harness the complete potential of siRNAs as therapeutic agents, various chemical modifications need to be performed to prevent nuclease attack, immune activation, increase the specificity of the interaction, and improve pharmacodynamics of the interacting components. Computational molecular dynamics simulations provide a probabilistic alternative for studying such complex structures. Both flexible and rigid docking processes can be utilized to understand the specificities of interactions as both protein-protein and protein nucleic acid docking algorithms have been implemented in free and licensed softwares, complexes obtained from which can then be subjected to analyses using the various interaction mapping tools to formulate a classical map of the RNAi interactome. In this chapter we attempt to elucidate the interactions of the key members of the holo-RISC complex using molecular docking and simulation. Specific interacting residues having the potential to serve as interacting hotspots were identified.
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